WorldWideScience

Sample records for robot behavior adaptation

  1. Biologically-Inspired Adaptive Obstacle Negotiation Behavior of Hexapod Robots

    DEFF Research Database (Denmark)

    Goldschmidt, Dennis; Wörgötter, Florentin; Manoonpong, Poramate

    2014-01-01

    by these findings, we present an adaptive neural control mechanism for obstacle negotiation behavior in hexapod robots. It combines locomotion control, backbone joint control, local leg reflexes, and neural learning. While the first three components generate locomotion including walking and climbing, the neural...... learning mechanism allows the robot to adapt its behavior for obstacle negotiation with respect to changing conditions, e.g., variable obstacle heights and different walking gaits. By successfully learning the association of an early, predictive signal (conditioned stimulus, CS) and a late, reflex signal...... (unconditioned stimulus, UCS), both provided by ultrasonic sensors at the front of the robot, the robot can autonomously find an appropriate distance from an obstacle to initiate climbing. The adaptive neural control was developed and tested first on a physical robot simulation, and was then successfully...

  2. Biologically-Inspired Adaptive Obstacle Negotiation Behavior of Hexapod Robots

    Directory of Open Access Journals (Sweden)

    Dennis eGoldschmidt

    2014-01-01

    Full Text Available Neurobiological studies have shown that insects are able to adapt leg movements and posture for obstacle negotiation in changing environments. Moreover, the distance to an obstacle where an insect begins to climb is found to be a major parameter for successful obstacle negotiation. Inspired by these findings, we present an adaptive neural control mechanism for obstacle negotiation behavior in hexapod robots. It combines locomotion control, backbone joint control, local leg reflexes, and neural learning. While the first three components generate locomotion including walking and climbing, the neural learning mechanism allows the robot to adapt its behavior for obstacle negotiation with respect to changing conditions, e.g., variable obstacle heights and different walking gaits. By successfully learning the association of an early, predictive signal (conditioned stimulus, CS and a late, reflex signal (unconditioned stimulus, UCS, both provided by ultrasonic sensors at the front of the robot, the robot can autonomously find an appropriate distance from an obstacle to initiate climbing. The adaptive neural control was developed and tested first on a physical robot simulation, and was then successfully transferred to a real hexapod robot, called AMOS II. The results show that the robot can efficiently negotiate obstacles with a height up to 85% of the robot's leg length in simulation and 75% in a real environment.

  3. Adaptive Behavior for Mobile Robots

    Science.gov (United States)

    Huntsberger, Terrance

    2009-01-01

    The term "System for Mobility and Access to Rough Terrain" (SMART) denotes a theoretical framework, a control architecture, and an algorithm that implements the framework and architecture, for enabling a land-mobile robot to adapt to changing conditions. SMART is intended to enable the robot to recognize adverse terrain conditions beyond its optimal operational envelope, and, in response, to intelligently reconfigure itself (e.g., adjust suspension heights or baseline distances between suspension points) or adapt its driving techniques (e.g., engage in a crabbing motion as a switchback technique for ascending steep terrain). Conceived for original application aboard Mars rovers and similar autonomous or semi-autonomous mobile robots used in exploration of remote planets, SMART could also be applied to autonomous terrestrial vehicles to be used for search, rescue, and/or exploration on rough terrain.

  4. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

    International Nuclear Information System (INIS)

    Pin, Francois G.

    2002-01-01

    Robotic tasks are typically defined in Task Space (e.g., the 3-D World), whereas robots are controlled in Joint Space (motors). The transformation from Task Space to Joint Space must consider the task objectives (e.g., high precision, strength optimization, torque optimization), the task constraints (e.g., obstacles, joint limits, non-holonomic constraints, contact or tool task constraints), and the robot kinematics configuration (e.g., tools, type of joints, mobile platform, manipulator, modular additions, locked joints). Commercially available robots are optimized for a specific set of tasks, objectives and constraints and, therefore, their control codes are extremely specific to a particular set of conditions. Thus, there exist a multiplicity of codes, each handling a particular set of conditions, but none suitable for use on robots with widely varying tasks, objectives, constraints, or environments. On the other hand, most DOE missions and tasks are typically ''batches of one''. Attempting to use commercial codes for such work requires significant personnel and schedule costs for re-programming or adding code to the robots whenever a change in task objective, robot configuration, number and type of constraint, etc. occurs. The objective of our project is to develop a ''generic code'' to implement this Task-space to Joint-Space transformation that would allow robot behavior adaptation, in real time (at loop rate), to changes in task objectives, number and type of constraints, modes of controls, kinematics configuration (e.g., new tools, added module). Our specific goal is to develop a single code for the general solution of under-specified systems of algebraic equations that is suitable for solving the inverse kinematics of robots, is useable for all types of robots (mobile robots, manipulators, mobile manipulators, etc.) with no limitation on the number of joints and the number of controlled Task-Space variables, can adapt to real time changes in number and

  5. Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

    Science.gov (United States)

    Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

    2015-01-01

    Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles

  6. Adaptive Robot to Person Encounter by Motion Patterns

    DEFF Research Database (Denmark)

    Andersen, Hans Jørgen; Bak, Thomas; Svenstrup, Mikael

    2009-01-01

    This paper introduces a new method for adaptive control of a robot approaching a person controlled by the person's interest in interaction. For adjustment of the robot behavior a cost function centered in the person is adapted according to an introduced person evaluator method relying on the three...... variables: the distance between the person and the robot, the relative velocity between the two, and position of the person. The person evaluator method determine the person's interest by evaluating the spatial relationship between robot and person in a Case Based Reasoning (CBR) system that is trained...... to determine to which degree the person is interested in interaction. The outcome of the CBR system is used to adapt the cost function around the person, so that the robot's behavior is adapted to the expressed interest. The proposed methods are evaluated by a number of physical experiments that demonstrate...

  7. Fuzzy Behaviors for Control of Mobile Robots

    Directory of Open Access Journals (Sweden)

    Saleh Zein-Sabatto

    2003-02-01

    Full Text Available In this research work, an RWI B-14 robot has been used as the development platform to embody some basic behaviors that can be combined to build more complex robotics behaviors. Emergency, avoid-obstacle, left wall- following, right wall-following, and move-to-point behaviors have been designed and embodied as basic robot behaviors. The basic behaviors developed in this research are designed based on fuzzy control technique and are integrated and coordinated to from complex robotics system. More behaviors can be added into the system as needed. A robot task can be defined by the user and executed by the intelligent robot control system. Testing results showed that fuzzy behaviors made the robot move intelligently and adapt to changes in its environment.

  8. Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

    Directory of Open Access Journals (Sweden)

    Eduard eGrinke

    2015-10-01

    Full Text Available Walking animals, like insects, with little neural computing can effectively perform complex behaviors. They can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a walking robot is a challenging task. In this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors in the network to generate different turning angles with short-term memory for a biomechanical walking robot. The turning information is transmitted as descending steering signals to the locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations as well as escaping from sharp corners or deadlocks. Using backbone joint control embedded in the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments.

  9. Adaptive heterogeneous multi-robot teams

    Energy Technology Data Exchange (ETDEWEB)

    Parker, L.E.

    1998-11-01

    This research addresses the problem of achieving fault tolerant cooperation within small- to medium-sized teams of heterogeneous mobile robots. The author describes a novel behavior-based, fully distributed architecture, called ALLIANCE, that utilizes adaptive action selection to achieve fault tolerant cooperative control in robot missions involving loosely coupled, largely independent tasks. The robots in this architecture possess a variety of high-level functions that they can perform during a mission, and must at all times select an appropriate action based on the requirements of the mission, the activities of other robots, the current environmental conditions, and their own internal states. Since such cooperative teams often work in dynamic and unpredictable environments, the software architecture allows the team members to respond robustly and reliably to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. After presenting ALLIANCE, the author describes in detail the experimental results of an implementation of this architecture on a team of physical mobile robots performing a cooperative box pushing demonstration. These experiments illustrate the ability of ALLIANCE to achieve adaptive, fault-tolerant cooperative control amidst dynamic changes in the capabilities of the robot team.

  10. An Adaptive Robot Game

    DEFF Research Database (Denmark)

    Hansen, Søren Tranberg; Svenstrup, Mikael; Dalgaard, Lars

    2010-01-01

    The goal of this paper is to describe an adaptive robot game, which motivates elderly people to do a regular amount of physical exercise while playing. One of the advantages of robot based games is that the initiative to play can be taken autonomously by the robot. In this case, the goal is to im......The goal of this paper is to describe an adaptive robot game, which motivates elderly people to do a regular amount of physical exercise while playing. One of the advantages of robot based games is that the initiative to play can be taken autonomously by the robot. In this case, the goal...... is to improve the mental and physical state of the user by playing a physical game with the robot. Ideally, a robot game should be simple to learn but difficult to master, providing an appropriate degree of challenge for players with different skills. In order to achieve that, the robot should be able to adapt...

  11. A Case-Study for Life-Long Learning and Adaptation in Cooperative Robot Teams

    International Nuclear Information System (INIS)

    Parker, L.E.

    1999-01-01

    While considerable progress has been made in recent years toward the development of multi-robot teams, much work remains to be done before these teams are used widely in real-world applications. Two particular needs toward this end are the development of mechanisms that enable robot teams to generate cooperative behaviors on their own, and the development of techniques that allow these teams to autonomously adapt their behavior over time as the environment or the robot team changes. This paper proposes the use of the Cooperative Multi-Robot Observation of Multiple Moving Targets (CMOMMT) application as a rich domain for studying the issues of multi-robot learning and adaptation. After discussing the need for learning and adaptation in multi-robot teams, this paper describes the CMOMMT application and its relevance to multi-robot learning. We discuss the results of the previously- developed, hand-generated algorithm for CMOMMT and the potential for learning that was discovered from the hand-generated approach. We then describe the early work that has been done (by us and others) to generate multi- robot learning techniques for the CMOMMT application, as well as our ongoing research to develop approaches that give performance as good, or better, than the hand-generated approach. The ultimate goal of this research is to develop techniques for multi-robot learning and adaptation in the CMOMMT application domain that will generalize to cooperative robot applications in other domains, thus making the practical use of multi-robot teams in a wide variety of real-world applications much closer to reality

  12. Arousal regulation and affective adaptation to human responsiveness by a robot that explores and learns a novel environment.

    Science.gov (United States)

    Hiolle, Antoine; Lewis, Matthew; Cañamero, Lola

    2014-01-01

    In the context of our work in developmental robotics regarding robot-human caregiver interactions, in this paper we investigate how a "baby" robot that explores and learns novel environments can adapt its affective regulatory behavior of soliciting help from a "caregiver" to the preferences shown by the caregiver in terms of varying responsiveness. We build on two strands of previous work that assessed independently (a) the differences between two "idealized" robot profiles-a "needy" and an "independent" robot-in terms of their use of a caregiver as a means to regulate the "stress" (arousal) produced by the exploration and learning of a novel environment, and (b) the effects on the robot behaviors of two caregiving profiles varying in their responsiveness-"responsive" and "non-responsive"-to the regulatory requests of the robot. Going beyond previous work, in this paper we (a) assess the effects that the varying regulatory behavior of the two robot profiles has on the exploratory and learning patterns of the robots; (b) bring together the two strands previously investigated in isolation and take a step further by endowing the robot with the capability to adapt its regulatory behavior along the "needy" and "independent" axis as a function of the varying responsiveness of the caregiver; and (c) analyze the effects that the varying regulatory behavior has on the exploratory and learning patterns of the adaptive robot.

  13. Robots that can adapt like animals.

    Science.gov (United States)

    Cully, Antoine; Clune, Jeff; Tarapore, Danesh; Mouret, Jean-Baptiste

    2015-05-28

    Robots have transformed many industries, most notably manufacturing, and have the power to deliver tremendous benefits to society, such as in search and rescue, disaster response, health care and transportation. They are also invaluable tools for scientific exploration in environments inaccessible to humans, from distant planets to deep oceans. A major obstacle to their widespread adoption in more complex environments outside factories is their fragility. Whereas animals can quickly adapt to injuries, current robots cannot 'think outside the box' to find a compensatory behaviour when they are damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. A promising approach to reducing robot fragility involves having robots learn appropriate behaviours in response to damage, but current techniques are slow even with small, constrained search spaces. Here we introduce an intelligent trial-and-error algorithm that allows robots to adapt to damage in less than two minutes in large search spaces without requiring self-diagnosis or pre-specified contingency plans. Before the robot is deployed, it uses a novel technique to create a detailed map of the space of high-performing behaviours. This map represents the robot's prior knowledge about what behaviours it can perform and their value. When the robot is damaged, it uses this prior knowledge to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a behaviour that compensates for the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new algorithm will enable more robust, effective, autonomous robots, and may shed light on the principles

  14. Behavior-based obstacle avoidance capability for biologically inspired eight-legged walking robot

    International Nuclear Information System (INIS)

    Izzeldin Ibrahim Mohd; Shamsudin M Amin; Adel Ali Syed Al-Jumaily

    1999-01-01

    Behavior-based approach has proven to be useful in making mobile robot working in real world situations. Since the behaviors are responsible for managing the interaction between the robots and its environment, observing their use can be exploited to model these interactions. A real-time obstacle avoidance algorithm has been developed and implemented. This algorithm permits the detection of unknown obstacle simultaneously with the steering of the mobile robot to avoid collisions and advance toward the target. In our approach the robot is initially given a set of behavior-producing modules to choose from, and the algorithm provides a memory-based approach to dynamically adapt the selection of the behaviors according to the history of their use. We developed a set of algorithms, which uses Subsumption Architecture (SA) for controlling an eight-legged walking robot operating in closed vicinity. This paper describes a successful application of these algorithms to Oct-Ib robot and experimental results of the robot navigating in complex environment. (Author)

  15. Dynamical Behavior of Multi-Robot Systems Using Lattice Gas Automata

    Energy Technology Data Exchange (ETDEWEB)

    Cameron, S.M.; Robinett, R.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1999-03-11

    Recent attention has been given to the deployment of an adaptable sensor array realized by multi-robotic systems. Our group has been studying the collective behavior of autonomous, multi-agent systems and their applications in the area of remote-sensing and emerging threats. To accomplish such tasks, an interdisciplinary research effort at Sandia National Laboratories are conducting tests in the fields of sensor technology, robotics, and multi-robotic and multi-agents architectures. Our goal is to coordinate a constellation of point sensors that optimizes spatial coverage and multivariate signal analysis using unmanned robotic vehicles (e.g., RATLERs, Robotic All-ten-sin Lunar Exploration Rover-class vehicles). Overall design methodology is to evolve complex collective behaviors realized through simple interaction (kinetic) physics and artificial intelligence to enable real-time operational responses to emerging threats. This paper focuses on our recent work understanding the dynamics of many-body systems using the physics-based hydrodynamic model of lattice gas automata. Three design features are investigated. One, for single-speed robots, a hexagonal nearest-neighbor interaction topology is necessary to preserve standard hydrodynamic flow. Two, adaptability, defined by the swarm's deformation rate, can be controlled through the hydrodynamic viscosity term, which, in turn, is defined by the local robotic interaction rules. Three, due to the inherent non-linearity of the dynamical equations describing large ensembles, development of stability criteria ensuring convergence to equilibrium states is developed by scaling information flow rates relative to a swarm's hydrodynamic flow rate. An initial test case simulates a swarm of twenty-five robots that maneuvers past an obstacle while following a moving target. A genetic algorithm optimizes applied nearest-neighbor forces in each of five spatial regions distributed over the simulation domain. Armed with

  16. Soft Ultrathin Electronics Innervated Adaptive Fully Soft Robots.

    Science.gov (United States)

    Wang, Chengjun; Sim, Kyoseung; Chen, Jin; Kim, Hojin; Rao, Zhoulyu; Li, Yuhang; Chen, Weiqiu; Song, Jizhou; Verduzco, Rafael; Yu, Cunjiang

    2018-03-01

    Soft robots outperform the conventional hard robots on significantly enhanced safety, adaptability, and complex motions. The development of fully soft robots, especially fully from smart soft materials to mimic soft animals, is still nascent. In addition, to date, existing soft robots cannot adapt themselves to the surrounding environment, i.e., sensing and adaptive motion or response, like animals. Here, compliant ultrathin sensing and actuating electronics innervated fully soft robots that can sense the environment and perform soft bodied crawling adaptively, mimicking an inchworm, are reported. The soft robots are constructed with actuators of open-mesh shaped ultrathin deformable heaters, sensors of single-crystal Si optoelectronic photodetectors, and thermally responsive artificial muscle of carbon-black-doped liquid-crystal elastomer (LCE-CB) nanocomposite. The results demonstrate that adaptive crawling locomotion can be realized through the conjugation of sensing and actuation, where the sensors sense the environment and actuators respond correspondingly to control the locomotion autonomously through regulating the deformation of LCE-CB bimorphs and the locomotion of the robots. The strategy of innervating soft sensing and actuating electronics with artificial muscles paves the way for the development of smart autonomous soft robots. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

    International Nuclear Information System (INIS)

    Pin, Francois G.

    2003-01-01

    Our overall objective is the development of a generalized methodology and code for the automated generation of the kinematics equations of robots and for the analytical solution of their motion planning equations subject to time-varying constraints, behavioral objectives and modular configuration

  18. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

    International Nuclear Information System (INIS)

    Pin, Grancois G.

    2004-01-01

    Our overall objective is the development of a generalized methodology and code for the automated generation of the kinematics equations of robots and for the analytical solution of their motion planning equations subject to time-varying constraints, behavioral objectives, and modular configuration

  19. Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

    DEFF Research Database (Denmark)

    Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin

    2015-01-01

    correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking...... dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural...... mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online...

  20. Timing of Multimodal Robot Behaviors during Human-Robot Collaboration

    DEFF Research Database (Denmark)

    Jensen, Lars Christian; Fischer, Kerstin; Suvei, Stefan-Daniel

    2017-01-01

    In this paper, we address issues of timing between robot behaviors in multimodal human-robot interaction. In particular, we study what effects sequential order and simultaneity of robot arm and body movement and verbal behavior have on the fluency of interactions. In a study with the Care-O-bot, ...... output plays a special role because participants carry their expectations from human verbal interaction into the interactions with robots....

  1. Adaptive learning fuzzy control of a mobile robot

    International Nuclear Information System (INIS)

    Tsukada, Akira; Suzuki, Katsuo; Fujii, Yoshio; Shinohara, Yoshikuni

    1989-11-01

    In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)

  2. L-ALLIANCE: a mechanism for adaptive action selection in heterogeneous multi-robot teams

    Energy Technology Data Exchange (ETDEWEB)

    Parker, L.E.

    1995-11-01

    In practical applications of robotics, it is usually quite difficult, if not impossible, for the system designer to fully predict the environmental states in which the robots will operate. The complexity of the problem is further increased when dealing with teams of robots which themselves may be incompletely known and characterized in advance. It is thus highly desirable for robot teams to be able to adapt their performance during the mission due to changes in the environment, or to changes in other robot team members. In previous work, we introduced a behavior-based mechanism called the ALLIANCE architecture -- that facilitates the fault tolerant cooperative control of multi-robot teams. However, this previous work did not address the issue of how to dynamically update the control parameters during a mission to adapt to ongoing changes in the environment or in the robot team, and to ensure the efficiency of the collective team actions. In this paper, we address this issue by proposing the L-ALLIANCE mechanism, which defines an automated method whereby robots can use knowledge learned from previous experience to continually improve their collective action selection when working on missions composed of loosely coupled, discrete subtasks. This ability to dynamically update robotic control parameters provides a number of distinct advantages: it alleviates the need for human tuning of control parameters, it facilitates the use of custom-designed multi-robot teams for any given application, it improves the efficiency of the mission performance, and It allows robots to continually adapt their performance over time due to changes in the robot team and/or the environment. We describe the L-ALLIANCE mechanism, present the results of various alternative update strategies we investigated, present the formal model of the L-ALLIANCE mechanism, and present the results of a simple proof of concept implementation on a small team of heterogeneous mobile robots.

  3. Distributed Recurrent Neural Forward Models with Synaptic Adaptation and CPG-based control for Complex Behaviors of Walking Robots

    Directory of Open Access Journals (Sweden)

    Sakyasingha eDasgupta

    2015-09-01

    Full Text Available Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures with the underlying neural mechanisms. The neural mechanisms consist of 1 central pattern generator based control for generating basic rhythmic patterns and coordinated movements, 2 distributed (at each leg recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and 3 searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps as well as climbing over high obstacles. Furthermore we demonstrate that the newly developed recurrent network based approach to sensorimotor prediction outperforms the previous state of the art adaptive neuron

  4. Towards Behavior Control for Evolutionary Robot Based on RL with ENN

    Directory of Open Access Journals (Sweden)

    Jingan Yang

    2012-03-01

    Full Text Available This paper proposes a behavior-switching control strategy of anevolutionary robotics based on Artificial NeuralNetwork (ANN and Genetic Algorithms (GA. This method is able not only to construct thereinforcement learning models for autonomous robots and evolutionary robot modules thatcontrol behaviors and reinforcement learning environments, and but also to perform thebehavior-switching control and obstacle avoidance of an evolutionary robotics (ER intime-varying environments with static and moving obstacles by combining ANN and GA.The experimental results on thebasic behaviors and behavior-switching control have demonstrated that ourmethod can perform the decision-making strategy and parameters set opimization ofFNN and GA by learning and can escape successfully from the trap of a localminima and avoid \\emph{"motion deadlock" status} of humanoid soccer robotics agents,and reduce the oscillation of the planned trajectory betweenthe multiple obstacles by crossover and mutation. Some results of the proposed algorithmhave been successfully applied to our simulation humanoid robotics soccer team CIT3Dwhich won \\emph{the 1st prize} of RoboCup Championship and ChinaOpen2010 (July 2010 and \\emph{the $2^{nd}$ place}of the official RoboCup World Championship on 5-11 July, 2011 in Istanbul, Turkey.As compared with the conventional behavior network and the adaptive behavior method,the genetic encoding complexity of our algorithm is simplified, and the networkperformance and the {\\em convergence rate $\\rho$} have been greatlyimproved.

  5. Pose Estimation and Adaptive Robot Behaviour for Human-Robot Interaction

    DEFF Research Database (Denmark)

    Svenstrup, Mikael; Hansen, Søren Tranberg; Andersen, Hans Jørgen

    2009-01-01

    Abstract—This paper introduces a new method to determine a person’s pose based on laser range measurements. Such estimates are typically a prerequisite for any human-aware robot navigation, which is the basis for effective and timeextended interaction between a mobile robot and a human. The robot......’s pose. The resulting pose estimates are used to identify humans who wish to be approached and interacted with. The interaction motion of the robot is based on adaptive potential functions centered around the person that respect the persons social spaces. The method is tested in experiments...

  6. Behavior Selection of Mobile Robot Based on Integration of Multimodal Information

    Science.gov (United States)

    Chen, Bin; Kaneko, Masahide

    Recently, biologically inspired robots have been developed to acquire the capacity for directing visual attention to salient stimulus generated from the audiovisual environment. On purpose to realize this behavior, a general method is to calculate saliency maps to represent how much the external information attracts the robot's visual attention, where the audiovisual information and robot's motion status should be involved. In this paper, we represent a visual attention model where three modalities, that is, audio information, visual information and robot's motor status are considered, while the previous researches have not considered all of them. Firstly, we introduce a 2-D density map, on which the value denotes how much the robot pays attention to each spatial location. Then we model the attention density using a Bayesian network where the robot's motion statuses are involved. Secondly, the information from both of audio and visual modalities is integrated with the attention density map in integrate-fire neurons. The robot can direct its attention to the locations where the integrate-fire neurons are fired. Finally, the visual attention model is applied to make the robot select the visual information from the environment, and react to the content selected. Experimental results show that it is possible for robots to acquire the visual information related to their behaviors by using the attention model considering motion statuses. The robot can select its behaviors to adapt to the dynamic environment as well as to switch to another task according to the recognition results of visual attention.

  7. Goal inferences about robot behavior : goal inferences and human response behaviors

    NARCIS (Netherlands)

    Broers, H.A.T.; Ham, J.R.C.; Broeders, R.; De Silva, P.; Okada, M.

    2014-01-01

    This explorative research focused on the goal inferences human observers draw based on a robot's behavior, and the extent to which those inferences predict people's behavior in response to that robot. Results show that different robot behaviors cause different response behavior from people.

  8. Evolutionary online behaviour learning and adaptation in real robots.

    Science.gov (United States)

    Silva, Fernando; Correia, Luís; Christensen, Anders Lyhne

    2017-07-01

    Online evolution of behavioural control on real robots is an open-ended approach to autonomous learning and adaptation: robots have the potential to automatically learn new tasks and to adapt to changes in environmental conditions, or to failures in sensors and/or actuators. However, studies have so far almost exclusively been carried out in simulation because evolution in real hardware has required several days or weeks to produce capable robots. In this article, we successfully evolve neural network-based controllers in real robotic hardware to solve two single-robot tasks and one collective robotics task. Controllers are evolved either from random solutions or from solutions pre-evolved in simulation. In all cases, capable solutions are found in a timely manner (1 h or less). Results show that more accurate simulations may lead to higher-performing controllers, and that completing the optimization process in real robots is meaningful, even if solutions found in simulation differ from solutions in reality. We furthermore demonstrate for the first time the adaptive capabilities of online evolution in real robotic hardware, including robots able to overcome faults injected in the motors of multiple units simultaneously, and to modify their behaviour in response to changes in the task requirements. We conclude by assessing the contribution of each algorithmic component on the performance of the underlying evolutionary algorithm.

  9. An adaptive inverse kinematics algorithm for robot manipulators

    Science.gov (United States)

    Colbaugh, R.; Glass, K.; Seraji, H.

    1990-01-01

    An adaptive algorithm for solving the inverse kinematics problem for robot manipulators is presented. The algorithm is derived using model reference adaptive control (MRAC) theory and is computationally efficient for online applications. The scheme requires no a priori knowledge of the kinematics of the robot if Cartesian end-effector sensing is available, and it requires knowledge of only the forward kinematics if joint position sensing is used. Computer simulation results are given for the redundant seven-DOF robotics research arm, demonstrating that the proposed algorithm yields accurate joint angle trajectories for a given end-effector position/orientation trajectory.

  10. SIMULATION OF ADAPTIVE BEHAVIOR IN THE CONTEXT OF SOLVING AN AUTONOMOUS ROBOTIC VEHICLE MOTION TASK ON TWO-DIMENSIONAL PLANE WITH OBSTACLES

    Directory of Open Access Journals (Sweden)

    R. A. Prakapovich

    2014-01-01

    Full Text Available An adaptive neurocontroller for autonomous robotic vehicle control, which is designed to generate control signals (according to preprogrammed motion algorithm and to develop individual reactions to some external impacts during functioning process, that allows the robot to adapt to external environment changes, is suggested. To debug and test the proposed neurocontroller a specially designed program, able to simulate the sensory and executive systems operation of the robotic vehicle, is used.

  11. A neural learning classifier system with self-adaptive constructivism for mobile robot control.

    Science.gov (United States)

    Hurst, Jacob; Bull, Larry

    2006-01-01

    For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

  12. Robotic intelligence kernel

    Science.gov (United States)

    Bruemmer, David J [Idaho Falls, ID

    2009-11-17

    A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

  13. Direct adaptive control of a PUMA 560 industrial robot

    Science.gov (United States)

    Seraji, Homayoun; Lee, Thomas; Delpech, Michel

    1989-01-01

    The implementation and experimental validation of a new direct adaptive control scheme on a PUMA 560 industrial robot is described. The testbed facility consists of a Unimation PUMA 560 six-jointed robot and controller, and a DEC MicroVAX II computer which hosts the Robot Control C Library software. The control algorithm is implemented on the MicroVAX which acts as a digital controller for the PUMA robot, and the Unimation controller is effectively bypassed and used merely as an I/O device to interface the MicroVAX to the joint motors. The control algorithm for each robot joint consists of an auxiliary signal generated by a constant-gain Proportional plus Integral plus Derivative (PID) controller, and an adaptive position-velocity (PD) feedback controller with adjustable gains. The adaptive independent joint controllers compensate for the inter-joint couplings and achieve accurate trajectory tracking without the need for the complex dynamic model and parameter values of the robot. Extensive experimental results on PUMA joint control are presented to confirm the feasibility of the proposed scheme, in spite of strong interactions between joint motions. Experimental results validate the capabilities of the proposed control scheme. The control scheme is extremely simple and computationally very fast for concurrent processing with high sampling rates.

  14. Adaptive Control Methods for Soft Robots

    Data.gov (United States)

    National Aeronautics and Space Administration — I propose to develop methods for soft and inflatable robots that will allow the control system to adapt and change control parameters based on changing conditions...

  15. Combining Environment-Driven Adaptation and Task-Driven Optimisation in Evolutionary Robotics

    NARCIS (Netherlands)

    Haasdijk, E.W.; Bredeche, Nicolas; Eiben, A.E.

    2014-01-01

    Embodied evolutionary robotics is a sub-field of evolutionary robotics that employs evolutionary algorithms on the robotic hardware itself, during the operational period, i.e., in an on-line fashion. This enables robotic systems that continuously adapt, and are therefore capable of (re-)adjusting

  16. Toward Speech and Nonverbal Behaviors Integration for Humanoid Robot

    Directory of Open Access Journals (Sweden)

    Wei Wang

    2012-09-01

    Full Text Available It is essential to integrate speeches and nonverbal behaviors for a humanoid robot in human-robot interaction. This paper presents an approach using multi-object genetic algorithm to match the speeches and behaviors automatically. Firstly, with humanoid robot's emotion status, we construct a hierarchical structure to link voice characteristics and nonverbal behaviors. Secondly, these behaviors corresponding to speeches are matched and integrated into an action sequence based on genetic algorithm, so the robot can consistently speak and perform emotional behaviors. Our approach takes advantage of relevant knowledge described by psychologists and nonverbal communication. And from experiment results, our ultimate goal, implementing an affective robot to act and speak with partners vividly and fluently, could be achieved.

  17. Adaptive training algorithm for robot-assisted upper-arm rehabilitation, applicable to individualised and therapeutic human-robot interaction.

    Science.gov (United States)

    Chemuturi, Radhika; Amirabdollahian, Farshid; Dautenhahn, Kerstin

    2013-09-28

    Rehabilitation robotics is progressing towards developing robots that can be used as advanced tools to augment the role of a therapist. These robots are capable of not only offering more frequent and more accessible therapies but also providing new insights into treatment effectiveness based on their ability to measure interaction parameters. A requirement for having more advanced therapies is to identify how robots can 'adapt' to each individual's needs at different stages of recovery. Hence, our research focused on developing an adaptive interface for the GENTLE/A rehabilitation system. The interface was based on a lead-lag performance model utilising the interaction between the human and the robot. The goal of the present study was to test the adaptability of the GENTLE/A system to the performance of the user. Point-to-point movements were executed using the HapticMaster (HM) robotic arm, the main component of the GENTLE/A rehabilitation system. The points were displayed as balls on the screen and some of the points also had a real object, providing a test-bed for the human-robot interaction (HRI) experiment. The HM was operated in various modes to test the adaptability of the GENTLE/A system based on the leading/lagging performance of the user. Thirty-two healthy participants took part in the experiment comprising of a training phase followed by the actual-performance phase. The leading or lagging role of the participant could be used successfully to adjust the duration required by that participant to execute point-to-point movements, in various modes of robot operation and under various conditions. The adaptability of the GENTLE/A system was clearly evident from the durations recorded. The regression results showed that the participants required lower execution times with the help from a real object when compared to just a virtual object. The 'reaching away' movements were longer to execute when compared to the 'returning towards' movements irrespective of the

  18. Estimating Position of Mobile Robots From Omnidirectional Vision Using an Adaptive Algorithm.

    Science.gov (United States)

    Li, Luyang; Liu, Yun-Hui; Wang, Kai; Fang, Mu

    2015-08-01

    This paper presents a novel and simple adaptive algorithm for estimating the position of a mobile robot with high accuracy in an unknown and unstructured environment by fusing images of an omnidirectional vision system with measurements of odometry and inertial sensors. Based on a new derivation where the omnidirectional projection can be linearly parameterized by the positions of the robot and natural feature points, we propose a novel adaptive algorithm, which is similar to the Slotine-Li algorithm in model-based adaptive control, to estimate the robot's position by using the tracked feature points in image sequence, the robot's velocity, and orientation angles measured by odometry and inertial sensors. It is proved that the adaptive algorithm leads to global exponential convergence of the position estimation errors to zero. Simulations and real-world experiments are performed to demonstrate the performance of the proposed algorithm.

  19. Folk-Psychological Interpretation of Human vs. Humanoid Robot Behavior: Exploring the Intentional Stance toward Robots.

    Science.gov (United States)

    Thellman, Sam; Silvervarg, Annika; Ziemke, Tom

    2017-01-01

    People rely on shared folk-psychological theories when judging behavior. These theories guide people's social interactions and therefore need to be taken into consideration in the design of robots and other autonomous systems expected to interact socially with people. It is, however, not yet clear to what degree the mechanisms that underlie people's judgments of robot behavior overlap or differ from the case of human or animal behavior. To explore this issue, participants ( N = 90) were exposed to images and verbal descriptions of eight different behaviors exhibited either by a person or a humanoid robot. Participants were asked to rate the intentionality, controllability and desirability of the behaviors, and to judge the plausibility of seven different types of explanations derived from a recently proposed psychological model of lay causal explanation of human behavior. Results indicate: substantially similar judgments of human and robot behavior, both in terms of (1a) ascriptions of intentionality/controllability/desirability and in terms of (1b) plausibility judgments of behavior explanations; (2a) high level of agreement in judgments of robot behavior - (2b) slightly lower but still largely similar to agreement over human behaviors; (3) systematic differences in judgments concerning the plausibility of goals and dispositions as explanations of human vs. humanoid behavior. Taken together, these results suggest that people's intentional stance toward the robot was in this case very similar to their stance toward the human.

  20. Navigasi Berbasis Behavior dan Fuzzy Logic pada Simulasi Robot Bergerak Otonom

    Directory of Open Access Journals (Sweden)

    Rendyansyah

    2016-03-01

    Full Text Available Mobile robot is the robotic mechanism that is able to moved automatically. The movement of the robot automatically require a navigation system. Navigation is a method for determining the robot motion. In this study, using a method developed robot navigation behavior with fuzzy logic. The behavior of the robot is divided into several modules, such as walking, avoid obstacles, to follow walls, corridors and conditions of u-shape. In this research designed mobile robot simulation in a visual programming. Robot is equipped with seven distance sensor and divided into several groups to test the behavior that is designed, so that the behavior of the robot generate speed and steering control. Based on experiments that have been conducted shows that mobile robot simulation can run smooth on many conditions. This proves that the implementation of the formation of behavior and fuzzy logic techniques on the robot working well

  1. Model and Behavior-Based Robotic Goalkeeper

    DEFF Research Database (Denmark)

    Lausen, H.; Nielsen, J.; Nielsen, M.

    2003-01-01

    This paper describes the design, implementation and test of a goalkeeper robot for the Middle-Size League of RoboCub. The goalkeeper task is implemented by a set of primitive tasks and behaviours coordinated by a 2-level hierarchical state machine. The primitive tasks concerning complex motion...... control are implemented by a non-linear control algorithm, adapted to the different task goals (e.g., follow the ball or the robot posture from local features extracted from images acquired by a catadioptric omni-directional vision system. Most robot parameters were designed based on simulations carried...

  2. Adaptive Nonlinear Tracking for Robotic Walking

    Czech Academy of Sciences Publication Activity Database

    Dolinský, Kamil; Čelikovský, Sergej

    2012-01-01

    Roč. 1, č. 1 (2012), s. 28-35 ISSN 2223-7038 Institutional research plan: CEZ:AV0Z10750506 Keywords : Adaptive control * Kalman filter * walking robots Subject RIV: BC - Control Systems Theory http://lib.physcon.ru/doc?id=9e51935aa5bc

  3. Adaptive Inverse Optimal Control for Rehabilitation Robot Systems Using Actor-Critic Algorithm

    Directory of Open Access Journals (Sweden)

    Fancheng Meng

    2014-01-01

    Full Text Available The higher goal of rehabilitation robot is to aid a person to achieve a desired functional task (e.g., tracking trajectory based on assisted-as-needed principle. To this goal, a new adaptive inverse optimal hybrid control (AHC combining inverse optimal control and actor-critic learning is proposed. Specifically, an uncertain nonlinear rehabilitation robot model is firstly developed that includes human motor behavior dynamics. Then, based on this model, an open-loop error system is formed; thereafter, an inverse optimal control input is designed to minimize the cost functional and a NN-based actor-critic feedforward signal is responsible for the nonlinear dynamic part contaminated by uncertainties. Finally, the AHC controller is proven (through a Lyapunov-based stability analysis to yield a global uniformly ultimately bounded stability result, and the resulting cost functional is meaningful. Simulation and experiment on rehabilitation robot demonstrate the effectiveness of the proposed control scheme.

  4. Developing robotic behavior using a genetic programming model

    International Nuclear Information System (INIS)

    Pryor, R.J.

    1998-01-01

    This report describes the methodology for using a genetic programming model to develop tracking behaviors for autonomous, microscale robotic vehicles. The use of such vehicles for surveillance and detection operations has become increasingly important in defense and humanitarian applications. Through an evolutionary process similar to that found in nature, the genetic programming model generates a computer program that when downloaded onto a robotic vehicle's on-board computer will guide the robot to successfully accomplish its task. Simulations of multiple robots engaged in problem-solving tasks have demonstrated cooperative behaviors. This report also discusses the behavior model produced by genetic programming and presents some results achieved during the study

  5. People-Centered Development of a Smart Learning Ecosystem of Adaptive Robots

    DEFF Research Database (Denmark)

    Fischer, Daniel Kjær Bonde; Kristiansen, Jakob; Mariager, Casper

    2019-01-01

    Robots are currently moving out of the laboratory and company floor into more human and social contexts including care, rehabilitation and education. While those robots are usually envisioned as a kind of social interaction partner, we suggest a different approach, where robots become adaptive...

  6. A discrete-time adaptive control scheme for robot manipulators

    Science.gov (United States)

    Tarokh, M.

    1990-01-01

    A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

  7. Neural Behavior Chain Learning of Mobile Robot Actions

    Directory of Open Access Journals (Sweden)

    Lejla Banjanovic-Mehmedovic

    2012-01-01

    Full Text Available This paper presents a visual/motor behavior learning approach, based on neural networks. We propose Behavior Chain Model (BCM in order to create a way of behavior learning. Our behavior-based system evolution task is a mobile robot detecting a target and driving/acting towards it. First, the mapping relations between the image feature domain of the object and the robot action domain are derived. Second, a multilayer neural network for offline learning of the mapping relations is used. This learning structure through neural network training process represents a connection between the visual perceptions and motor sequence of actions in order to grip a target. Last, using behavior learning through a noticed action chain, we can predict mobile robot behavior for a variety of similar tasks in similar environment. Prediction results suggest that the methodology is adequate and could be recognized as an idea for designing different mobile robot behaviour assistance.

  8. An Exploratory Investigation into the Effects of Adaptation in Child-Robot Interaction

    Science.gov (United States)

    Salter, Tamie; Michaud, François; Létourneau, Dominic

    The work presented in this paper describes an exploratory investigation into the potential effects of a robot exhibiting an adaptive behaviour in reaction to a child’s interaction. In our laboratory we develop robotic devices for a diverse range of children that differ in age, gender and ability, which includes children that are diagnosed with cognitive difficulties. As all children vary in their personalities and styles of interaction, it would follow that adaptation could bring many benefits. In this abstract we give our initial examination of a series of trials which explore the effects of a fully autonomous rolling robot exhibiting adaptation (through changes in motion and sound) compared to it exhibiting pre-programmed behaviours. We investigate sensor readings on-board the robot that record the level of ‘interaction’ that the robot receives when a child plays with it and also we discuss the results from analysing video footage looking at the social aspect of the trial.

  9. Implementation of robust adaptive control for robotic manipulator using TMS320C30

    International Nuclear Information System (INIS)

    Han, S. H.

    1996-01-01

    A new adaptive digital control scheme for the robotic manipulator is proposed in this paper. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the adaptive feedforward and feedback controller and PI type time-varying control elements. The control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot. (author)

  10. Friendly network robotics; Friendly network robotics

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    This paper summarizes the research results on the friendly network robotics in fiscal 1996. This research assumes an android robot as an ultimate robot and the future robot system utilizing computer network technology. The robot aiming at human daily work activities in factories or under extreme environments is required to work under usual human work environments. The human robot with similar size, shape and functions to human being is desirable. Such robot having a head with two eyes, two ears and mouth can hold a conversation with human being, can walk with two legs by autonomous adaptive control, and has a behavior intelligence. Remote operation of such robot is also possible through high-speed computer network. As a key technology to use this robot under coexistence with human being, establishment of human coexistent robotics was studied. As network based robotics, use of robots connected with computer networks was also studied. In addition, the R-cube (R{sup 3}) plan (realtime remote control robot technology) was proposed. 82 refs., 86 figs., 12 tabs.

  11. Robotic Fish to Aid Animal Behavior Studies and Informal Science Learning

    Science.gov (United States)

    Phamduy, Paul

    The application of robotic fish in the fields of animal behavior and informal science learning are new and relatively untapped. In the context of animal behavior studies, robotic fish offers a consistent and customizable stimulus that could contribute to dissect the determinants of social behavior. In the realm of informal science learning, robotic fish are gaining momentum for the possibility of educating the general public simultaneously on fish physiology and underwater robotics. In this dissertation, the design and development of a number of robotic fish platforms and prototypes and their application in animal behavioral studies and informal science learning settings are presented. Robotic platforms for animal behavioral studies focused on the utilization replica or same scale prototypes. A novel robotic fish platform, featuring a three-dimensional swimming multi-linked robotic fish, was developed with three control modes varying in the level of robot autonomy offered. This platform was deployed at numerous science festivals and science centers, to obtain data on visitor engagement and experience.

  12. Adaptive Robot Control – An Experimental Comparison

    Directory of Open Access Journals (Sweden)

    Francesco Alonge

    2012-11-01

    Full Text Available This paper deals with experimental comparison between stable adaptive controllers of robotic manipulators based on Model Based Adaptive, Neural Network and Wavelet -Based control. The above control methods were compared with each other in terms of computational efficiency, need for accurate mathematical model of the manipulator and tracking performances. An original management algorithm of the Wavelet Network control scheme has been designed, with the aim of constructing the net automatically during the trajectory tracking, without the need to tune it to the trajectory itself. Experimental tests, carried out on a planar two link manipulator, show that the Wavelet-Based control scheme, with the new management algorithm, outperforms the conventional Model-Based schemes in the presence of structural uncertainties in the mathematical model of the robot, without pre-training and more efficiently than the Neural Network approach.

  13. Adaptation of the IBM ECR [electric cantilever robot] robot to plutonium processing applications

    International Nuclear Information System (INIS)

    Armantrout, G.A.; Pedrotti, L.R.; Halter, E.A.; Crossfield, M.

    1990-12-01

    The changing regulatory climate in the US is adding increasing incentive to reduce operator dose and TRU waste for DOE plutonium processing operations. To help achieve that goal the authors have begun adapting a small commercial overhead gantry robot, the IBM electric cantilever robot (ECR), to plutonium processing applications. Steps are being taken to harden this robot to withstand the dry, often abrasive, environment within a plutonium glove box and to protect the electronic components against alpha radiation. A mock-up processing system for the reduction of the oxide to a metal was prepared and successfully demonstrated. Design of a working prototype is now underway using the results of this mock-up study. 7 figs., 4 tabs

  14. ADAPTIVE DISTRIBUTION OF A SWARM OF HETEROGENEOUS ROBOTS

    Directory of Open Access Journals (Sweden)

    Amanda Prorok

    2016-02-01

    Full Text Available We present a method that distributes a swarm of heterogeneous robots among a set of tasks that require specialized capabilities in order to be completed. We model the system of heterogeneous robots as a community of species, where each species (robot type is defined by the traits (capabilities that it owns. Our method is based on a continuous abstraction of the swarm at a macroscopic level as we model robots switching between tasks. We formulate an optimization problem that produces an optimal set of transition rates for each species, so that the desired trait distribution is reached as quickly as possible. Since our method is based on the derivation of an analytical gradient, it is very efficient with respect to state-of-the-art methods. Building on this result, we propose a real-time optimization method that enables an online adaptation of transition rates. Our approach is well-suited for real-time applications that rely on online redistribution of large-scale robotic systems.

  15. Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants

    Directory of Open Access Journals (Sweden)

    Francesco Corucci

    2017-07-01

    Full Text Available In this paper, a comprehensive methodology and simulation framework will be reviewed, designed in order to study the emergence of adaptive and intelligent behavior in generic soft-bodied creatures. By incorporating artificial evolutionary and developmental processes, the system allows to evolve complete creatures (brain, body, developmental properties, sensory, control system, etc. for different task environments. Whether the evolved creatures will resemble animals or plants is in general not known a priori, and depends on the specific task environment set up by the experimenter. In this regard, the system may offer a unique opportunity to explore differences and similarities between these two worlds. Different material properties can be simulated and optimized, from a continuum of soft/stiff materials, to the interconnection of heterogeneous structures, both found in animals and plants alike. The adopted genetic encoding and simulation environment are particularly suitable in order to evolve distributed sensory and control systems, which play a particularly important role in plants. After a general description of the system some case studies will be presented, focusing on the emergent properties of the evolved creatures. Particular emphasis will be on some unifying concepts that are thought to play an important role in the emergence of intelligent and adaptive behavior across both the animal and plant kingdoms, such as morphological computation and morphological developmental plasticity. Overall, with this paper, we hope to draw attention on set of tools, methodologies, ideas and results, which may be relevant to researchers interested in plant-inspired robotics and intelligence.

  16. A Study on Bipedal and Mobile Robot Behavior Through Modeling and Simulation

    Directory of Open Access Journals (Sweden)

    Nirmala Nirmala

    2015-05-01

    Full Text Available The purpose of this work is to study and analyze mobile robot behavior. In performing this, a framework is adopted and developed for mobile and bipedal robot. The robots are design, build, and run as proceed from the development of mechanical structure, electronics and control integration, and control software application. The behavior of those robots are difficult to be observed and analyzed qualitatively. To evaluate the design and behavior quality, modeling and simulation of robot structure and its task capability is performed. The stepwise procedure to robot behavior study is explained. Behavior cases study are experimented to bipedal robots, transporter robot and Autonomous Guided Vehicle (AGV developed at our institution. The experimentation are conducted on those robots by adjusting their dynamic properties and/or surrounding environment. Validation is performed by comparing the simulation result and the real robot execution. The simulation gives a more idealistic behavior execution rather than realistic one. Adjustments are performed to fine tuning simulation's parameters to provide a more realistic performance.

  17. Developing new behavior strategies of robot soccer team SjF TUKE Robotics

    Directory of Open Access Journals (Sweden)

    Mikuláš Hajduk

    2016-09-01

    Full Text Available There are too many types of robotic soccer approaches at present. SjF TUKE Robotics, who won robot soccer world tournament for year 2010 in category MiroSot, is a team with multiagent system approach. They have one main agent (master and five agent players, represented by robots. There is a point of view, in the article, for code programmer how to create new behavior strategies by creating a new code for master. There is a methodology how to prepare and create it following some rules.

  18. Adaptive Neural Output Feedback Control for Uncertain Robot Manipulators with Input Saturation

    Directory of Open Access Journals (Sweden)

    Rong Mei

    2017-01-01

    Full Text Available This paper presents an adaptive neural output feedback control scheme for uncertain robot manipulators with input saturation using the radial basis function neural network (RBFNN and disturbance observer. First, the RBFNN is used to approximate the system uncertainty, and the unknown approximation error of the RBFNN and the time-varying unknown external disturbance of robot manipulators are integrated as a compounded disturbance. Then, the state observer and the disturbance observer are proposed to estimate the unmeasured system state and the unknown compounded disturbance based on RBFNN. At the same time, the adaptation technique is employed to tackle the control input saturation problem. Utilizing the estimate outputs of the RBFNN, the state observer, and the disturbance observer, the adaptive neural output feedback control scheme is developed for robot manipulators using the backstepping technique. The convergence of all closed-loop signals is rigorously proved via Lyapunov analysis and the asymptotically convergent tracking error is obtained under the integrated effect of the system uncertainty, the unmeasured system state, the unknown external disturbance, and the input saturation. Finally, numerical simulation results are presented to illustrate the effectiveness of the proposed adaptive neural output feedback control scheme for uncertain robot manipulators.

  19. Motion and Emotional Behavior Design for Pet Robot Dog

    Science.gov (United States)

    Cheng, Chi-Tai; Yang, Yu-Ting; Miao, Shih-Heng; Wong, Ching-Chang

    A pet robot dog with two ears, one mouth, one facial expression plane, and one vision system is designed and implemented so that it can do some emotional behaviors. Three processors (Inter® Pentium® M 1.0 GHz, an 8-bit processer 8051, and embedded soft-core processer NIOS) are used to control the robot. One camera, one power detector, four touch sensors, and one temperature detector are used to obtain the information of the environment. The designed robot with 20 DOF (degrees of freedom) is able to accomplish the walking motion. A behavior system is built on the implemented pet robot so that it is able to choose a suitable behavior for different environmental situation. From the practical test, we can see that the implemented pet robot dog can do some emotional interaction with the human.

  20. Challenges in adapting imitation and reinforcement learning to compliant robots

    Directory of Open Access Journals (Sweden)

    Calinon Sylvain

    2011-12-01

    Full Text Available There is an exponential increase of the range of tasks that robots are forecasted to accomplish. (Reprogramming these robots becomes a critical issue for their commercialization and for their applications to real-world scenarios in which users without expertise in robotics wish to adapt the robot to their needs. This paper addresses the problem of designing userfriendly human-robot interfaces to transfer skills in a fast and efficient manner. This paper presents recent work conducted at the Learning and Interaction group at ADVR-IIT, ranging from skill acquisition through kinesthetic teaching to self-refinement strategies initiated from demonstrations. Our group started to explore the use of imitation and exploration strategies that can take advantage of the compliant capabilities of recent robot hardware and control architectures.

  1. Toward understanding social cues and signals in human-robot interaction: effects of robot gaze and proxemic behavior.

    Science.gov (United States)

    Fiore, Stephen M; Wiltshire, Travis J; Lobato, Emilio J C; Jentsch, Florian G; Huang, Wesley H; Axelrod, Benjamin

    2013-01-01

    As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human-robot interaction (HRI). We then discuss the need to examine the relationship between social cues and signals as a function of the degree to which a robot is perceived as a socially present agent. We describe an experiment in which social cues were manipulated on an iRobot Ava(TM) mobile robotics platform in a hallway navigation scenario. Cues associated with the robot's proxemic behavior were found to significantly affect participant perceptions of the robot's social presence and emotional state while cues associated with the robot's gaze behavior were not found to be significant. Further, regardless of the proxemic behavior, participants attributed more social presence and emotional states to the robot over repeated interactions than when they first interacted with it. Generally, these results indicate the importance for HRI research to consider how social cues expressed by a robot can differentially affect perceptions of the robot's mental states and intentions. The discussion focuses on implications for the design of robotic systems and future directions for research on the relationship between social cues and signals.

  2. A Novel Greeting Selection System for a Culture-Adaptive Humanoid Robot

    Directory of Open Access Journals (Sweden)

    Gabriele Trovato

    2015-04-01

    Full Text Available Robots, especially humanoids, are expected to perform human-like actions and adapt to our ways of communication in order to facilitate their acceptance in human society. Among humans, rules of communication change depending on background culture: greetings are a part of communication in which cultural differences are strong. Robots should adapt to these specific differences in order to communicate effectively, being able to select the appropriate manner of greeting for different cultures depending on the social context. In this paper, we present the modelling of social factors that influence greeting choice, and the resulting novel culture-dependent greeting gesture and words selection system. An experiment with German participants was run using the humanoid robot ARMAR-IIIb. Thanks to this system, the robot, after interacting with Germans, can perform greeting gestures appropriate to German culture in addition to a repertoire of greetings appropriate to Japanese culture.

  3. HiMoP: A three-component architecture to create more human-acceptable social-assistive robots : Motivational architecture for assistive robots.

    Science.gov (United States)

    Rodríguez-Lera, Francisco J; Matellán-Olivera, Vicente; Conde-González, Miguel Á; Martín-Rico, Francisco

    2018-05-01

    Generation of autonomous behavior for robots is a general unsolved problem. Users perceive robots as repetitive tools that do not respond to dynamic situations. This research deals with the generation of natural behaviors in assistive service robots for dynamic domestic environments, particularly, a motivational-oriented cognitive architecture to generate more natural behaviors in autonomous robots. The proposed architecture, called HiMoP, is based on three elements: a Hierarchy of needs to define robot drives; a set of Motivational variables connected to robot needs; and a Pool of finite-state machines to run robot behaviors. The first element is inspired in Alderfer's hierarchy of needs, which specifies the variables defined in the motivational component. The pool of finite-state machine implements the available robot actions, and those actions are dynamically selected taking into account the motivational variables and the external stimuli. Thus, the robot is able to exhibit different behaviors even under similar conditions. A customized version of the "Speech Recognition and Audio Detection Test," proposed by the RoboCup Federation, has been used to illustrate how the architecture works and how it dynamically adapts and activates robots behaviors taking into account internal variables and external stimuli.

  4. Periodic activations of behaviours and emotional adaptation in behaviour-based robotics

    Science.gov (United States)

    Burattini, Ernesto; Rossi, Silvia

    2010-09-01

    The possible modulatory influence of motivations and emotions is of great interest in designing robotic adaptive systems. In this paper, an attempt is made to connect the concept of periodic behaviour activations to emotional modulation, in order to link the variability of behaviours to the circumstances in which they are activated. The impact of emotion is studied, described as timed controlled structures, on simple but conflicting reactive behaviours. Through this approach it is shown that the introduction of such asynchronies in the robot control system may lead to an adaptation in the emergent behaviour without having an explicit action selection mechanism. The emergent behaviours of a simple robot designed with both a parallel and a hierarchical architecture are evaluated and compared.

  5. Modeling and Simulation of Elementary Robot Behaviors using Associative Memories

    Directory of Open Access Journals (Sweden)

    Claude F. Touzet

    2006-06-01

    Full Text Available Today, there are several drawbacks that impede the necessary and much needed use of robot learning techniques in real applications. First, the time needed to achieve the synthesis of any behavior is prohibitive. Second, the robot behavior during the learning phase is – by definition – bad, it may even be dangerous. Third, except within the lazy learning approach, a new behavior implies a new learning phase. We propose in this paper to use associative memories (self-organizing maps to encode the non explicit model of the robot-world interaction sampled by the lazy memory, and then generate a robot behavior by means of situations to be achieved, i.e., points on the self-organizing maps. Any behavior can instantaneously be synthesized by the definition of a goal situation. Its performance will be minimal (not necessarily bad and will improve by the mere repetition of the behavior.

  6. Mathematical model for adaptive control system of ASEA robot at Kennedy Space Center

    Science.gov (United States)

    Zia, Omar

    1989-01-01

    The dynamic properties and the mathematical model for the adaptive control of the robotic system presently under investigation at Robotic Application and Development Laboratory at Kennedy Space Center are discussed. NASA is currently investigating the use of robotic manipulators for mating and demating of fuel lines to the Space Shuttle Vehicle prior to launch. The Robotic system used as a testbed for this purpose is an ASEA IRB-90 industrial robot with adaptive control capabilities. The system was tested and it's performance with respect to stability was improved by using an analogue force controller. The objective of this research project is to determine the mathematical model of the system operating under force feedback control with varying dynamic internal perturbation in order to provide continuous stable operation under variable load conditions. A series of lumped parameter models are developed. The models include some effects of robot structural dynamics, sensor compliance, and workpiece dynamics.

  7. Robotic Oncological Surgery: Technology That's Here to Stay?

    Directory of Open Access Journals (Sweden)

    HRH Patel

    2009-09-01

    Full Text Available A robot functioning in an environment may exhibit various forms of behavior emerge from the interaction with its environment through sense, control and plan activities. Hence, this paper introduces a behaviour selection based navigation and obstacle avoidance algorithm with effective method for adapting robotic behavior according to the environment conditions and the navigated terrain. The developed algorithm enable the robot to select the suitable behavior in real-time to avoid obstacles based on sensory information through visual and ultrasonic sensors utilizing the robot's ability to step over obstacles, and move between surfaces of different heights. In addition, it allows the robot to react in appropriate manner to the changing conditions either by fine-tuning of behaviors or by selecting different set of behaviors to increase the efficiency of the robot over time. The presented approach has been demonstrated on quadruped robot in several different experimental environments and the paper provides an analysis of its performance.

  8. Autonomous Shepherding Behaviors of Multiple Target Steering Robots.

    Science.gov (United States)

    Lee, Wonki; Kim, DaeEun

    2017-11-25

    This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots' position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach.

  9. Toward understanding social cues and signals in human–robot interaction: effects of robot gaze and proxemic behavior

    Science.gov (United States)

    Fiore, Stephen M.; Wiltshire, Travis J.; Lobato, Emilio J. C.; Jentsch, Florian G.; Huang, Wesley H.; Axelrod, Benjamin

    2013-01-01

    As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human–robot interaction (HRI). We then discuss the need to examine the relationship between social cues and signals as a function of the degree to which a robot is perceived as a socially present agent. We describe an experiment in which social cues were manipulated on an iRobot AvaTM mobile robotics platform in a hallway navigation scenario. Cues associated with the robot’s proxemic behavior were found to significantly affect participant perceptions of the robot’s social presence and emotional state while cues associated with the robot’s gaze behavior were not found to be significant. Further, regardless of the proxemic behavior, participants attributed more social presence and emotional states to the robot over repeated interactions than when they first interacted with it. Generally, these results indicate the importance for HRI research to consider how social cues expressed by a robot can differentially affect perceptions of the robot’s mental states and intentions. The discussion focuses on implications for the design of robotic systems and future directions for research on the relationship between social cues and signals. PMID:24348434

  10. Towards understanding social cues and signals in human-robot interaction: Effects of robot gaze and proxemic behavior

    Directory of Open Access Journals (Sweden)

    Stephen M. Fiore

    2013-11-01

    Full Text Available As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human-robot interaction (HRI. We then discuss the need to examine the relationship between social cues and signals as a function of the degree to which a robot is perceived as a socially present agent. We describe an experiment in which social cues were manipulated on an iRobot Ava™ Mobile Robotics Platform in a hallway navigation scenario. Cues associated with the robot’s proxemic behavior were found to significantly affect participant perceptions of the robot’s social presence and emotional state while cues associated with the robot’s gaze behavior were not found to be significant. Further, regardless of the proxemic behavior, participants attributed more social presence and emotional states to the robot over repeated interactions than when they first interacted with it. Generally, these results indicate the importance for HRI research to consider how social cues expressed by a robot can differentially affect perceptions of the robot’s mental states and intentions. The discussion focuses on implications for the design of robotic systems and future directions for research on the relationship between social cues and signals.

  11. Combining environment-driven adaptation and task-driven optimisation in evolutionary robotics.

    Science.gov (United States)

    Haasdijk, Evert; Bredeche, Nicolas; Eiben, A E

    2014-01-01

    Embodied evolutionary robotics is a sub-field of evolutionary robotics that employs evolutionary algorithms on the robotic hardware itself, during the operational period, i.e., in an on-line fashion. This enables robotic systems that continuously adapt, and are therefore capable of (re-)adjusting themselves to previously unknown or dynamically changing conditions autonomously, without human oversight. This paper addresses one of the major challenges that such systems face, viz. that the robots must satisfy two sets of requirements. Firstly, they must continue to operate reliably in their environment (viability), and secondly they must competently perform user-specified tasks (usefulness). The solution we propose exploits the fact that evolutionary methods have two basic selection mechanisms-survivor selection and parent selection. This allows evolution to tackle the two sets of requirements separately: survivor selection is driven by the environment and parent selection is based on task-performance. This idea is elaborated in the Multi-Objective aNd open-Ended Evolution (monee) framework, which we experimentally validate. Experiments with robotic swarms of 100 simulated e-pucks show that monee does indeed promote task-driven behaviour without compromising environmental adaptation. We also investigate an extension of the parent selection process with a 'market mechanism' that can ensure equitable distribution of effort over multiple tasks, a particularly pressing issue if the environment promotes specialisation in single tasks.

  12. Combining environment-driven adaptation and task-driven optimisation in evolutionary robotics.

    Directory of Open Access Journals (Sweden)

    Evert Haasdijk

    Full Text Available Embodied evolutionary robotics is a sub-field of evolutionary robotics that employs evolutionary algorithms on the robotic hardware itself, during the operational period, i.e., in an on-line fashion. This enables robotic systems that continuously adapt, and are therefore capable of (re-adjusting themselves to previously unknown or dynamically changing conditions autonomously, without human oversight. This paper addresses one of the major challenges that such systems face, viz. that the robots must satisfy two sets of requirements. Firstly, they must continue to operate reliably in their environment (viability, and secondly they must competently perform user-specified tasks (usefulness. The solution we propose exploits the fact that evolutionary methods have two basic selection mechanisms-survivor selection and parent selection. This allows evolution to tackle the two sets of requirements separately: survivor selection is driven by the environment and parent selection is based on task-performance. This idea is elaborated in the Multi-Objective aNd open-Ended Evolution (monee framework, which we experimentally validate. Experiments with robotic swarms of 100 simulated e-pucks show that monee does indeed promote task-driven behaviour without compromising environmental adaptation. We also investigate an extension of the parent selection process with a 'market mechanism' that can ensure equitable distribution of effort over multiple tasks, a particularly pressing issue if the environment promotes specialisation in single tasks.

  13. The embodiment of cockroach aggregation behavior in a group of micro-robots.

    Science.gov (United States)

    Garnier, Simon; Jost, Christian; Gautrais, Jacques; Asadpour, Masoud; Caprari, Gilles; Jeanson, Raphaël; Grimal, Anne; Theraulaz, Guy

    2008-01-01

    We report the faithful reproduction of the self-organized aggregation behavior of the German cockroach Blattella germanica with a group of robots. We describe the implementation of the biological model provided by Jeanson et al. in Alice robots, and we compare the behaviors of the cockroaches and the robots using the same experimental and analytical methodology. We show that the aggregation behavior of the German cockroach was successfully transferred to the Alice robot despite strong differences between robots and animals at the perceptual, actuatorial, and computational levels. This article highlights some of the major constraints one may encounter during such a work and proposes general principles to ensure that the behavioral model is accurately transferred to the artificial agents.

  14. Adaptive Synchronization of Robotic Sensor Networks

    OpenAIRE

    Yıldırım, Kasım Sinan; Gürcan, Önder

    2014-01-01

    The main focus of recent time synchronization research is developing power-efficient synchronization methods that meet pre-defined accuracy requirements. However, an aspect that has been often overlooked is the high dynamics of the network topology due to the mobility of the nodes. Employing existing flooding-based and peer-to-peer synchronization methods, are networked robots still be able to adapt themselves and self-adjust their logical clocks under mobile network dynamics? In this paper, ...

  15. Adaptive PID formation control of nonholonomic robots without leader's velocity information.

    Science.gov (United States)

    Shen, Dongbin; Sun, Weijie; Sun, Zhendong

    2014-03-01

    This paper proposes an adaptive proportional integral derivative (PID) algorithm to solve a formation control problem in the leader-follower framework where the leader robot's velocities are unknown for the follower robots. The main idea is first to design some proper ideal control law for the formation system to obtain a required performance, and then to propose the adaptive PID methodology to approach the ideal controller. As a result, the formation is achieved with much more enhanced robust formation performance. The stability of the closed-loop system is theoretically proved by Lyapunov method. Both numerical simulations and physical vehicle experiments are presented to verify the effectiveness of the proposed adaptive PID algorithm. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  16. The Impact of Robot Tutor Nonverbal Social Behavior on Child Learning

    Directory of Open Access Journals (Sweden)

    James Kennedy

    2017-04-01

    Full Text Available Several studies have indicated that interacting with social robots in educational contexts may lead to a greater learning than interactions with computers or virtual agents. As such, an increasing amount of social human–robot interaction research is being conducted in the learning domain, particularly with children. However, it is unclear precisely what social behavior a robot should employ in such interactions. Inspiration can be taken from human–human studies; this often leads to an assumption that the more social behavior an agent utilizes, the better the learning outcome will be. We apply a nonverbal behavior metric to a series of studies in which children are taught how to identify prime numbers by a robot with various behavioral manipulations. We find a trend, which generally agrees with the pedagogy literature, but also that overt nonverbal behavior does not account for all learning differences. We discuss the impact of novelty, child expectations, and responses to social cues to further the understanding of the relationship between robot social behavior and learning. We suggest that the combination of nonverbal behavior and social cue congruency is necessary to facilitate learning.

  17. Autonomous Shepherding Behaviors of Multiple Target Steering Robots

    Directory of Open Access Journals (Sweden)

    Wonki Lee

    2017-11-01

    Full Text Available This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots’ position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach.

  18. Adaptive Robotic Systems Design in University of Applied Sciences

    Directory of Open Access Journals (Sweden)

    Gunsing Jos

    2016-01-01

    Full Text Available In the industry for highly specialized machine building (small series with high variety and high complexity and in healthcare a demand for adaptive robotics is rapidly coming up. Technically skilled people are not always available in sufficient numbers. A lot of know how with respect to the required technologies is available but successful adaptive robotic system designs are still rare. In our research at the university of applied sciences we incorporate new available technologies in our education courses by way of research projects; in these projects students will investigate the application possibilities of new technologies together with companies and teachers. Thus we are able to transfer knowledge to the students including an innovation oriented attitude and skills. Last years we developed several industrial binpicking applications for logistics and machining-factories with different types of 3D vision. Also force feedback gripping has been developed including slip sensing. Especially for healthcare robotics we developed a so-called twisted wire actuator, which is very compact in combination with an underactuated gripper, manufactured in one piece in polyurethane. We work both on modeling and testing the functions of these designs but we work also on complete demonstrator systems. Since the amount of disciplines involved in complex product and machine design increases rapidly we pay a lot of attention with respect to systems engineering methods. Apart from the classical engineering disciplines like mechanical, electrical, software and mechatronics engineering, especially for adaptive robotics more and more disciplines like industrial product design, communication … multimedia design and of course physics and even art are to be involved depending on the specific application to be designed. Design tools like V-model, agile/scrum and design-approaches to obtain the best set of requirements are being implemented in the engineering studies from

  19. Beyond adaptive-critic creative learning for intelligent mobile robots

    Science.gov (United States)

    Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

    2001-10-01

    Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it

  20. The Tactile Ethics of Soft Robotics: Designing Wisely for Human-Robot Interaction.

    Science.gov (United States)

    Arnold, Thomas; Scheutz, Matthias

    2017-06-01

    Soft robots promise an exciting design trajectory in the field of robotics and human-robot interaction (HRI), promising more adaptive, resilient movement within environments as well as a safer, more sensitive interface for the objects or agents the robot encounters. In particular, tactile HRI is a critical dimension for designers to consider, especially given the onrush of assistive and companion robots into our society. In this article, we propose to surface an important set of ethical challenges for the field of soft robotics to meet. Tactile HRI strongly suggests that soft-bodied robots balance tactile engagement against emotional manipulation, model intimacy on the bonding with a tool not with a person, and deflect users from personally and socially destructive behavior the soft bodies and surfaces could normally entice.

  1. Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints

    Directory of Open Access Journals (Sweden)

    Kun Li

    2015-03-01

    Full Text Available For a domestic personal robot, personalized services are as important as predesigned tasks, because the robot needs to adjust the home state based on the operator's habits. An operator's habits are composed of cues, behaviors, and rewards. This article introduces behavioral footprints to describe the operator's behaviors in a house, and applies the inverse reinforcement learning technique to extract the operator's habits, represented by a reward function. We implemented the proposed approach with a mobile robot on indoor temperature adjustment, and compared this approach with a baseline method that recorded all the cues and behaviors of the operator. The result shows that the proposed approach allows the robot to reveal the operator's habits accurately and adjust the environment state accordingly.

  2. Adaptive training of neural networks for control of autonomous mobile robots

    NARCIS (Netherlands)

    Steur, E.; Vromen, T.; Nijmeijer, H.; Fossen, T.I.; Nijmeijer, H.; Pettersen, K.Y.

    2017-01-01

    We present an adaptive training procedure for a spiking neural network, which is used for control of a mobile robot. Because of manufacturing tolerances, any hardware implementation of a spiking neural network has non-identical nodes, which limit the performance of the controller. The adaptive

  3. Self-adaptive robot training of stroke survivors for continuous tracking movements

    Directory of Open Access Journals (Sweden)

    Morasso Pietro

    2010-03-01

    Full Text Available Abstract Background Although robot therapy is progressively becoming an accepted method of treatment for stroke survivors, few studies have investigated how to adapt the robot/subject interaction forces in an automatic way. The paper is a feasibility study of a novel self-adaptive robot controller to be applied with continuous tracking movements. Methods The haptic robot Braccio di Ferro is used, in relation with a tracking task. The proposed control architecture is based on three main modules: 1 a force field generator that combines a non linear attractive field and a viscous field; 2 a performance evaluation module; 3 an adaptive controller. The first module operates in a continuous time fashion; the other two modules operate in an intermittent way and are triggered at the end of the current block of trials. The controller progressively decreases the gain of the force field, within a session, but operates in a non monotonic way between sessions: it remembers the minimum gain achieved in a session and propagates it to the next one, which starts with a block whose gain is greater than the previous one. The initial assistance gains are chosen according to a minimal assistance strategy. The scheme can also be applied with closed eyes in order to enhance the role of proprioception in learning and control. Results The preliminary results with a small group of patients (10 chronic hemiplegic subjects show that the scheme is robust and promotes a statistically significant improvement in performance indicators as well as a recalibration of the visual and proprioceptive channels. The results confirm that the minimally assistive, self-adaptive strategy is well tolerated by severely impaired subjects and is beneficial also for less severe patients. Conclusions The experiments provide detailed information about the stability and robustness of the adaptive controller of robot assistance that could be quite relevant for the design of future large scale

  4. The quadruped robot adaptive control in trotting gait walking on slopes

    Science.gov (United States)

    Zhang, Shulong; Ma, Hongxu; Yang, Yu; Wang, Jian

    2017-10-01

    The quadruped robot can be decomposed into a planar seven-link closed kinematic chain in the direction of supporting line and a linear inverted pendulum in normal direction of supporting line. The ground slope can be estimated by using the body attitude information and supporting legs length. The slope degree is used in feedback, to achieve the point of quadruped robot adaptive control walking on slopes. The simulation results verify that the quadruped robot can achieves steady locomotion on the slope with the control strategy proposed in this passage.

  5. Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

    Directory of Open Access Journals (Sweden)

    Guofeng Tong

    2014-04-01

    Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

  6. Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.

    Science.gov (United States)

    Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H

    2017-07-01

    In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.

  7. A Basic Architecture of an Autonomous Adaptive System With Conscious-Like Function for a Humanoid Robot

    Directory of Open Access Journals (Sweden)

    Yasuo Kinouchi

    2018-04-01

    Full Text Available In developing a humanoid robot, there are two major objectives. One is developing a physical robot having body, hands, and feet resembling those of human beings and being able to similarly control them. The other is to develop a control system that works similarly to our brain, to feel, think, act, and learn like ours. In this article, an architecture of a control system with a brain-oriented logical structure for the second objective is proposed. The proposed system autonomously adapts to the environment and implements a clearly defined “consciousness” function, through which both habitual behavior and goal-directed behavior are realized. Consciousness is regarded as a function for effective adaptation at the system-level, based on matching and organizing the individual results of the underlying parallel-processing units. This consciousness is assumed to correspond to how our mind is “aware” when making our moment to moment decisions in our daily life. The binding problem and the basic causes of delay in Libet’s experiment are also explained by capturing awareness in this manner. The goal is set as an image in the system, and efficient actions toward achieving this goal are selected in the goal-directed behavior process. The system is designed as an artificial neural network and aims at achieving consistent and efficient system behavior, through the interaction of highly independent neural nodes. The proposed architecture is based on a two-level design. The first level, which we call the “basic-system,” is an artificial neural network system that realizes consciousness, habitual behavior and explains the binding problem. The second level, which we call the “extended-system,” is an artificial neural network system that realizes goal-directed behavior.

  8. Fish and robots swimming together in a water tunnel: robot color and tail-beat frequency influence fish behavior.

    Directory of Open Access Journals (Sweden)

    Giovanni Polverino

    Full Text Available The possibility of integrating bioinspired robots in groups of live social animals may constitute a valuable tool to study the basis of social behavior and uncover the fundamental determinants of animal functions and dysfunctions. In this study, we investigate the interactions between individual golden shiners (Notemigonus crysoleucas and robotic fish swimming together in a water tunnel at constant flow velocity. The robotic fish is designed to mimic its live counterpart in the aspect ratio, body shape, dimension, and locomotory pattern. Fish positional preference with respect to the robot is experimentally analyzed as the robot's color pattern and tail-beat frequency are varied. Behavioral observations are corroborated by particle image velocimetry studies aimed at investigating the flow structure behind the robotic fish. Experimental results show that the time spent by golden shiners in the vicinity of the bioinspired robotic fish is the highest when the robot mimics their natural color pattern and beats its tail at the same frequency. In these conditions, fish tend to swim at the same depth of the robotic fish, where the wake from the robotic fish is stronger and hydrodynamic return is most likely to be effective.

  9. Fish and robots swimming together in a water tunnel: robot color and tail-beat frequency influence fish behavior.

    Science.gov (United States)

    Polverino, Giovanni; Phamduy, Paul; Porfiri, Maurizio

    2013-01-01

    The possibility of integrating bioinspired robots in groups of live social animals may constitute a valuable tool to study the basis of social behavior and uncover the fundamental determinants of animal functions and dysfunctions. In this study, we investigate the interactions between individual golden shiners (Notemigonus crysoleucas) and robotic fish swimming together in a water tunnel at constant flow velocity. The robotic fish is designed to mimic its live counterpart in the aspect ratio, body shape, dimension, and locomotory pattern. Fish positional preference with respect to the robot is experimentally analyzed as the robot's color pattern and tail-beat frequency are varied. Behavioral observations are corroborated by particle image velocimetry studies aimed at investigating the flow structure behind the robotic fish. Experimental results show that the time spent by golden shiners in the vicinity of the bioinspired robotic fish is the highest when the robot mimics their natural color pattern and beats its tail at the same frequency. In these conditions, fish tend to swim at the same depth of the robotic fish, where the wake from the robotic fish is stronger and hydrodynamic return is most likely to be effective.

  10. Adaptive Controller for 6-DOF Parallel Robot Using T-S Fuzzy Inference

    Directory of Open Access Journals (Sweden)

    Xue Jian

    2013-02-01

    Full Text Available 6-DOF parallel robot always appears in the form of Stewart platform. It has been widely used in industry for the benefits such as strong structural stiffness, high movement accuracy and so on. Space docking technology makes higher requirements of motion accuracy and dynamic performance to the control method on 6-DOF parallel robot. In this paper, a hydraulic 6-DOF parallel robot was used to simulate the docking process. Based on this point, this paper gave a thorough study on the design of an adaptive controller to eliminate the asymmetric of controlled plant and uncertain load force interference. Takagi-Sugeno (T-S fuzzy inference model was used to build the fuzzy adaptive controller. With T-S model, the controller directly imposes adaptive control signal on the plant to make sure that the output of plant could track the reference model output. The controller has simple structure and is easy to implement. Experiment results show that the controller can eliminate asymmetric and achieve good dynamic performance, and has good robustness to load interference.

  11. Fuzzy Adaptation Algorithms’ Control for Robot Manipulators with Uncertainty Modelling Errors

    Directory of Open Access Journals (Sweden)

    Yongqing Fan

    2018-01-01

    Full Text Available A novel fuzzy control scheme with adaptation algorithms is developed for robot manipulators’ system. At the beginning, one adjustable parameter is introduced in the fuzzy logic system, the robot manipulators system with uncertain nonlinear terms as the master device and a reference model dynamic system as the slave robot system. To overcome the limitations such as online learning computation burden and logic structure in conventional fuzzy logic systems, a parameter should be used in fuzzy logic system, which composes fuzzy logic system with updated parameter laws, and can be formed for a new fashioned adaptation algorithms controller. The error closed-loop dynamical system can be stabilized based on Lyapunov analysis, the number of online learning computation burdens can be reduced greatly, and the different kinds of fuzzy logic systems with fuzzy rules or without any fuzzy rules are also suited. Finally, effectiveness of the proposed approach has been shown in simulation example.

  12. Adaptive Rationality, Adaptive Behavior and Institutions

    Directory of Open Access Journals (Sweden)

    Volchik Vyacheslav, V.

    2015-12-01

    Full Text Available The economic literature focused on understanding decision-making and choice processes reveals a vast collection of approaches to human rationality. Theorists’ attention has moved from absolutely rational, utility-maximizing individuals to boundedly rational and adaptive ones. A number of economists have criticized the concepts of adaptive rationality and adaptive behavior. One of the recent trends in the economic literature is to consider humans irrational. This paper offers an approach which examines adaptive behavior in the context of existing institutions and constantly changing institutional environment. It is assumed that adaptive behavior is a process of evolutionary adjustment to fundamental uncertainty. We emphasize the importance of actors’ engagement in trial and error learning, since if they are involved in this process, they obtain experience and are able to adapt to existing and new institutions. The paper aims at identifying relevant institutions, adaptive mechanisms, informal working rules and practices that influence actors’ behavior in the field of Higher Education in Russia (Rostov Region education services market has been taken as an example. The paper emphasizes the application of qualitative interpretative methods (interviews and discourse analysis in examining actors’ behavior.

  13. An Augmented Discrete-Time Approach for Human-Robot Collaboration

    Directory of Open Access Journals (Sweden)

    Peidong Liang

    2016-01-01

    Full Text Available Human-robot collaboration (HRC is a key feature to distinguish the new generation of robots from conventional robots. Relevant HRC topics have been extensively investigated recently in academic institutes and companies to improve human and robot interactive performance. Generally, human motor control regulates human motion adaptively to the external environment with safety, compliance, stability, and efficiency. Inspired by this, we propose an augmented approach to make a robot understand human motion behaviors based on human kinematics and human postural impedance adaptation. Human kinematics is identified by geometry kinematics approach to map human arm configuration as well as stiffness index controlled by hand gesture to anthropomorphic arm. While human arm postural stiffness is estimated and calibrated within robot empirical stability region, human motion is captured by employing a geometry vector approach based on Kinect. A biomimetic controller in discrete-time is employed to make Baxter robot arm imitate human arm behaviors based on Baxter robot dynamics. An object moving task is implemented to validate the performance of proposed methods based on Baxter robot simulator. Results show that the proposed approach to HRC is intuitive, stable, efficient, and compliant, which may have various applications in human-robot collaboration scenarios.

  14. Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment.

    Science.gov (United States)

    Yao, Yao; Storme, Veronique; Marchal, Kathleen; Van de Peer, Yves

    2016-01-01

    We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population.

  15. Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment

    Science.gov (United States)

    Yao, Yao; Storme, Veronique; Marchal, Kathleen

    2016-01-01

    We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population. PMID:28028477

  16. Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment

    Directory of Open Access Journals (Sweden)

    Yao Yao

    2016-12-01

    Full Text Available We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population.

  17. Multiple Decoupled CPGs with Local Sensory Feedback for Adaptive Locomotion Behaviors of Bio-inspired Walking Robots

    DEFF Research Database (Denmark)

    Shaker Barikhan, Subhi; Wörgötter, Florentin; Manoonpong, Poramate

    2014-01-01

    , and their interactions during body and leg movements through the environment. Based on this concept, we present here an artificial bio-inspired walking system. Its intralimb coordination is formed by multiple decoupled CPGs while its interlimb coordination is attained by the interactions between body dynamics...... and the environment through local sensory feedback of each leg. Simulation results show that this bio-inspired approach generates self-organizing emergent locomotion allowing the robot to adaptively form regular patterns, to stably walk while pushing an object with its front legs or performing multiple stepping...

  18. An Adaptive Approach for Precise Underwater Vehicle Control in Combined Robot-Diver Operations

    Science.gov (United States)

    2015-03-01

    and Nicosia and Tomei [13] focused on industrial applications involving robotic manipulator arms carrying various loads. The application of...1987. 94 [13] S. Nicosia and P. Tomei, “Model reference adaptive control algorithms for industrial robots ,” Automatica, vol. 20, pp. 635–644, 9... kinematic and dynamic properties,” The International Journal of Robotics Research, vol. 25, pp. 283–296, March 01, 2006. [17] A. Sanei and M. French

  19. Effects of Robot Facial Characteristics and Gender in Persuasive Human-Robot Interaction

    Directory of Open Access Journals (Sweden)

    Aimi S. Ghazali

    2018-06-01

    Full Text Available The growing interest in social robotics makes it relevant to examine the potential of robots as persuasive agents and, more specifically, to examine how robot characteristics influence the way people experience such interactions and comply with the persuasive attempts by robots. The purpose of this research is to identify how the (ostensible gender and the facial characteristics of a robot influence the extent to which people trust it and the psychological reactance they experience from its persuasive attempts. This paper reports a laboratory study where SociBot™, a robot capable of displaying different faces and dynamic social cues, delivered persuasive messages to participants while playing a game. In-game choice behavior was logged, and trust and reactance toward the advisor were measured using questionnaires. Results show that a robotic advisor with upturned eyebrows and lips (features that people tend to trust more in humans is more persuasive, evokes more trust, and less psychological reactance compared to one displaying eyebrows pointing down and lips curled downwards at the edges (facial characteristics typically not trusted in humans. Gender of the robot did not affect trust, but participants experienced higher psychological reactance when interacting with a robot of the opposite gender. Remarkably, mediation analysis showed that liking of the robot fully mediates the influence of facial characteristics on trusting beliefs and psychological reactance. Also, psychological reactance was a strong and reliable predictor of trusting beliefs but not of trusting behavior. These results suggest robots that are intended to influence human behavior should be designed to have facial characteristics we trust in humans and could be personalized to have the same gender as the user. Furthermore, personalization and adaptation techniques designed to make people like the robot more may help ensure they will also trust the robot.

  20. Biologically inspired control of humanoid robot arms robust and adaptive approaches

    CERN Document Server

    Spiers, Adam; Herrmann, Guido

    2016-01-01

    This book investigates a biologically inspired method of robot arm control, developed with the objective of synthesising human-like motion dynamically, using nonlinear, robust and adaptive control techniques in practical robot systems. The control method caters to a rising interest in humanoid robots and the need for appropriate control schemes to match these systems. Unlike the classic kinematic schemes used in industrial manipulators, the dynamic approaches proposed here promote human-like motion with better exploitation of the robot’s physical structure. This also benefits human-robot interaction. The control schemes proposed in this book are inspired by a wealth of human-motion literature that indicates the drivers of motion to be dynamic, model-based and optimal. Such considerations lend themselves nicely to achievement via nonlinear control techniques without the necessity for extensive and complex biological models. The operational-space method of robot control forms the basis of many of the techniqu...

  1. Adapting a robotics program to enhance participation and interest in STEM among children with disabilities: a pilot study.

    Science.gov (United States)

    Lindsay, Sally; Hounsell, Kara Grace

    2017-10-01

    Youth with disabilities are under-represented in science, technology, engineering, and math (STEM) in school and in the workforce. One encouraging approach to engage youth's interest in STEM is through robotics; however, such programs are mostly for typically developing youth. The purpose of this study was to understand the development and implementation of an adapted robotics program for children and youth with disabilities and their experiences within it. Our mixed methods pilot study (pre- and post-workshop surveys, observations, and interviews) involved 41 participants including: 18 youth (aged 6-13), 12 parents and 11 key informants. The robotics program involved 6, two-hour workshops held at a paediatric hospital. Our findings showed that several adaptations made to the robotics program helped to enhance the participation of children with disabilities. Adaptations addressed the educational/curriculum, cognitive and learning, physical and social needs of the children. In regards to experiences within the adapted hospital program, our findings highlight that children enjoyed the program and learned about computer programming and building robots. Clinicians and educators should consider engaging youth with disabilities in robotics to enhance learning and interest in STEM. Implications for Rehabilitation Clinicians and educators should consider adapting curriculum content and mode of delivery of LEGO ® robotics programs to include youth with disabilities. Appropriate staffing including clinicians and educators who are knowledgeable about youth with disabilities and LEGO ® robotics are needed. Clinicians should consider engaging youth with disabilities in LEGO ® to enhance learning and interest in STEM.

  2. Adaptive Human-Aware Robot Navigation in Close Proximity to Humans

    DEFF Research Database (Denmark)

    Svenstrup, Mikael; Hansen, Søren Tranberg; Andersen, Hans Jørgen

    2011-01-01

    For robots to be able coexist with people in future everyday human environments, they must be able to act in a safe, natural and comfortable way. This work addresses the motion of a mobile robot in an environment, where humans potentially want to interact with it. The designed system consists...... system that uses a potential field to derive motion that respects the personʹs social zones and perceived interest in interaction. The operation of the system is evaluated in a controlled scenario in an open hall environment. It is demonstrated that the robot is able to learn to estimate if a person...... wishes to interact, and that the system is capable of adapting to changing behaviours of the humans in the environment....

  3. Optimized Assistive Human-Robot Interaction Using Reinforcement Learning.

    Science.gov (United States)

    Modares, Hamidreza; Ranatunga, Isura; Lewis, Frank L; Popa, Dan O

    2016-03-01

    An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive controller is designed in the inner loop to make the unknown nonlinear robot behave like a prescribed robot impedance model as perceived by a human operator. In contrast to existing neural network and adaptive impedance-based control methods, no information of the task performance or the prescribed robot impedance model parameters is required in the inner loop. Then, a task-specific outer-loop controller is designed to find the optimal parameters of the prescribed robot impedance model to adjust the robot's dynamics to the operator skills and minimize the tracking error. The outer loop includes the human operator, the robot, and the task performance details. The problem of finding the optimal parameters of the prescribed robot impedance model is transformed into a linear quadratic regulator (LQR) problem which minimizes the human effort and optimizes the closed-loop behavior of the HRI system for a given task. To obviate the requirement of the knowledge of the human model, integral reinforcement learning is used to solve the given LQR problem. Simulation results on an x - y table and a robot arm, and experimental implementation results on a PR2 robot confirm the suitability of the proposed method.

  4. Behavioral similarity measurement based on image processing for robots that use imitative learning

    Science.gov (United States)

    Sterpin B., Dante G.; Martinez S., Fernando; Jacinto G., Edwar

    2017-02-01

    In the field of the artificial societies, particularly those are based on memetics, imitative behavior is essential for the development of cultural evolution. Applying this concept for robotics, through imitative learning, a robot can acquire behavioral patterns from another robot. Assuming that the learning process must have an instructor and, at least, an apprentice, the fact to obtain a quantitative measurement for their behavioral similarity, would be potentially useful, especially in artificial social systems focused on cultural evolution. In this paper the motor behavior of both kinds of robots, for two simple tasks, is represented by 2D binary images, which are processed in order to measure their behavioral similarity. The results shown here were obtained comparing some similarity measurement methods for binary images.

  5. Modbus RTU protocol and arduino IO package: A real time implementation of a 3 finger adaptive robot gripper

    Directory of Open Access Journals (Sweden)

    Sadun Amirul Syafiq

    2017-01-01

    Full Text Available Recently, the Modbus RTU protocol has been widely accepted in the application of robotics, communications and industrial control systems due to its simplicity and reliability. With the help of the MATLAB Instrument Control Toolbox, a serial communication between Simulink and a 3 Finger Adaptive Robot Gripper can be realized to demonstrate a grasping functionality. The toolbox includes a “to instrument” and “query instrument” programming blocks that enable the users to create a serial communication with the targeted hardware/robot. Similarly, the Simulink Arduino IO package also offers a real-time feature that enabled it to act as a DAQ device. This paper establishes a real-time robot control by using Modbus RTU and Arduino IO Package for a 3 Finger Adaptive Robot Gripper. The robot communication and grasping performance were successfully implemented and demonstrated. In particular, three (3 different grasping mode via normal, wide and pinch were tested. Moreover, the robot gripper’s feedback data, such as encoder position, motor current and the grasping force were easily measured and acquired in real-time. This certainly essential for future grasping analysis of a 3 Finger Adaptive Robot Gripper.

  6. Responsive Social Positioning Behaviors for Semi-Autonomous Telepresence Robots

    NARCIS (Netherlands)

    Vroon, Jered Hendrik

    2017-01-01

    Social interaction with a mobile robot requires the establishment of appropriate social positioning behaviors. Previous work has focused mostly on general and static rules that can be applied to robotics, such as proxemics. How can we deal effectively and efficiently with the dynamic positioning

  7. Adaptive control of two-wheeled mobile balance robot capable to adapt different surfaces using a novel artificial neural network–based real-time switching dynamic controller

    Directory of Open Access Journals (Sweden)

    Ali Unluturk

    2017-03-01

    Full Text Available In this article, a novel real-time artificial neural network–based adaptable switching dynamic controller is developed and practically implemented. It will be used for real-time control of two-wheeled balance robot which can balance itself upright position on different surfaces. In order to examine the efficiency of the proposed controller, a two-wheeled mobile balance robot is designed and a test platform for experimental setup is made for balance problem on different surfaces. In a developed adaptive controller algorithm which is capable to adapt different surfaces, mean absolute target angle deviation error, mean absolute target displacement deviation error and mean absolute controller output data are employed for surface estimation by using artificial neural network. In a designed two-wheeled mobile balance robot system, robot tilt angle is estimated via Kalman filter from accelerometer and gyroscope sensor signals. Furthermore, a visual robot control interface is developed in C++ software development environment so that robot controller parameters can be changed as desired. In addition, robot balance angle, linear displacement and controller output can be observed online on personal computer. According to the real-time experimental results, the proposed novel type controller gives more effective results than the classic ones.

  8. Fuzzy adaptive robust control for space robot considering the effect of the gravity

    Directory of Open Access Journals (Sweden)

    Qin Li

    2014-12-01

    Full Text Available Space robot is assembled and tested in gravity environment, and completes on-orbit service (OOS in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control (FARC strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative (PD controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.

  9. Continuing Robot Skill Learning after Demonstration with Human Feedback

    Directory of Open Access Journals (Sweden)

    Argall Brenna D.

    2011-12-01

    Full Text Available Though demonstration-based approaches have been successfully applied to learning a variety of robot behaviors, there do exist some limitations. The ability to continue learning after demonstration, based on execution experience with the learned policy, therefore has proven to be an asset to many demonstration-based learning systems. This paper discusses important considerations for interfaces that provide feedback to adapt and improve demonstrated behaviors. Feedback interfaces developed for two robots with very different motion capabilities - a wheeled mobile robot and high degree-of-freedom humanoid - are highlighted.

  10. Obstacle avoidance for kinematically redundant robots using an adaptive fuzzy logic algorithm

    International Nuclear Information System (INIS)

    Beheshti, M.T.H.; Tehrani, A.K.

    1999-05-01

    In this paper the Adaptive Fuzzy Logic approach for solving the inverse kinematics of redundant robots in an environment with obstacles is presented. The obstacles are modeled as convex bodies. A fuzzy rule base that is updated via an adaptive law is used to solve the inverse kinematic problem. Additional rules have been introduced to take care of the obstacles avoidance problem. The proposed method has advantages such as high accuracy, simplicity of computations and generality for all redundant robots. Simulation results illustrate much better tracking performance than the dynamic base solution for a given trajectory in cartesian space, while guaranteeing a collision-free trajectory and observation of a mechanical joint limit

  11. Distributed behavior-based control architecture for a wall climbing robot

    International Nuclear Information System (INIS)

    Nadir Ould Khessal; Shamsudin H.M. Amin . nadir.ok@ieee.org

    1999-01-01

    In the past two decades, Behavior-based AI (Artificial Intelligence) has emerged as a new approach in designing mobile robot control architecture. It stresses on the issues of reactivity, concurrency and real-time control. In this paper we propose a new approach in designing robust intelligent controllers for mobile robot platforms. The Behaviour-based paradigm implemented in a multiprocessing firmware architecture will further enhance parallelism present in the subsumption paradigm itself and increased real-timeness. The paper summarises research done to design a four-legged wall climbing robot. The emphasis will be on the control architecture of the robot based on the Behavior -based paradigm. The robot control architecture is made up of two layers, the locomotion layer and the gait controller layer. The two layers are implemented on a Vesta 68332 processor board running the Behaviour-based kernel, The software is developed using the L programming language, introduced by IS Robotics. The Behaviour-based paradigm is outlined and contrasted with the classical Knowledge-based approach. A description of the distributed architecture is presented followed by a presentation of the Behaviour-based agents for the two layers. (author)

  12. Wireless Visual Sensor Network Robots- Based for the Emulation of Collective Behavior

    Directory of Open Access Journals (Sweden)

    Fredy Hernán Martinez Sarmiento

    2012-03-01

    Full Text Available We consider the problem of bacterial quorum sensing emulate on small mobile robots. Robots that reflect the behavior of bacteria are designed as mobile wireless camera nodes. They are able to structure a dynamic wireless sensor network. Emulated behavior corresponds to a simplification of bacterial quorum sensing, where the action of a network node is conditioned by the population density of robots(nodes in a given area. The population density reading is done visually using a camera. The robot makes an estimate of the population density of the images, and acts according to this information. The operation of the camera is done with a custom firmware, reducing the complexity of the node without loss of performance. It was noted the route planning and the collective behavior of robots without the use of any other external or local communication. Neither was it necessary to develop a model system, precise state estimation or state feedback.

  13. Novel Adaptive Forward Neural MIMO NARX Model for the Identification of Industrial 3-DOF Robot Arm Kinematics

    Directory of Open Access Journals (Sweden)

    Ho Pham Huy Anh

    2012-10-01

    Full Text Available In this paper, a novel forward adaptive neural MIMO NARX model is used for modelling and identifying the forward kinematics of an industrial 3-DOF robot arm system. The nonlinear features of the forward kinematics of the industrial robot arm drive are thoroughly modelled based on the forward adaptive neural NARX model-based identification process using experimental input-output training data. This paper proposes a novel use of a back propagation (BP algorithm to generate the forward neural MIMO NARX (FNMN model for the forward kinematics of the industrial 3-DOF robot arm. The results show that the proposed adaptive neural NARX model trained by a Back Propagation learning algorithm yields outstanding performance and perfect accuracy.

  14. Design and Implementation of a Bionic Mimosa Robot with Delicate Leaf Swing Behavior

    Directory of Open Access Journals (Sweden)

    Chung-Liang Chang

    2014-12-01

    Full Text Available This study designed and developed a bionic mimosa robot with delicate leaf swing behaviors. For different swing behaviors, this study developed a variety of situations, in which the bionic mimosa robot would display different postures. The core technologies used were Shape Memory Alloys (SMAs, plastic material, and an intelligent control device. The technology particularly focused on the SMAs memory processing bend mode, directional guidance, and the position of SMAs installed inside the plastic material. Performance analysis and evaluation were conducted using two SMAs for mimosa opening/closing behaviors. Finally, by controlling the mimosa behavior with a micro-controller, the optimal strain swing behavior was realized through fuzzy logic control in order to display the different postures of mimosa under different situations. The proposed method is applicable to micro-bionic robot systems, entertainment robots, biomedical engineering, and architectural aesthetics-related fields in the future.

  15. Flowrate behavior and clustering of self-driven robots in a channel

    Science.gov (United States)

    Tian, Bo; Sun, Wang-Ping; Li, Ming; Jiang, Rui; Hu, Mao-Bin

    2018-03-01

    In this paper, the collective motion of self-driven robots is studied experimentally and theoretically. In the channel, the flowrate of robots increases with the density linearly, even if the density of the robots tends to 1.0. There is no abrupt drop in the flowrate, similar to the collective motion of ants. We find that the robots will adjust their velocities by a serial of tiny collisions. The speed-adjustment will affect both robots involved in the collision, and will help to maintain a nearly uniform velocity for the robots. As a result, the flowrate drop will disappear. In the motion, the robots neither gather together nor scatter completely. Instead, they form some clusters to move together. These clusters are not stable during the moving process, but their sizes follow a power-law-alike distribution. We propose a theoretical model to simulate this collective motion process, which can reproduce these behaviors well. Analytic results about the flowrate behavior are also consistent with experiments. Project supported by the Key Research and Development Program, China (Grant No. 2016YFC0802508) and the National Natural Science Foundation of China (Grant Nos. 11672289 and 11422221).

  16. Supervisory Adaptive Network-Based Fuzzy Inference System (SANFIS Design for Empirical Test of Mobile Robot

    Directory of Open Access Journals (Sweden)

    Yi-Jen Mon

    2012-10-01

    Full Text Available A supervisory Adaptive Network-based Fuzzy Inference System (SANFIS is proposed for the empirical control of a mobile robot. This controller includes an ANFIS controller and a supervisory controller. The ANFIS controller is off-line tuned by an adaptive fuzzy inference system, the supervisory controller is designed to compensate for the approximation error between the ANFIS controller and the ideal controller, and drive the trajectory of the system onto a specified surface (called the sliding surface or switching surface while maintaining the trajectory onto this switching surface continuously to guarantee the system stability. This SANFIS controller can achieve favourable empirical control performance of the mobile robot in the empirical tests of driving the mobile robot with a square path. Practical experimental results demonstrate that the proposed SANFIS can achieve better control performance than that achieved using an ANFIS controller for empirical control of the mobile robot.

  17. Human motion behavior while interacting with an industrial robot.

    Science.gov (United States)

    Bortot, Dino; Ding, Hao; Antonopolous, Alexandros; Bengler, Klaus

    2012-01-01

    Human workers and industrial robots both have specific strengths within industrial production. Advantageously they complement each other perfectly, which leads to the development of human-robot interaction (HRI) applications. Bringing humans and robots together in the same workspace may lead to potential collisions. The avoidance of such is a central safety requirement. It can be realized with sundry sensor systems, all of them decelerating the robot when the distance to the human decreases alarmingly and applying the emergency stop, when the distance becomes too small. As a consequence, the efficiency of the overall systems suffers, because the robot has high idle times. Optimized path planning algorithms have to be developed to avoid that. The following study investigates human motion behavior in the proximity of an industrial robot. Three different kinds of encounters between the two entities under three robot speed levels are prompted. A motion tracking system is used to capture the motions. Results show, that humans keep an average distance of about 0,5m to the robot, when the encounter occurs. Approximation of the workbenches is influenced by the robot in ten of 15 cases. Furthermore, an increase of participants' walking velocity with higher robot velocities is observed.

  18. Auto-adaptative Robot-aided Therapy based in 3D Virtual Tasks controlled by a Supervised and Dynamic Neuro-Fuzzy System

    Directory of Open Access Journals (Sweden)

    Luis Daniel Lledó

    2015-03-01

    Full Text Available This paper presents an application formed by a classification method based on the architecture of ART neural network (Adaptive Resonance Theory and the Fuzzy Set Theory to classify physiological reactions in order to automatically and dynamically adapt a robot-assisted rehabilitation therapy to the patient needs, using a three-dimensional task in a virtual reality system. Firstly, the mathematical and structural model of the neuro-fuzzy classification method is described together with the signal and training data acquisition. Then, the virtual designed task with physics behavior and its development procedure are explained. Finally, the general architecture of the experimentation for the auto-adaptive therapy is presented using the classification method with the virtual reality exercise.

  19. On the Evolution of Behaviors through Embodied Imitation.

    Science.gov (United States)

    Erbas, Mehmet D; Bull, Larry; Winfield, Alan F T

    2015-01-01

    This article describes research in which embodied imitation and behavioral adaptation are investigated in collective robotics. We model social learning in artificial agents with real robots. The robots are able to observe and learn each others' movement patterns using their on-board sensors only, so that imitation is embodied. We show that the variations that arise from embodiment allow certain behaviors that are better adapted to the process of imitation to emerge and evolve during multiple cycles of imitation. As these behaviors are more robust to uncertainties in the real robots' sensors and actuators, they can be learned by other members of the collective with higher fidelity. Three different types of learned-behavior memory have been experimentally tested to investigate the effect of memory capacity on the evolution of movement patterns, and results show that as the movement patterns evolve through multiple cycles of imitation, selection, and variation, the robots are able to, in a sense, agree on the structure of the behaviors that are imitated.

  20. Assistance dogs provide a useful behavioral model to enrich communicative skills of assistance robots.

    Science.gov (United States)

    Gácsi, Márta; Szakadát, Sára; Miklósi, Adám

    2013-01-01

    These studies are part of a project aiming to reveal relevant aspects of human-dog interactions, which could serve as a model to design successful human-robot interactions. Presently there are no successfully commercialized assistance robots, however, assistance dogs work efficiently as partners for persons with disabilities. In Study 1, we analyzed the cooperation of 32 assistance dog-owner dyads performing a carrying task. We revealed typical behavior sequences and also differences depending on the dyads' experiences and on whether the owner was a wheelchair user. In Study 2, we investigated dogs' responses to unforeseen difficulties during a retrieving task in two contexts. Dogs displayed specific communicative and displacement behaviors, and a strong commitment to execute the insoluble task. Questionnaire data from Study 3 confirmed that these behaviors could successfully attenuate owners' disappointment. Although owners anticipated the technical competence of future assistance robots to be moderate/high, they could not imagine robots as emotional companions, which negatively affected their acceptance ratings of future robotic assistants. We propose that assistance dogs' cooperative behaviors and problem solving strategies should inspire the development of the relevant functions and social behaviors of assistance robots with limited manual and verbal skills.

  1. Fuzzy Logic Based Behavior Fusion for Navigation of an Intelligent Mobile Robot

    Institute of Scientific and Technical Information of China (English)

    李伟; 陈祖舜; 等

    1996-01-01

    This paper presents a new method for behavior fusion control of a mobile robot in uncertain environments.Using behavior fusion by fuzzy logic,a mobile robot is able to directly execute its motion according to range information about environments,acquired by ultrasonic sensors,without the need for trajectory planning.Based on low-level behavior control,an efficient strategy for integrating high-level global planning for robot motion can be formulated,since,in most applications,some information on environments is prior knowledge.A global planner,therefore,only to generate some subgoal positions rather than exact geometric paths.Because such subgoals can be easily removed from or added into the plannes,this strategy reduces computational time for global planning and is flexible for replanning in dynamic environments.Simulation results demonstrate that the proposed strategy can be applied to robot motion in complex and dynamic environments.

  2. Robotics

    Science.gov (United States)

    Popov, E. P.; Iurevich, E. I.

    The history and the current status of robotics are reviewed, as are the design, operation, and principal applications of industrial robots. Attention is given to programmable robots, robots with adaptive control and elements of artificial intelligence, and remotely controlled robots. The applications of robots discussed include mechanical engineering, cargo handling during transportation and storage, mining, and metallurgy. The future prospects of robotics are briefly outlined.

  3. Robo-AO KP: A new era in robotic adaptive optics

    Science.gov (United States)

    Riddle, Reed L.; Baranec, Christoph; Law, Nicholas M.; Kulkarni, Shrinivas R.; Duev, Dmitry; Ziegler, Carl; Jensen-Clem, Rebecca M.; Atkinson, Dani Eleanor; Tanner, Angelle M.; Zhang, Celia; Ray, Amy

    2016-01-01

    Robo-AO is the first and only fully automated adaptive optics laser guide star AO instrument. It was developed as an instrument for 1-3m robotic telescopes, in order to take advantage of their availability to pursue large survey programs and target of opportunity observations that aren't possible with other AO systems. Robo-AO is currently the most efficient AO system in existence, and it can achieve an observation rate of 20+ science targets per hour. In more than three years of operations at Palomar Observatory, it has been quite successful, producing technology that is being adapted by other AO systems and robotic telescope projects, as well as several high impact scientific publications. Now, Robo-AO has been selected to take over operation of the Kitt Peak National Observatory 2.1m telescope. This will give Robo-AO KP the opportunity to pursue multiple science programs consisting of several thousand targets each during the three years it will be on the telescope. One-sixth of the observing time will be allocated to the US community through the NOAO TAC process. This presentation will discuss the process adapting Robo-AO to the KPNO 2.1m telescope, the plans for integration and initial operations, and the science operations and programs to be pursued.

  4. Behavioral Adaptation and Acceptance

    NARCIS (Netherlands)

    Martens, M.H.; Jenssen, G.D.

    2012-01-01

    One purpose of Intelligent Vehicles is to improve road safety, throughput, and emissions. However, the predicted effects are not always as large as aimed for. Part of this is due to indirect behavioral changes of drivers, also called behavioral adaptation. Behavioral adaptation (BA) refers to

  5. Rhythm Patterns Interaction - Synchronization Behavior for Human-Robot Joint Action

    Science.gov (United States)

    Mörtl, Alexander; Lorenz, Tamara; Hirche, Sandra

    2014-01-01

    Interactive behavior among humans is governed by the dynamics of movement synchronization in a variety of repetitive tasks. This requires the interaction partners to perform for example rhythmic limb swinging or even goal-directed arm movements. Inspired by that essential feature of human interaction, we present a novel concept and design methodology to synthesize goal-directed synchronization behavior for robotic agents in repetitive joint action tasks. The agents’ tasks are described by closed movement trajectories and interpreted as limit cycles, for which instantaneous phase variables are derived based on oscillator theory. Events segmenting the trajectories into multiple primitives are introduced as anchoring points for enhanced synchronization modes. Utilizing both continuous phases and discrete events in a unifying view, we design a continuous dynamical process synchronizing the derived modes. Inverse to the derivation of phases, we also address the generation of goal-directed movements from the behavioral dynamics. The developed concept is implemented to an anthropomorphic robot. For evaluation of the concept an experiment is designed and conducted in which the robot performs a prototypical pick-and-place task jointly with human partners. The effectiveness of the designed behavior is successfully evidenced by objective measures of phase and event synchronization. Feedback gathered from the participants of our exploratory study suggests a subjectively pleasant sense of interaction created by the interactive behavior. The results highlight potential applications of the synchronization concept both in motor coordination among robotic agents and in enhanced social interaction between humanoid agents and humans. PMID:24752212

  6. STDP-based behavior learning on the TriBot robot

    Science.gov (United States)

    Arena, P.; De Fiore, S.; Patané, L.; Pollino, M.; Ventura, C.

    2009-05-01

    This paper describes a correlation-based navigation algorithm, based on an unsupervised learning paradigm for spiking neural networks, called Spike Timing Dependent Plasticity (STDP). This algorithm was implemented on a new bio-inspired hybrid mini-robot called TriBot to learn and increase its behavioral capabilities. In fact correlation based algorithms have been found to explain many basic behaviors in simple animals. The main interesting consequence of STDP is that the system is able to learn high-level sensor features, based on a set of basic reflexes, depending on some low-level sensor inputs. TriBot is composed of 3 modules, the first two being identical and inspired by the Whegs hybrid robot. The peculiar characteristics of the robot consists in the innovative shape of the three-spoke appendages that allow to increase stability of the structure. The last module is composed of two standard legs with 3 degrees of freedom each. Thanks to the cooperation among these modules, TriBot is able to face with irregular terrains overcoming potential deadlock situations, to climb high obstacles compared to its size and to manipulate objects. Robot experiments will be reported to demonstrate the potentiality and the effectiveness of the approach.

  7. Mergeable nervous systems for robots.

    Science.gov (United States)

    Mathews, Nithin; Christensen, Anders Lyhne; O'Grady, Rehan; Mondada, Francesco; Dorigo, Marco

    2017-09-12

    Robots have the potential to display a higher degree of lifetime morphological adaptation than natural organisms. By adopting a modular approach, robots with different capabilities, shapes, and sizes could, in theory, construct and reconfigure themselves as required. However, current modular robots have only been able to display a limited range of hardwired behaviors because they rely solely on distributed control. Here, we present robots whose bodies and control systems can merge to form entirely new robots that retain full sensorimotor control. Our control paradigm enables robots to exhibit properties that go beyond those of any existing machine or of any biological organism: the robots we present can merge to form larger bodies with a single centralized controller, split into separate bodies with independent controllers, and self-heal by removing or replacing malfunctioning body parts. This work takes us closer to robots that can autonomously change their size, form and function.Robots that can self-assemble into different morphologies are desired to perform tasks that require different physical capabilities. Mathews et al. design robots whose bodies and control systems can merge and split to form new robots that retain full sensorimotor control and act as a single entity.

  8. Optimization of Power Utilization in Multimobile Robot Foraging Behavior Inspired by Honeybees System

    Science.gov (United States)

    Ahmad, Faisul Arif; Ramli, Abd Rahman; Samsudin, Khairulmizam; Hashim, Shaiful Jahari

    2014-01-01

    Deploying large numbers of mobile robots which can interact with each other produces swarm intelligent behavior. However, mobile robots are normally running with finite energy resource, supplied from finite battery. The limitation of energy resource required human intervention for recharging the batteries. The sharing information among the mobile robots would be one of the potentials to overcome the limitation on previously recharging system. A new approach is proposed based on integrated intelligent system inspired by foraging of honeybees applied to multimobile robot scenario. This integrated approach caters for both working and foraging stages for known/unknown power station locations. Swarm mobile robot inspired by honeybee is simulated to explore and identify the power station for battery recharging. The mobile robots will share the location information of the power station with each other. The result showed that mobile robots consume less energy and less time when they are cooperating with each other for foraging process. The optimizing of foraging behavior would result in the mobile robots spending more time to do real work. PMID:24949491

  9. An adaptable Boolean net trainable to control a computing robot

    International Nuclear Information System (INIS)

    Lauria, F. E.; Prevete, R.; Milo, M.; Visco, S.

    1999-01-01

    We discuss a method to implement in a Boolean neural network a Hebbian rule so to obtain an adaptable universal control system. We start by presenting both the Boolean neural net and the Hebbian rule we have considered. Then we discuss, first, the problems arising when the latter is naively implemented in a Boolean neural net, second, the method consenting us to overcome them and the ensuing adaptable Boolean neural net paradigm. Next, we present the adaptable Boolean neural net as an intelligent control system, actually controlling a writing robot, and discuss how to train it in the execution of the elementary arithmetic operations on operands represented by numerals with an arbitrary number of digits

  10. Goal-recognition-based adaptive brain-computer interface for navigating immersive robotic systems

    Science.gov (United States)

    Abu-Alqumsan, Mohammad; Ebert, Felix; Peer, Angelika

    2017-06-01

    Objective. This work proposes principled strategies for self-adaptations in EEG-based Brain-computer interfaces (BCIs) as a way out of the bandwidth bottleneck resulting from the considerable mismatch between the low-bandwidth interface and the bandwidth-hungry application, and a way to enable fluent and intuitive interaction in embodiment systems. The main focus is laid upon inferring the hidden target goals of users while navigating in a remote environment as a basis for possible adaptations. Approach. To reason about possible user goals, a general user-agnostic Bayesian update rule is devised to be recursively applied upon the arrival of evidences, i.e. user input and user gaze. Experiments were conducted with healthy subjects within robotic embodiment settings to evaluate the proposed method. These experiments varied along three factors: the type of the robot/environment (simulated and physical), the type of the interface (keyboard or BCI), and the way goal recognition (GR) is used to guide a simple shared control (SC) driving scheme. Main results. Our results show that the proposed GR algorithm is able to track and infer the hidden user goals with relatively high precision and recall. Further, the realized SC driving scheme benefits from the output of the GR system and is able to reduce the user effort needed to accomplish the assigned tasks. Despite the fact that the BCI requires higher effort compared to the keyboard conditions, most subjects were able to complete the assigned tasks, and the proposed GR system is additionally shown able to handle the uncertainty in user input during SSVEP-based interaction. The SC application of the belief vector indicates that the benefits of the GR module are more pronounced for BCIs, compared to the keyboard interface. Significance. Being based on intuitive heuristics that model the behavior of the general population during the execution of navigation tasks, the proposed GR method can be used without prior tuning for the

  11. Control of autonomous robot using neural networks

    Science.gov (United States)

    Barton, Adam; Volna, Eva

    2017-07-01

    The aim of the article is to design a method of control of an autonomous robot using artificial neural networks. The introductory part describes control issues from the perspective of autonomous robot navigation and the current mobile robots controlled by neural networks. The core of the article is the design of the controlling neural network, and generation and filtration of the training set using ART1 (Adaptive Resonance Theory). The outcome of the practical part is an assembled Lego Mindstorms EV3 robot solving the problem of avoiding obstacles in space. To verify models of an autonomous robot behavior, a set of experiments was created as well as evaluation criteria. The speed of each motor was adjusted by the controlling neural network with respect to the situation in which the robot was found.

  12. Evolution of Signaling in a Multi-Robot System: Categorization and Communication

    Science.gov (United States)

    Ampatzis, Christos; Tuci, Elio; Trianni, Vito; Dorigo, Marco

    We use Evolutionary Robotics to design robot controllers in which decision-making mechanisms to switch from solitary to social behavior are integrated with the mechanisms that underpin the sensory-motor repertoire of the robots. In particular, we study the evolution of behavioral and communicative skills in a categorization task. The individual decision-making structures are based on the integration over time of sensory information. The mechanisms for switching from solitary to social behavior and the ways in which the robots can affect each other's behavior are not predetermined by the experimenter, but are aspects of our model designed by artificial evolution. Our results show that evolved robots manage to cooperate and collectively discriminate between different environments by developing a simple communication protocol based on sound signaling. Communication emerges in the absence of explicit selective pressure coded in the fitness function. The evolution of communication is neither trivial nor obvious; for a meaningful signaling system to evolve, evolution must produce both appropriate signals and appropriate reactions to signals. The use of communication proves to be adaptive for the group, even if, in principle, non-cooperating robots can be equally successful with cooperating robots.

  13. Adaptive Hybrid Visual Servo Regulation of Mobile Robots Based on Fast Homography Decomposition

    Directory of Open Access Journals (Sweden)

    Chunfu Wu

    2015-01-01

    Full Text Available For the monocular camera-based mobile robot system, an adaptive hybrid visual servo regulation algorithm which is based on a fast homography decomposition method is proposed to drive the mobile robot to its desired position and orientation, even when object’s imaging depth and camera’s position extrinsic parameters are unknown. Firstly, the homography’s particular properties caused by mobile robot’s 2-DOF motion are taken into account to induce a fast homography decomposition method. Secondly, the homography matrix and the extracted orientation error, incorporated with the desired view’s single feature point, are utilized to form an error vector and its open-loop error function. Finally, Lyapunov-based techniques are exploited to construct an adaptive regulation control law, followed by the experimental verification. The experimental results show that the proposed fast homography decomposition method is not only simple and efficient, but also highly precise. Meanwhile, the designed control law can well enable mobile robot position and orientation regulation despite the lack of depth information and camera’s position extrinsic parameters.

  14. Improving the Adaptability of Simulated Evolutionary Swarm Robots in Dynamically Changing Environments

    Science.gov (United States)

    Yao, Yao; Marchal, Kathleen; Van de Peer, Yves

    2014-01-01

    One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN). An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store ‘good behaviour’ and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment. PMID:24599485

  15. Improving the adaptability of simulated evolutionary swarm robots in dynamically changing environments.

    Directory of Open Access Journals (Sweden)

    Yao Yao

    Full Text Available One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN. An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store 'good behaviour' and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment.

  16. micROS: a morphable, intelligent and collective robot operating system.

    Science.gov (United States)

    Yang, Xuejun; Dai, Huadong; Yi, Xiaodong; Wang, Yanzhen; Yang, Shaowu; Zhang, Bo; Wang, Zhiyuan; Zhou, Yun; Peng, Xuefeng

    2016-01-01

    Robots are developing in much the same way that personal computers did 40 years ago, and robot operating system is the critical basis. Current robot software is mainly designed for individual robots. We present in this paper the design of micROS, a morphable, intelligent and collective robot operating system for future collective and collaborative robots. We first present the architecture of micROS, including the distributed architecture for collective robot system as a whole and the layered architecture for every single node. We then present the design of autonomous behavior management based on the observe-orient-decide-act cognitive behavior model and the design of collective intelligence including collective perception, collective cognition, collective game and collective dynamics. We also give the design of morphable resource management, which first categorizes robot resources into physical, information, cognitive and social domains, and then achieve morphability based on self-adaptive software technology. We finally deploy micROS on NuBot football robots and achieve significant improvement in real-time performance.

  17. An adaptive unscented Kalman filter-based adaptive tracking control for wheeled mobile robots with control constrains in the presence of wheel slipping

    Directory of Open Access Journals (Sweden)

    Mingyue Cui

    2016-09-01

    Full Text Available A novel control approach is proposed for trajectory tracking of a wheeled mobile robot with unknown wheels’ slipping. The longitudinal and lateral slipping are considered and processed as three time-varying parameters. The adaptive unscented Kalman filter is then designed to estimate the slipping parameters online, an adaptive adjustment of the noise covariances in the estimation process is implemented using a technique of covariance matching in the adaptive unscented Kalman filter context. Considering the practical physical constrains, a stable tracking control law for this robot system is proposed by the backstepping method. Asymptotic stability is guaranteed by Lyapunov stability theory. Control gains are determined online by applying pole placement method. Simulation and real experiment results show the effectiveness and robustness of the proposed control method.

  18. Portraits of self-organization in fish schools interacting with robots

    Science.gov (United States)

    Aureli, M.; Fiorilli, F.; Porfiri, M.

    2012-05-01

    In this paper, we propose an enabling computational and theoretical framework for the analysis of experimental instances of collective behavior in response to external stimuli. In particular, this work addresses the characterization of aggregation and interaction phenomena in robot-animal groups through the exemplary analysis of fish schooling in the vicinity of a biomimetic robot. We adapt global observables from statistical mechanics to capture the main features of the shoal collective motion and its response to the robot from experimental observations. We investigate the shoal behavior by using a diffusion mapping analysis performed on these global observables that also informs the definition of relevant portraits of self-organization.

  19. Information driven self-organization of complex robotic behaviors.

    Directory of Open Access Journals (Sweden)

    Georg Martius

    Full Text Available Information theory is a powerful tool to express principles to drive autonomous systems because it is domain invariant and allows for an intuitive interpretation. This paper studies the use of the predictive information (PI, also called excess entropy or effective measure complexity, of the sensorimotor process as a driving force to generate behavior. We study nonlinear and nonstationary systems and introduce the time-local predicting information (TiPI which allows us to derive exact results together with explicit update rules for the parameters of the controller in the dynamical systems framework. In this way the information principle, formulated at the level of behavior, is translated to the dynamics of the synapses. We underpin our results with a number of case studies with high-dimensional robotic systems. We show the spontaneous cooperativity in a complex physical system with decentralized control. Moreover, a jointly controlled humanoid robot develops a high behavioral variety depending on its physics and the environment it is dynamically embedded into. The behavior can be decomposed into a succession of low-dimensional modes that increasingly explore the behavior space. This is a promising way to avoid the curse of dimensionality which hinders learning systems to scale well.

  20. A Novel Low-Cost Adaptive Scanner Concept for Mobile Robots

    Directory of Open Access Journals (Sweden)

    Ivo Stančić

    2014-09-01

    Full Text Available A fundamental problem in mobile robot applications is the need for accurate knowledge of the position of a vehicle for localizing itself and for avoiding obstacles in its path. In the search for a solution to this problem, researchers and engineers have developed different sensors, systems and techniques. Modern mobile robots relay information obtained from a variety of sensors and sophisticated data fusion algorithms. In this paper, a novel concept for a low-cost adaptive scanner based on a projected light pattern is proposed. The main advantage of the proposed system is its adaptivity, which enables the rapid scanning of the robot’s surroundings in search of obstacles and a more detailed scan of a single object to retrieve its surface configuration and perform some limited analyses. This paper addresses the concept behind such a scanner, where a proof-of-concept is achieved using an office DLP projector. During the measurements, the accuracy of the proposed system was tested on obstacles and objects with known configurations. The obtained results are presented and analyzed, and conclusions about the system’s performance and possible improvements are discussed.

  1. Adaptive Robotic Fabrication for Conditions of Material Inconsistency

    DEFF Research Database (Denmark)

    Nicholas, Paul; Zwierzycki, Mateusz; Clausen Nørgaard, Esben

    2017-01-01

    This paper describes research that addresses the variable behaviour of industrial quality metals and the extension of computational techniques into the fabrication process. It describes the context of robotic incremental sheet metal forming, a freeform method for imparting 3D form onto a 2D thin...... and the fabrication process? Here, two adaptive methods are presented that aim to increase forming accuracy with only a minimum increase in fabrication time, and that maintain ongoing input from the results of the fabrication process. The first method is an online sensor-based strategy and the second method...

  2. Novel Adaptive Forward Neural MIMO NARX Model for the Identification of Industrial 3-DOF Robot Arm Kinematics

    OpenAIRE

    Ho Pham Huy Anh; Nguyen Thanh Nam

    2012-01-01

    In this paper, a novel forward adaptive neural MIMO NARX model is used for modelling and identifying the forward kinematics of an industrial 3‐DOF robot arm system. The nonlinear features of the forward kinematics of the industrial robot arm drive are thoroughly modelled based on the forward adaptive neural NARX model‐based identification process using experimental input‐output training data. This paper proposes a novel use of a back propagation (BP) algorithm to generate the forward neural M...

  3. What happens when a robot favors someone? How a tour guide robot uses gaze behavior to address multiple persons while storytelling about art

    NARCIS (Netherlands)

    Karreman, Daphne Eleonora; Sépulveda Bradford, Gilberto; van Dijk, Elisabeth M.A.G.; Lohse, M.; Evers, Vanessa

    2013-01-01

    We report intermediate results of an ongoing study into the effectiveness of robot gaze behaviors when addressing multiple persons. The work is being carried out as part of the EU FP7 project FROG and concerns the design and evaluation of interactive behaviors of a tour guide robot. Our objective is

  4. Design and Experimental Development of a Pneumatic Stiffness Adjustable Foot System for Biped Robots Adaptable to Bumps on the Ground

    Directory of Open Access Journals (Sweden)

    Xizhe Zang

    2017-09-01

    Full Text Available Walking on rough terrains still remains a challenge that needs to be addressed for biped robots because the unevenness on the ground can easily disrupt the walking stability. This paper proposes a novel foot system with passively adjustable stiffness for biped robots which is adaptable to small-sized bumps on the ground. The robotic foot is developed by attaching eight pneumatic variable stiffness units to the sole separately and symmetrically. Each variable stiffness unit mainly consists of a pneumatic bladder and a mechanical reversing valve. When walking on rough ground, the pneumatic bladders in contact with bumps are compressed, and the corresponding reversing valves are triggered to expel out the air, enabling the pneumatic bladders to adapt to the bumps with low stiffness; while the other pneumatic bladders remain rigid and maintain stable contact with the ground, providing support to the biped robot. The performances of the proposed foot system, including the variable stiffness mechanism, the adaptability on the bumps of different heights, and the application on a biped robot prototype are demonstrated by various experiments.

  5. Artificial emotion triggered stochastic behavior transitions with motivational gain effects for multi-objective robot tasks

    Science.gov (United States)

    Dağlarli, Evren; Temeltaş, Hakan

    2007-04-01

    This paper presents artificial emotional system based autonomous robot control architecture. Hidden Markov model developed as mathematical background for stochastic emotional and behavior transitions. Motivation module of architecture considered as behavioral gain effect generator for achieving multi-objective robot tasks. According to emotional and behavioral state transition probabilities, artificial emotions determine sequences of behaviors. Also motivational gain effects of proposed architecture can be observed on the executing behaviors during simulation.

  6. Generic robot architecture

    Science.gov (United States)

    Bruemmer, David J [Idaho Falls, ID; Few, Douglas A [Idaho Falls, ID

    2010-09-21

    The present invention provides methods, computer readable media, and apparatuses for a generic robot architecture providing a framework that is easily portable to a variety of robot platforms and is configured to provide hardware abstractions, abstractions for generic robot attributes, environment abstractions, and robot behaviors. The generic robot architecture includes a hardware abstraction level and a robot abstraction level. The hardware abstraction level is configured for developing hardware abstractions that define, monitor, and control hardware modules available on a robot platform. The robot abstraction level is configured for defining robot attributes and provides a software framework for building robot behaviors from the robot attributes. Each of the robot attributes includes hardware information from at least one hardware abstraction. In addition, each robot attribute is configured to substantially isolate the robot behaviors from the at least one hardware abstraction.

  7. A Human-Robot Co-Manipulation Approach Based on Human Sensorimotor Information.

    Science.gov (United States)

    Peternel, Luka; Tsagarakis, Nikos; Ajoudani, Arash

    2017-07-01

    This paper aims to improve the interaction and coordination between the human and the robot in cooperative execution of complex, powerful, and dynamic tasks. We propose a novel approach that integrates online information about the human motor function and manipulability properties into the hybrid controller of the assistive robot. Through this human-in-the-loop framework, the robot can adapt to the human motor behavior and provide the appropriate assistive response in different phases of the cooperative task. We experimentally evaluate the proposed approach in two human-robot co-manipulation tasks that require specific complementary behavior from the two agents. Results suggest that the proposed technique, which relies on a minimum degree of task-level pre-programming, can achieve an enhanced physical human-robot interaction performance and deliver appropriate level of assistance to the human operator.

  8. Robot vision

    International Nuclear Information System (INIS)

    Hall, E.L.

    1984-01-01

    Almost all industrial robots use internal sensors such as shaft encoders which measure rotary position, or tachometers which measure velocity, to control their motions. Most controllers also provide interface capabilities so that signals from conveyors, machine tools, and the robot itself may be used to accomplish a task. However, advanced external sensors, such as visual sensors, can provide a much greater degree of adaptability for robot control as well as add automatic inspection capabilities to the industrial robot. Visual and other sensors are now being used in fundamental operations such as material processing with immediate inspection, material handling with adaption, arc welding, and complex assembly tasks. A new industry of robot vision has emerged. The application of these systems is an area of great potential

  9. Engineering the evolution of self-organizing behaviors in swarm robotics: a case study.

    Science.gov (United States)

    Trianni, Vito; Nolfi, Stefano

    2011-01-01

    Evolutionary robotics (ER) is a powerful approach for the automatic synthesis of robot controllers, as it requires little a priori knowledge about the problem to be solved in order to obtain good solutions. This is particularly true for collective and swarm robotics, in which the desired behavior of the group is an indirect result of the control and communication rules followed by each individual. However, the experimenter must make several arbitrary choices in setting up the evolutionary process, in order to define the correct selective pressures that can lead to the desired results. In some cases, only a deep understanding of the obtained results can point to the critical aspects that constrain the system, which can be later modified in order to re-engineer the evolutionary process towards better solutions. In this article, we discuss the problem of engineering the evolutionary machinery that can lead to the desired result in the swarm robotics context. We also present a case study about self-organizing synchronization in a swarm of robots, in which some arbitrarily chosen properties of the communication system hinder the scalability of the behavior to large groups. We show that by modifying the communication system, artificial evolution can synthesize behaviors that scale properly with the group size.

  10. Adaptive Behavior and Problem Behavior in Young Children with Williams Syndrome

    Science.gov (United States)

    Hahn, Laura J.; Fidler, Deborah J.; Hepburn, Susan L.

    2014-01-01

    The present study compares the adaptive behavior profile of 18 young children with Williams syndrome (WS) and a developmentally matched group of 19 children with developmental disabilities and examines the relationship between adaptive behavior and problem behaviors in WS. Parents completed the Vineland Adaptive Behavioral Scales--Interview…

  11. Adaptive behavior of children with visual impairment

    OpenAIRE

    Anđelković Marija

    2014-01-01

    Adaptive behavior includes a wide range of skills necessary for independent, safe and adequate performance of everyday activities. Practical, social and conceptual skills make the concept of adaptive behavior. The aim of this paper is to provide an insight into the existing studies of adaptive behavior in persons with visual impairment. The paper mainly focuses on the research on adaptive behavior in children with visual impairment. The results show that the acquisition of adaptive skills is ...

  12. TEXPLORE temporal difference reinforcement learning for robots and time-constrained domains

    CERN Document Server

    Hester, Todd

    2013-01-01

    This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time. Robots have the potential to solve many problems in society, because of their ability to work in dangerous places doing necessary jobs that no one wants or is able to do. One barrier to their widespread deployment is that they are mainly limited to tasks where it is possible to hand-program behaviors for every situation that may be encountered. For robots to meet their potential, they need methods that enable them to learn and adapt to novel situations that they were not programmed for. Reinforcement learning (RL) is a paradigm for learning sequential decision making processes and could solve the problems of learning and adaptation on robots. This book identifies four key challenges that must be addressed for an RL algorithm to be practical for robotic control tasks. These RL for Robotics Challenges are: 1) it must learn in very few samples; 2) it must learn in domains with continuou...

  13. You Look Human, But Act Like a Machine: Agent Appearance and Behavior Modulate Different Aspects of Human–Robot Interaction

    Directory of Open Access Journals (Sweden)

    Abdulaziz Abubshait

    2017-08-01

    Full Text Available Gaze following occurs automatically in social interactions, but the degree to which gaze is followed depends on whether an agent is perceived to have a mind, making its behavior socially more relevant for the interaction. Mind perception also modulates the attitudes we have toward others, and determines the degree of empathy, prosociality, and morality invested in social interactions. Seeing mind in others is not exclusive to human agents, but mind can also be ascribed to non-human agents like robots, as long as their appearance and/or behavior allows them to be perceived as intentional beings. Previous studies have shown that human appearance and reliable behavior induce mind perception to robot agents, and positively affect attitudes and performance in human–robot interaction. What has not been investigated so far is whether different triggers of mind perception have an independent or interactive effect on attitudes and performance in human–robot interaction. We examine this question by manipulating agent appearance (human vs. robot and behavior (reliable vs. random within the same paradigm and examine how congruent (human/reliable vs. robot/random versus incongruent (human/random vs. robot/reliable combinations of these triggers affect performance (i.e., gaze following and attitudes (i.e., agent ratings in human–robot interaction. The results show that both appearance and behavior affect human–robot interaction but that the two triggers seem to operate in isolation, with appearance more strongly impacting attitudes, and behavior more strongly affecting performance. The implications of these findings for human–robot interaction are discussed.

  14. You Look Human, But Act Like a Machine: Agent Appearance and Behavior Modulate Different Aspects of Human-Robot Interaction.

    Science.gov (United States)

    Abubshait, Abdulaziz; Wiese, Eva

    2017-01-01

    Gaze following occurs automatically in social interactions, but the degree to which gaze is followed depends on whether an agent is perceived to have a mind, making its behavior socially more relevant for the interaction. Mind perception also modulates the attitudes we have toward others, and determines the degree of empathy, prosociality, and morality invested in social interactions. Seeing mind in others is not exclusive to human agents, but mind can also be ascribed to non-human agents like robots, as long as their appearance and/or behavior allows them to be perceived as intentional beings. Previous studies have shown that human appearance and reliable behavior induce mind perception to robot agents, and positively affect attitudes and performance in human-robot interaction. What has not been investigated so far is whether different triggers of mind perception have an independent or interactive effect on attitudes and performance in human-robot interaction. We examine this question by manipulating agent appearance (human vs. robot) and behavior (reliable vs. random) within the same paradigm and examine how congruent (human/reliable vs. robot/random) versus incongruent (human/random vs. robot/reliable) combinations of these triggers affect performance (i.e., gaze following) and attitudes (i.e., agent ratings) in human-robot interaction. The results show that both appearance and behavior affect human-robot interaction but that the two triggers seem to operate in isolation, with appearance more strongly impacting attitudes, and behavior more strongly affecting performance. The implications of these findings for human-robot interaction are discussed.

  15. Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot

    Directory of Open Access Journals (Sweden)

    Qingsong Ai

    2017-12-01

    Full Text Available A rehabilitation robot plays an important role in relieving the therapists’ burden and helping patients with ankle injuries to perform more accurate and effective rehabilitation training. However, a majority of current ankle rehabilitation robots are rigid and have drawbacks in terms of complex structure, poor flexibility and lack of safety. Taking advantages of pneumatic muscles’ good flexibility and light weight, we developed a novel two degrees of freedom (2-DOF parallel compliant ankle rehabilitation robot actuated by pneumatic muscles (PMs. To solve the PM’s nonlinear characteristics during operation and to tackle the human-robot uncertainties in rehabilitation, an adaptive backstepping sliding mode control (ABS-SMC method is proposed in this paper. The human-robot external disturbance can be estimated by an observer, who is then used to adjust the robot output to accommodate external changes. The system stability is guaranteed by the Lyapunov stability theorem. Experimental results on the compliant ankle rehabilitation robot show that the proposed ABS-SMC is able to estimate the external disturbance online and adjust the control output in real time during operation, resulting in a higher trajectory tracking accuracy and better response performance especially in dynamic conditions.

  16. Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot.

    Science.gov (United States)

    Ai, Qingsong; Zhu, Chengxiang; Zuo, Jie; Meng, Wei; Liu, Quan; Xie, Sheng Q; Yang, Ming

    2017-12-28

    A rehabilitation robot plays an important role in relieving the therapists' burden and helping patients with ankle injuries to perform more accurate and effective rehabilitation training. However, a majority of current ankle rehabilitation robots are rigid and have drawbacks in terms of complex structure, poor flexibility and lack of safety. Taking advantages of pneumatic muscles' good flexibility and light weight, we developed a novel two degrees of freedom (2-DOF) parallel compliant ankle rehabilitation robot actuated by pneumatic muscles (PMs). To solve the PM's nonlinear characteristics during operation and to tackle the human-robot uncertainties in rehabilitation, an adaptive backstepping sliding mode control (ABS-SMC) method is proposed in this paper. The human-robot external disturbance can be estimated by an observer, who is then used to adjust the robot output to accommodate external changes. The system stability is guaranteed by the Lyapunov stability theorem. Experimental results on the compliant ankle rehabilitation robot show that the proposed ABS-SMC is able to estimate the external disturbance online and adjust the control output in real time during operation, resulting in a higher trajectory tracking accuracy and better response performance especially in dynamic conditions.

  17. Affective and behavioral responses to robot-initiated social touch : Towards understanding the opportunities and limitations of physical contact in human-robot interaction

    NARCIS (Netherlands)

    Willemse, C.J.A.M.; Toet, A.; Erp, J.B.F. van

    2017-01-01

    Social touch forms an important aspect of the human non-verbal communication repertoire, but is often overlooked in human–robot interaction. In this study, we investigated whether robot-initiated touches can induce physiological, emotional, and behavioral responses similar to those reported for

  18. Affective and Behavioral Responses to Robot-Initiated Social Touch : Toward Understanding the Opportunities and Limitations of Physical Contact in Human–Robot Interaction

    NARCIS (Netherlands)

    Willemse, Christian J. A. M.; Toet, Alexander; van Erp, Jan B. F.

    2017-01-01

    Social touch forms an important aspect of the human non-verbal communication repertoire, but is often overlooked in human-robot interaction. In this study, we investigated whether robot-initiated touches can induce physiological, emotional, and behavioral responses similar to those reported for

  19. A biologically inspired meta-control navigation system for the Psikharpax rat robot

    International Nuclear Information System (INIS)

    Caluwaerts, K; Staffa, M; N’Guyen, S; Grand, C; Dollé, L; Favre-Félix, A; Girard, B; Khamassi, M

    2012-01-01

    A biologically inspired navigation system for the mobile rat-like robot named Psikharpax is presented, allowing for self-localization and autonomous navigation in an initially unknown environment. The ability of parts of the model (e.g. the strategy selection mechanism) to reproduce rat behavioral data in various maze tasks has been validated before in simulations. But the capacity of the model to work on a real robot platform had not been tested. This paper presents our work on the implementation on the Psikharpax robot of two independent navigation strategies (a place-based planning strategy and a cue-guided taxon strategy) and a strategy selection meta-controller. We show how our robot can memorize which was the optimal strategy in each situation, by means of a reinforcement learning algorithm. Moreover, a context detector enables the controller to quickly adapt to changes in the environment—recognized as new contexts—and to restore previously acquired strategy preferences when a previously experienced context is recognized. This produces adaptivity closer to rat behavioral performance and constitutes a computational proposition of the role of the rat prefrontal cortex in strategy shifting. Moreover, such a brain-inspired meta-controller may provide an advancement for learning architectures in robotics. (paper)

  20. Adaptive locomotor training on an end-effector gait robot: evaluation of the ground reaction forces in different training conditions.

    Science.gov (United States)

    Tomelleri, Christopher; Waldner, Andreas; Werner, Cordula; Hesse, Stefan

    2011-01-01

    The main goal of robotic gait rehabilitation is the restoration of independent gait. To achieve this goal different and specific patterns have to be practiced intensively in order to stimulate the learning process of the central nervous system. The gait robot G-EO Systems was designed to allow the repetitive practice of floor walking, stair climbing and stair descending. A novel control strategy allows training in adaptive mode. The force interactions between the foot and the ground were analyzed on 8 healthy volunteers in three different conditions: real floor walking on a treadmill, floor walking on the gait robot in passive mode, floor walking on the gait robot in adaptive mode. The ground reaction forces were measured by a Computer Dyno Graphy (CDG) analysis system. The results show different intensities of the ground reaction force across all of the three conditions. The intensities of force interactions during the adaptive training mode are comparable to the real walking on the treadmill. Slight deviations still occur in regard to the timing pattern of the forces. The adaptive control strategy comes closer to the physiological swing phase than the passive mode and seems to be a promising option for the treatment of gait disorders. Clinical trials will validate the efficacy of this new option in locomotor therapy on the patients. © 2011 IEEE

  1. Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots.

    Science.gov (United States)

    Duarte, Miguel; Costa, Vasco; Gomes, Jorge; Rodrigues, Tiago; Silva, Fernando; Oliveira, Sancho Moura; Christensen, Anders Lyhne

    2016-01-01

    Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.

  2. Influences of a Socially Interactive Robot on the Affective Behavior of Young Children with Disabilities. Social Robots Research Reports, Number 3

    Science.gov (United States)

    Dunst, Carl J.; Prior, Jeremy; Hamby, Deborah W.; Trivette, Carol M.

    2013-01-01

    Findings from two studies of 11 young children with autism, Down syndrome, or attention deficit disorders investigating the effects of Popchilla, a socially interactive robot, on the children's affective behavior are reported. The children were observed under two conditions, child-toy interactions and child-robot interactions, and ratings of child…

  3. Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human–Robot Interaction

    Directory of Open Access Journals (Sweden)

    Juan M. Gandarias

    2018-02-01

    Full Text Available The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM. Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more, with a lower mean of pressure values (up to 72% less than when using a rigid sensor, with a softer grip, which is needed in physical human–robot interaction (pHRI. A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78% with a rigid sensor.

  4. Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human-Robot Interaction.

    Science.gov (United States)

    Gandarias, Juan M; Gómez-de-Gabriel, Jesús M; García-Cerezo, Alfonso J

    2018-02-26

    The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs) using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM). Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more), with a lower mean of pressure values (up to 72% less) than when using a rigid sensor, with a softer grip, which is needed in physical human-robot interaction (pHRI). A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78%) with a rigid sensor.

  5. Distributed control of multi-robot teams: Cooperative baton passing task

    Energy Technology Data Exchange (ETDEWEB)

    Parker, L.E.

    1998-11-01

    This research addresses the problem of achieving fault tolerant cooperation within small- to medium-sized teams of heterogeneous mobile robots. The author describes a novel behavior-based, fully distributed architecture, called ALLIANCE, that utilizes adaptive action selection to achieve fault tolerant cooperative control. The robots in this architecture possess a variety of high-level functions that they can perform during a mission, and must at all times select an appropriate action based on the requirements of the mission, the activities of other robots, the current environmental conditions, and their own internal states. Since such cooperative teams often work in dynamic and unpredictable environments, the software architecture allows the team members to respond robustly and reliably to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. After presenting ALLIANCE, they describe the implementation of this architecture on a team of physical mobile robots performing a cooperative baton passing task. These experiments illustrate the ability of ALLIANCE to achieve adaptive, fault-tolerant cooperative control amidst dynamic changes during the task.

  6. Influence of robotic shoal size, configuration, and activity on zebrafish behavior in a free-swimming environment.

    Science.gov (United States)

    Butail, Sachit; Polverino, Giovanni; Phamduy, Paul; Del Sette, Fausto; Porfiri, Maurizio

    2014-12-15

    In animal studies, robots have been recently used as a valid tool for testing a wide spectrum of hypotheses. These robots often exploit visual or auditory cues to modulate animal behavior. The propensity of zebrafish, a model organism in biological studies, toward fish with similar color patterns and shape has been leveraged to design biologically inspired robots that successfully attract zebrafish in preference tests. With an aim of extending the application of such robots to field studies, here, we investigate the response of zebrafish to multiple robotic fish swimming at different speeds and in varying arrangements. A soft real-time multi-target tracking and control system remotely steers the robots in circular trajectories during the experimental trials. Our findings indicate a complex behavioral response of zebrafish to biologically inspired robots. More robots produce a significant change in salient measures of stress, with a fast robot swimming alone causing more freezing and erratic activity than two robots swimming slowly together. In addition, fish spend more time in the proximity of a robot when they swim far apart than when the robots swim close to each other. Increase in the number of robots also significantly alters the degree of alignment of fish motion with a robot. Results from this study are expected to advance our understanding of robot perception by live animals and aid in hypothesis-driven studies in unconstrained free-swimming environments. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning

    Directory of Open Access Journals (Sweden)

    Nizar Hadi Abbas

    2016-07-01

    Full Text Available This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In order to evaluate the proposed algorithm in term of finding the best solution, six benchmark test functions are used to make a comparison between AMOPSO and the standard MOPSO. The results show that the AMOPSO has a better ability to get away from local optimums with a quickest convergence than the MOPSO. The simulation results using Matlab 2014a, indicate that this methodology is extremely valuable for every robot in multi-robot framework to discover its own particular proper pa‌th from the start to the destination position with minimum distance and time.

  8. Dynamic whole-body robotic manipulation

    Science.gov (United States)

    Abe, Yeuhi; Stephens, Benjamin; Murphy, Michael P.; Rizzi, Alfred A.

    2013-05-01

    The creation of dynamic manipulation behaviors for high degree of freedom, mobile robots will allow them to accomplish increasingly difficult tasks in the field. We are investigating how the coordinated use of the body, legs, and integrated manipulator, on a mobile robot, can improve the strength, velocity, and workspace when handling heavy objects. We envision that such a capability would aid in a search and rescue scenario when clearing obstacles from a path or searching a rubble pile quickly. Manipulating heavy objects is especially challenging because the dynamic forces are high and a legged system must coordinate all its degrees of freedom to accomplish tasks while maintaining balance. To accomplish these types of manipulation tasks, we use trajectory optimization techniques to generate feasible open-loop behaviors for our 28 dof quadruped robot (BigDog) by planning trajectories in a 13 dimensional space. We apply the Covariance Matrix Adaptation (CMA) algorithm to solve for trajectories that optimize task performance while also obeying important constraints such as torque and velocity limits, kinematic limits, and center of pressure location. These open-loop behaviors are then used to generate desired feed-forward body forces and foot step locations, which enable tracking on the robot. Some hardware results for cinderblock throwing are demonstrated on the BigDog quadruped platform augmented with a human-arm-like manipulator. The results are analogous to how a human athlete maximizes distance in the discus event by performing a precise sequence of choreographed steps.

  9. Learning Semantics of Gestural Instructions for Human-Robot Collaboration

    Science.gov (United States)

    Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

    2018-01-01

    Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions. PMID:29615888

  10. Learning Semantics of Gestural Instructions for Human-Robot Collaboration.

    Science.gov (United States)

    Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

    2018-01-01

    Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions.

  11. Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human--Robot Interaction

    Directory of Open Access Journals (Sweden)

    Tatsuro Yamada

    2016-07-01

    Full Text Available To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language--behavior relationships and the temporal patterns of interaction. Here, ``internal dynamics'' refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language--behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language--behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

  12. Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

    Science.gov (United States)

    Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

    2016-01-01

    To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

  13. Effects of Interruptibility-Aware Robot Behavior

    OpenAIRE

    Banerjee, Siddhartha; Silva, Andrew; Feigh, Karen; Chernova, Sonia

    2018-01-01

    As robots become increasingly prevalent in human environments, there will inevitably be times when a robot needs to interrupt a human to initiate an interaction. Our work introduces the first interruptibility-aware mobile robot system, and evaluates the effects of interruptibility-awareness on human task performance, robot task performance, and on human interpretation of the robot's social aptitude. Our results show that our robot is effective at predicting interruptibility at high accuracy, ...

  14. Adaptive control of 5 DOF upper-limb exoskeleton robot with improved safety.

    Science.gov (United States)

    Kang, Hao-Bo; Wang, Jian-Hui

    2013-11-01

    This paper studies an adaptive control strategy for a class of 5 DOF upper-limb exoskeleton robot with a special safety consideration. The safety requirement plays a critical role in the clinical treatment when assisting patients with shoulder, elbow and wrist joint movements. With the objective of assuring the tracking performance of the pre-specified operations, the proposed adaptive controller is firstly designed to be robust to the model uncertainties. To further improve the safety and fault-tolerance in the presence of unknown large parameter variances or even actuator faults, the adaptive controller is on-line updated according to the information provided by an adaptive observer without additional sensors. An output tracking performance is well achieved with a tunable error bound. The experimental example also verifies the effectiveness of the proposed control scheme. © 2013 ISA. Published by ISA. All rights reserved.

  15. On the applicability of the decentralized control mechanism extracted from the true slime mold: a robotic case study with a serpentine robot

    International Nuclear Information System (INIS)

    Sato, Takahide; Kano, Takeshi; Ishiguro, Akio

    2011-01-01

    A systematic method for an autonomous decentralized control system is still lacking, despite its appealing concept. In order to alleviate this, we focused on the amoeboid locomotion of the true slime mold, and extracted a design scheme for the decentralized control mechanism that leads to adaptive behavior for the entire system, based on the so-called discrepancy function. In this paper, we intensively investigate the universality of this design scheme by applying it to a different type of locomotion based on a 'synthetic approach'. As a first step, we implement this design scheme to the control of a real physical two-dimensional serpentine robot that exhibits slithering locomotion. The experimental results show that the robot exhibits adaptive behavior and responds to the environmental changes; it is also robust against malfunctions of the body segments due to the local sensory feedback control that is based on the discrepancy function. We expect the results to shed new light on the methodology of autonomous decentralized control systems.

  16. Task oriented evaluation system for maintenance robots

    International Nuclear Information System (INIS)

    Asame, Hajime; Endo, Isao; Kotosaka, Shin-ya; Takata, Shozo; Hiraoka, Hiroyuki; Kohda, Takehisa; Matsumoto, Akihiro; Yamagishi, Kiichiro.

    1994-01-01

    The adaptability evaluation of maintenance robots to autonomous plants has been discussed. In this paper, a new concept of autonomous plant with maintenance robots are introduced, and a framework of autonomous maintenance system is proposed. Then, task-oriented evaluation of robot arms is discussed for evaluating their adaptability to maintenance tasks, and a new criterion called operability is proposed for adaptability evaluation. The task-oriented evaluation system is implemented and applied to structural design of robot arms. Using genetic algorithm, an optimal structure adaptable to a pump disassembly task is obtained. (author)

  17. Distributed multi-robot sensing and tracking: a behavior-based approach

    International Nuclear Information System (INIS)

    Parker, L.E.

    1995-01-01

    An important issue that arises in the automation of many large-scale surveillance and reconnaissance tasks is that of tracking the movements of (or maintaining passive contact with) objects navigating in a bounded area of interest. Oftentimes in these problems, the area to be monitored will move over time or will not permit fixed sensors, thus requiring a team of mobile sensors -- or robots -- to monitor the area collectively. In these situations, the robots must not only have mechanisms for determining how to track objects and how to fuse information from neighboring robots, but they must also have distributed control strategies for ensuring that the entire area of interest is continually covered to the greatest extent possible. This paper focuses on the distributed control issue by describing a proposed decentralized control mechanism that allows a team of robots to collectively track and monitor objects in an uncluttered area of interest. The approach is based upon an extension to the ALLIANCE behavior-based architecture that generalizes from the domain of loosely-coupled, independent applications to the domain of strongly cooperative applications, in which the action selection of a robot is dependent upon the actions selected by its teammates. We conclude the paper by describing our ongoing implementation of the proposed approach on a team of four mobile robots

  18. Distributed multi-robot sensing and tracking: a behavior-based approach

    Energy Technology Data Exchange (ETDEWEB)

    Parker, L.E.

    1995-12-31

    An important issue that arises in the automation of many large-scale surveillance and reconnaissance tasks is that of tracking the movements of (or maintaining passive contact with) objects navigating in a bounded area of interest. Oftentimes in these problems, the area to be monitored will move over time or will not permit fixed sensors, thus requiring a team of mobile sensors -- or robots -- to monitor the area collectively. In these situations, the robots must not only have mechanisms for determining how to track objects and how to fuse information from neighboring robots, but they must also have distributed control strategies for ensuring that the entire area of interest is continually covered to the greatest extent possible. This paper focuses on the distributed control issue by describing a proposed decentralized control mechanism that allows a team of robots to collectively track and monitor objects in an uncluttered area of interest. The approach is based upon an extension to the ALLIANCE behavior-based architecture that generalizes from the domain of loosely-coupled, independent applications to the domain of strongly cooperative applications, in which the action selection of a robot is dependent upon the actions selected by its teammates. We conclude the paper by describing our ongoing implementation of the proposed approach on a team of four mobile robots.

  19. ALLIANCE: An architecture for fault tolerant multi-robot cooperation

    Energy Technology Data Exchange (ETDEWEB)

    Parker, L.E.

    1995-02-01

    ALLIANCE is a software architecture that facilitates the fault tolerant cooperative control of teams of heterogeneous mobile robots performing missions composed of loosely coupled, largely independent subtasks. ALLIANCE allows teams of robots, each of which possesses a variety of high-level functions that it can perform during a mission, to individually select appropriate actions throughout the mission based on the requirements of the mission, the activities of other robots, the current environmental conditions, and the robot`s own internal states. ALLIANCE is a fully distributed, behavior-based architecture that incorporates the use of mathematically modeled motivations (such as impatience and acquiescence) within each robot to achieve adaptive action selection. Since cooperative robotic teams usually work in dynamic and unpredictable environments, this software architecture allows the robot team members to respond robustly, reliably, flexibly, and coherently to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. The feasibility of this architecture is demonstrated in an implementation on a team of mobile robots performing a laboratory version of hazardous waste cleanup.

  20. Testing Biological Hypotheses with Embodied Robots: Adaptations, Accidents, and By-Products in the Evolution of Vertebrates

    OpenAIRE

    Roberts, Sonia F.; Hirokawa, Jonathan; Rosenblum, Hannah G.; Sakhtah, Hassan; Gutierrez, Andres A.; Porter, Marianne E.; Long, John H.

    2014-01-01

    Evolutionary robotics allows biologists to test hypotheses about extinct animals. In our case, we modeled some of the first vertebrates, jawless fishes, in order to study the evolution of the trait after which vertebrates are named: vertebrae. We tested the hypothesis that vertebrae are an adaptation for enhanced feeding and fleeing performance. We created a population of autonomous embodied robots, Preyro, in which the number of vertebrae, N, were free to evolve. In addition, two other trait...

  1. Adaptive Control for Autonomous Navigation of Mobile Robots Considering Time Delay and Uncertainty

    Science.gov (United States)

    Armah, Stephen Kofi

    Autonomous control of mobile robots has attracted considerable attention of researchers in the areas of robotics and autonomous systems during the past decades. One of the goals in the field of mobile robotics is development of platforms that robustly operate in given, partially unknown, or unpredictable environments and offer desired services to humans. Autonomous mobile robots need to be equipped with effective, robust and/or adaptive, navigation control systems. In spite of enormous reported work on autonomous navigation control systems for mobile robots, achieving the goal above is still an open problem. Robustness and reliability of the controlled system can always be improved. The fundamental issues affecting the stability of the control systems include the undesired nonlinear effects introduced by actuator saturation, time delay in the controlled system, and uncertainty in the model. This research work develops robustly stabilizing control systems by investigating and addressing such nonlinear effects through analytical, simulations, and experiments. The control systems are designed to meet specified transient and steady-state specifications. The systems used for this research are ground (Dr Robot X80SV) and aerial (Parrot AR.Drone 2.0) mobile robots. Firstly, an effective autonomous navigation control system is developed for X80SV using logic control by combining 'go-to-goal', 'avoid-obstacle', and 'follow-wall' controllers. A MATLAB robot simulator is developed to implement this control algorithm and experiments are conducted in a typical office environment. The next stage of the research develops an autonomous position (x, y, and z) and attitude (roll, pitch, and yaw) controllers for a quadrotor, and PD-feedback control is used to achieve stabilization. The quadrotor's nonlinear dynamics and kinematics are implemented using MATLAB S-function to generate the state output. Secondly, the white-box and black-box approaches are used to obtain a linearized

  2. ALLIANCE: An architecture for fault tolerant, cooperative control of heterogeneous mobile robots

    Energy Technology Data Exchange (ETDEWEB)

    Parker, L.E.

    1995-02-01

    This research addresses the problem of achieving fault tolerant cooperation within small- to medium-sized teams of heterogeneous mobile robots. The author describes a novel behavior-based, fully distributed architecture, called ALLIANCE, that utilizes adaptive action selection to achieve fault tolerant cooperative control in robot missions involving loosely coupled, largely independent tasks. The robots in this architecture possess a variety of high-level functions that they can perform during a mission, and must at all times select an appropriate action based on the requirements of the mission, the activities of other robots, the current environmental conditions, and their own internal states. Since such cooperative teams often work in dynamic and unpredictable environments, the software architecture allows the team members to respond robustly and reliably to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. After presenting ALLIANCE, the author describes in detail experimental results of an implementation of this architecture on a team of physical mobile robots performing a cooperative box pushing demonstration. These experiments illustrate the ability of ALLIANCE to achieve adaptive, fault-tolerant cooperative control amidst dynamic changes in the capabilities of the robot team.

  3. Cerebellar-inspired adaptive control of a robot eye actuated by pneumatic artificial muscles.

    Science.gov (United States)

    Lenz, Alexander; Anderson, Sean R; Pipe, A G; Melhuish, Chris; Dean, Paul; Porrill, John

    2009-12-01

    In this paper, a model of cerebellar function is implemented and evaluated in the control of a robot eye actuated by pneumatic artificial muscles. The investigated control problem is stabilization of the visual image in response to disturbances. This is analogous to the vestibuloocular reflex (VOR) in humans. The cerebellar model is structurally based on the adaptive filter, and the learning rule is computationally analogous to least-mean squares, where parameter adaptation at the parallel fiber/Purkinje cell synapse is driven by the correlation of the sensory error signal (carried by the climbing fiber) and the motor command signal. Convergence of the algorithm is first analyzed in simulation on a model of the robot and then tested online in both one and two degrees of freedom. The results show that this model of neural function successfully works on a real-world problem, providing empirical evidence for validating: 1) the generic cerebellar learning algorithm; 2) the function of the cerebellum in the VOR; and 3) the signal transmission between functional neural components of the VOR.

  4. Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

    Science.gov (United States)

    Nurzaman, Surya G.

    2016-01-01

    Sensor morphology, the morphology of a sensing mechanism which plays a role of shaping the desired response from physical stimuli from surroundings to generate signals usable as sensory information, is one of the key common aspects of sensing processes. This paper presents a structured review of researches on bioinspired sensor morphology implemented in robotic systems, and discusses the fundamental design principles. Based on literature review, we propose two key arguments: first, owing to its synthetic nature, biologically inspired robotics approach is a unique and powerful methodology to understand the role of sensor morphology and how it can evolve and adapt to its task and environment. Second, a consideration of an integrative view of perception by looking into multidisciplinary and overarching mechanisms of sensor morphology adaptation across biology and engineering enables us to extract relevant design principles that are important to extend our understanding of the unfinished concepts in sensing and perception. PMID:27499843

  5. Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton.

    Science.gov (United States)

    Koller, Jeffrey R; Jacobs, Daniel A; Ferris, Daniel P; Remy, C David

    2015-11-04

    Robotic ankle exoskeletons can provide assistance to users and reduce metabolic power during walking. Our research group has investigated the use of proportional myoelectric control for controlling robotic ankle exoskeletons. Previously, these controllers have relied on a constant gain to map user's muscle activity to actuation control signals. A constant gain may act as a constraint on the user, so we designed a controller that dynamically adapts the gain to the user's myoelectric amplitude. We hypothesized that an adaptive gain proportional myoelectric controller would reduce metabolic energy expenditure compared to walking with the ankle exoskeleton unpowered because users could choose their preferred control gain. We tested eight healthy subjects walking with the adaptive gain proportional myoelectric controller with bilateral ankle exoskeletons. The adaptive gain was updated each stride such that on average the user's peak muscle activity was mapped to maximal power output of the exoskeleton. All subjects participated in three identical training sessions where they walked on a treadmill for 50 minutes (30 minutes of which the exoskeleton was powered) at 1.2 ms(-1). We calculated and analyzed metabolic energy consumption, muscle recruitment, inverse kinematics, inverse dynamics, and exoskeleton mechanics. Using our controller, subjects achieved a metabolic reduction similar to that seen in previous work in about a third of the training time. The resulting controller gain was lower than that seen in previous work (β=1.50±0.14 versus a constant β=2). The adapted gain allowed users more total ankle joint power than that of unassisted walking, increasing ankle power in exchange for a decrease in hip power. Our findings indicate that humans prefer to walk with greater ankle mechanical power output than their unassisted gait when provided with an ankle exoskeleton using an adaptive controller. This suggests that robotic assistance from an exoskeleton can allow

  6. Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

    Directory of Open Access Journals (Sweden)

    Chunmei Liu

    2016-01-01

    Full Text Available This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour.

  7. Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

    Science.gov (United States)

    2016-01-01

    This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165

  8. Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes.

    Science.gov (United States)

    Liu, Hengli; Luo, Jun; Wu, Peng; Xie, Shaorong; Li, Hengyu

    2015-01-01

    A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination.

  9. Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes

    Directory of Open Access Journals (Sweden)

    Hengli Liu

    2015-01-01

    Full Text Available A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination.

  10. Automated Kinematics Equations Generation and Constrained Motion Planning Resolution for Modular and Reconfigurable Robots

    Energy Technology Data Exchange (ETDEWEB)

    Pin, Francois G.; Love, Lonnie L.; Jung, David L.

    2004-03-29

    Contrary to the repetitive tasks performed by industrial robots, the tasks in most DOE missions such as environmental restoration or Decontamination and Decommissioning (D&D) can be characterized as ''batches-of-one'', in which robots must be capable of adapting to changes in constraints, tools, environment, criteria and configuration. No commercially available robot control code is suitable for use with such widely varying conditions. In this talk we present our development of a ''generic code'' to allow real time (at loop rate) robot behavior adaptation to changes in task objectives, tools, number and type of constraints, modes of controls or kinematics configuration. We present the analytical framework underlying our approach and detail the design of its two major modules for the automatic generation of the kinematics equations when the robot configuration or tools change and for the motion planning under time-varying constraints. Sample problems illustrating the capabilities of the developed system are presented.

  11. ALLIANCE: An architecture for fault tolerant multi-robot cooperation

    International Nuclear Information System (INIS)

    Parker, L.E.

    1995-02-01

    ALLIANCE is a software architecture that facilitates the fault tolerant cooperative control of teams of heterogeneous mobile robots performing missions composed of loosely coupled, largely independent subtasks. ALLIANCE allows teams of robots, each of which possesses a variety of high-level functions that it can perform during a mission, to individually select appropriate actions throughout the mission based on the requirements of the mission, the activities of other robots, the current environmental conditions, and the robot's own internal states. ALLIANCE is a fully distributed, behavior-based architecture that incorporates the use of mathematically modeled motivations (such as impatience and acquiescence) within each robot to achieve adaptive action selection. Since cooperative robotic teams usually work in dynamic and unpredictable environments, this software architecture allows the robot team members to respond robustly, reliably, flexibly, and coherently to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. The feasibility of this architecture is demonstrated in an implementation on a team of mobile robots performing a laboratory version of hazardous waste cleanup

  12. Adaptive and Energy Efficient Walking in a Hexapod Robot under Neuromechanical Control and Sensorimotor Learning

    DEFF Research Database (Denmark)

    Xiong, Xiaofeng; Wörgötter, Florentin; Manoonpong, Poramate

    2016-01-01

    The control of multilegged animal walking is a neuromechanical process, and to achieve this in an adaptive and energy efficient way is a difficult and challenging problem. This is due to the fact that this process needs in real time: 1) to coordinate very many degrees of freedom of jointed legs; 2......) to generate the proper leg stiffness (i.e., compliance); and 3) to determine joint angles that give rise to particular positions at the endpoints of the legs. To tackle this problem for a robotic application, here we present a neuromechanical controller coupled with sensorimotor learning. The controller...... energy efficient walking, compared to other small legged robots. In addition, this paper also shows that the tight combination of neural control with tunable muscle-like functions, guided by sensory feedback and coupled with sensorimotor learning, is a way forward to better understand and solve adaptive...

  13. Short-term locomotor adaptation to a robotic ankle exoskeleton does not alter soleus Hoffmann reflex amplitude.

    Science.gov (United States)

    Kao, Pei-Chun; Lewis, Cara L; Ferris, Daniel P

    2010-07-26

    To improve design of robotic lower limb exoskeletons for gait rehabilitation, it is critical to identify neural mechanisms that govern locomotor adaptation to robotic assistance. Previously, we demonstrated soleus muscle recruitment decreased by approximately 35% when walking with a pneumatically-powered ankle exoskeleton providing plantar flexor torque under soleus proportional myoelectric control. Since a substantial portion of soleus activation during walking results from the stretch reflex, increased reflex inhibition is one potential mechanism for reducing soleus recruitment when walking with exoskeleton assistance. This is clinically relevant because many neurologically impaired populations have hyperactive stretch reflexes and training to reduce the reflexes could lead to substantial improvements in their motor ability. The purpose of this study was to quantify soleus Hoffmann (H-) reflex responses during powered versus unpowered walking. We tested soleus H-reflex responses in neurologically intact subjects (n=8) that had trained walking with the soleus controlled robotic ankle exoskeleton. Soleus H-reflex was tested at the mid and late stance while subjects walked with the exoskeleton on the treadmill at 1.25 m/s, first without power (first unpowered), then with power (powered), and finally without power again (second unpowered). We also collected joint kinematics and electromyography. When the robotic plantar flexor torque was provided, subjects walked with lower soleus electromyographic (EMG) activation (27-48%) and had concomitant reductions in H-reflex amplitude (12-24%) compared to the first unpowered condition. The H-reflex amplitude in proportion to the background soleus EMG during powered walking was not significantly different from the two unpowered conditions. These findings suggest that the nervous system does not inhibit the soleus H-reflex in response to short-term adaption to exoskeleton assistance. Future studies should determine if the

  14. Adaptive behavior of children with visual impairment

    Directory of Open Access Journals (Sweden)

    Anđelković Marija

    2014-01-01

    Full Text Available Adaptive behavior includes a wide range of skills necessary for independent, safe and adequate performance of everyday activities. Practical, social and conceptual skills make the concept of adaptive behavior. The aim of this paper is to provide an insight into the existing studies of adaptive behavior in persons with visual impairment. The paper mainly focuses on the research on adaptive behavior in children with visual impairment. The results show that the acquisition of adaptive skills is mainly low or moderately low in children and youth with visual impairment. Children with visual impairment achieve the worst results in social skills and everyday life skills, while the most acquired are communication skills. Apart from the degree of visual impairment, difficulties in motor development also significantly influence the acquisition of practical and social skills of blind persons and persons with low vision.

  15. An Adaptive Web-Based Support to e-Education in Robotics and Automation

    Science.gov (United States)

    di Giamberardino, Paolo; Temperini, Marco

    The paper presents the hardware and software architecture of a remote laboratory, with robotics and automation applications, devised to support e-teaching and e-learning activities, at an undergraduate level in computer engineering. The hardware is composed by modular structures, based on the Lego Mindstorms components: they are reasonably sophisticated in terms of functions, pretty easy to use, and sufficiently affordable in terms of cost. Moreover, being the robots intrinsically modular, wrt the number and distribution of sensors and actuators, they are easily and quickly reconfigurable. A web application makes the laboratory and its robots available via internet. The software framework allows the teacher to define, for the course under her/his responsibility, a learning path made of different and differently complex exercises, graduated in terms of the "difficulty" they require to meet and of the "competence" that the solver is supposed to have shown. The learning path of exercises is adapted to the individual learner's progressively growing competence: at any moment, only a subset of the exercises is available (depending on how close their levels of competence and difficulty are to those of the exercises already solved by the learner).

  16. Efficient Active Sensing with Categorized Further Explorations for a Home Behavior-Monitoring Robot

    Directory of Open Access Journals (Sweden)

    Wenwei Yu

    2017-01-01

    Full Text Available Mobile robotics is a potential solution to home behavior monitoring for the elderly. For a mobile robot in the real world, there are several types of uncertainties for its perceptions, such as the ambiguity between a target object and the surrounding objects and occlusions by furniture. The problem could be more serious for a home behavior-monitoring system, which aims to accurately recognize the activity of a target person, in spite of these uncertainties. It detects irregularities and categorizes situations requiring further explorations, which strategically maximize the information needed for activity recognition while minimizing the costs. Two schemes of active sensing, based on two irregularity detections, namely, heuristic-based and template-matching-based irregularity detections, were implemented and examined for body contour-based activity recognition. Their time cost and accuracy in activity recognition were evaluated through experiments in both a controlled scenario and a home living scenario. Experiment results showed that the categorized further explorations guided the robot system to sense the target person actively. As a result, with the proposed approach, the robot system has achieved higher accuracy of activity recognition.

  17. Using Sun’s Java Real-Time System to Manage Behavior-Based Mobile Robot Controllers

    Directory of Open Access Journals (Sweden)

    Andrew McKenzie

    2011-01-01

    Full Text Available Implementing a robot controller that can effectively manage limited resources in a deterministic, real-time manner is challenging. Behavior-based architectures that decompose autonomy into levels of intelligence are popular due to their robustness but do not provide real-time features that enforce timing constraints or support determinism. We propose an architecture and approach for using the real-time features of the Real-Time Specification for Java (RTSJ in a behavior-based mobile robot controller to show that timing constraints affect performance. This is accomplished by extending a real-time aware architecture that explicitly enumerates timing requirements for each behavior. It is not enough to reduce latency. The usefulness of this approach is demonstrated via an implementation on Solaris 10 and the Sun Java Real-Time System (Java RTS. Experimental results are obtained using a K-team Koala robot performing path following with four composite behaviors. Experiments were conducted using several task period sets in three cases: real-time threads with the real-time garbage collector, real-time threads with the non- real-time garbage collector, and non-real-time threads with the non-real-time garbage collector. Results show that even if latency and determinism are improved, the timing of each individual behavior significantly affects task performance.

  18. Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation

    Directory of Open Access Journals (Sweden)

    Jesus A Garrido Alcazar

    2013-10-01

    Full Text Available Adaptable gain regulation is at the core of the forward controller operation performed by the cerebro-cerebellar loops and it allows the intensity of motor acts to be finely tuned in a predictive manner. In order to learn and store information about body-object dynamics and to generate an internal model of movement, the cerebellum is thought to employ long-term synaptic plasticity. LTD at the PF-PC synapse has classically been assumed to subserve this function (Marr, 1969. However, this plasticity alone cannot account for the broad dynamic ranges and time scales of cerebellar adaptation. We therefore tested the role of plasticity distributed over multiple synaptic sites (Gao et al., 2012; Hansel et al., 2001 by generating an analog cerebellar model embedded into a control loop connected to a robotic simulator. The robot used a three-joint arm and performed repetitive fast manipulations with different masses along an 8-shape trajectory. In accordance with biological evidence, the cerebellum model was endowed with both LTD and LTP at the PF-PC, MF-DCN and PC-DCN synapses. This resulted in a network scheme whose effectiveness was extended considerably compared to one including just PF-PC synaptic plasticity. Indeed, the system including distributed plasticity reliably self-adapted to manipulate different masses and to learn the arm-object dynamics over a time course that included fast learning and consolidation, along the lines of what has been observed in behavioral tests. In particular, PF-PC plasticity operated as a time correlator between the actual input state and the system error, while MF-DCN and PC-DCN plasticity played a key role in generating the gain controller. This model suggests that distributed synaptic plasticity allows generation of the complex learning properties of the cerebellum. The incorporation of further plasticity mechanisms and of spiking signal processing will allow this concept to be extended in a more realistic

  19. Development of Tremor Suppression Control System Using Adaptive Filter and Its Application to Meal-assist Robot

    Science.gov (United States)

    Yano, Ken'ichi; Ohara, Eiichi; Horihata, Satoshi; Aoki, Takaaki; Nishimoto, Yutaka

    A robot that supports independent living by assisting with eating and other activities which use the operator's own hand would be helpful for people suffering from tremors of the hand or any other body part. The proposed system using adaptive filter estimates tremor frequencies with a time-varying property and individual differences online. In this study, the estimated frequency is used to adjusting the tremor suppression filter which insulates the voluntary motion signal from the sensor signal containing tremor components. These system are integrated into the control system of the Meal-Assist Robot. As a result, the developed system makes it possible for the person with a tremor to manipulate the supporting robot without causing operability to deteriorate and without hazards due to improper operation.

  20. Adaptive Tracking and Obstacle Avoidance Control for Mobile Robots with Unknown Sliding

    Directory of Open Access Journals (Sweden)

    Mingyue Cui

    2012-11-01

    Full Text Available An adaptive control approach is proposed for trajectory tracking and obstacle avoidance for mobile robots with consideration given to unknown sliding. A kinematic model of mobile robots is established in this paper, in which both longitudinal and lateral sliding are considered and processed as three time-varying parameters. A sliding model observer is introduced to estimate the sliding parameters online. A stable tracking control law for this nonholonomic system is proposed to compensate the unknown sliding effect. From Lyapunov-stability analysis, it is proved, regardless of unknown sliding, that tracking errors of the controlled closed-loop system are asymptotically stable, the tracking errors converge to zero outside the obstacle detection region and obstacle avoidance is guaranteed inside the obstacle detection region. The efficiency and robustness of the proposed control system are verified by simulation results.

  1. Effects of different kinds of robot feedback

    DEFF Research Database (Denmark)

    Fischer, Kerstin; Lohan, K. S.; Nehaniv, C.

    2013-01-01

    , we investigate the impact of the robot's learning success on tutors' tutoring strategies. Our results show that only in the condition in which the robot's behavior is socially contingent, the human tutors adjust their behavior to the robot. In the developmentally equally plausible object......In this paper, we investigate to what extent tutors' behavior is influenced by different kinds of robot feedback. In particular, we study the effects of online robot feedback in which the robot responds either contingently to the tutor's social behavior or by tracking the objects presented. Also......-driven condition, in which the robot tracked the objects presented, tutors do not change their behavior significantly, even though in both conditions the robot develops from a prelinguistic stage to producing keywords. Socially contingent robot feedback has thus the potential to influence tutors' behavior over...

  2. Adaptation of a haptic robot in a 3T fMRI.

    Science.gov (United States)

    Snider, Joseph; Plank, Markus; May, Larry; Liu, Thomas T; Poizner, Howard

    2011-10-04

    Functional magnetic resonance imaging (fMRI) provides excellent functional brain imaging via the BOLD signal with advantages including non-ionizing radiation, millimeter spatial accuracy of anatomical and functional data, and nearly real-time analyses. Haptic robots provide precise measurement and control of position and force of a cursor in a reasonably confined space. Here we combine these two technologies to allow precision experiments involving motor control with haptic/tactile environment interaction such as reaching or grasping. The basic idea is to attach an 8 foot end effecter supported in the center to the robot allowing the subject to use the robot, but shielding it and keeping it out of the most extreme part of the magnetic field from the fMRI machine (Figure 1). The Phantom Premium 3.0, 6DoF, high-force robot (SensAble Technologies, Inc.) is an excellent choice for providing force-feedback in virtual reality experiments, but it is inherently non-MR safe, introduces significant noise to the sensitive fMRI equipment, and its electric motors may be affected by the fMRI's strongly varying magnetic field. We have constructed a table and shielding system that allows the robot to be safely introduced into the fMRI environment and limits both the degradation of the fMRI signal by the electrically noisy motors and the degradation of the electric motor performance by the strongly varying magnetic field of the fMRI. With the shield, the signal to noise ratio (SNR: mean signal/noise standard deviation) of the fMRI goes from a baseline of ~380 to ~330, and ~250 without the shielding. The remaining noise appears to be uncorrelated and does not add artifacts to the fMRI of a test sphere (Figure 2). The long, stiff handle allows placement of the robot out of range of the most strongly varying parts of the magnetic field so there is no significant effect of the fMRI on the robot. The effect of the handle on the robot's kinematics is minimal since it is lightweight (~2

  3. Behavior coordination of mobile robotics using supervisory control of fuzzy discrete event systems.

    Science.gov (United States)

    Jayasiri, Awantha; Mann, George K I; Gosine, Raymond G

    2011-10-01

    In order to incorporate the uncertainty and impreciseness present in real-world event-driven asynchronous systems, fuzzy discrete event systems (DESs) (FDESs) have been proposed as an extension to crisp DESs. In this paper, first, we propose an extension to the supervisory control theory of FDES by redefining fuzzy controllable and uncontrollable events. The proposed supervisor is capable of enabling feasible uncontrollable and controllable events with different possibilities. Then, the extended supervisory control framework of FDES is employed to model and control several navigational tasks of a mobile robot using the behavior-based approach. The robot has limited sensory capabilities, and the navigations have been performed in several unmodeled environments. The reactive and deliberative behaviors of the mobile robotic system are weighted through fuzzy uncontrollable and controllable events, respectively. By employing the proposed supervisory controller, a command-fusion-type behavior coordination is achieved. The observability of fuzzy events is incorporated to represent the sensory imprecision. As a systematic analysis of the system, a fuzzy-state-based controllability measure is introduced. The approach is implemented in both simulation and real time. A performance evaluation is performed to quantitatively estimate the validity of the proposed approach over its counterparts.

  4. Patient-Centeredness as Physician Behavioral Adaptability to Patient Preferences.

    Science.gov (United States)

    Carrard, Valérie; Schmid Mast, Marianne; Jaunin-Stalder, Nicole; Junod Perron, Noëlle; Sommer, Johanna

    2018-05-01

    A physician who communicates in a patient-centered way is a physician who adapts his or her communication style to what each patient needs. In order to do so, the physician has to (1) accurately assess each patient's states and traits (interpersonal accuracy) and (2) possess a behavioral repertoire to choose from in order to actually adapt his or her behavior to different patients (behavioral adaptability). Physician behavioral adaptability describes the change in verbal or nonverbal behavior a physician shows when interacting with patients who have different preferences in terms of how the physician should interact with them. We hypothesized that physician behavioral adaptability to their patients' preferences would lead to better patient outcomes and that physician interpersonal accuracy was positively related to behavioral adaptability. To test these hypotheses, we recruited 61 physicians who completed an interpersonal accuracy test before being videotaped during four consultations with different patients. The 244 participating patients indicated their preferences for their physician's interaction style prior to the consultation and filled in a consultation outcomes questionnaire directly after the consultation. We coded the physician's verbal and nonverbal behavior for each of the consultations and compared it to the patients' preferences to obtain a measure of physician behavioral adaptability. Results partially confirmed our hypotheses in that female physicians who adapted their nonverbal (but not their verbal) behavior had patients who reported more positive consultation outcomes. Moreover, the more female physicians were accurate interpersonally, the more they showed verbal and nonverbal behavioral adaptability. For male physicians, more interpersonal accuracy was linked to less nonverbal adaptability.

  5. A multitasking behavioral control system for the Robotic All-Terrain Lunar Exploration Rover (RATLER)

    Science.gov (United States)

    Klarer, Paul

    1993-01-01

    An approach for a robotic control system which implements so called 'behavioral' control within a realtime multitasking architecture is proposed. The proposed system would attempt to ameliorate some of the problems noted by some researchers when implementing subsumptive or behavioral control systems, particularly with regard to multiple processor systems and realtime operations. The architecture is designed to allow synchronous operations between various behavior modules by taking advantage of a realtime multitasking system's intertask communications channels, and by implementing each behavior module and each interconnection node as a stand-alone task. The potential advantages of this approach over those previously described in the field are discussed. An implementation of the architecture is planned for a prototype Robotic All Terrain Lunar Exploration Rover (RATLER) currently under development and is briefly described.

  6. Adaptive particle filter for localization problem in service robotics

    Directory of Open Access Journals (Sweden)

    Heilig Alexander

    2018-01-01

    Full Text Available In this paper we present a statistical approach to the likelihood computation and adaptive resampling algorithm for particle filters using low cost ultrasonic sensors in the context of service robotics. This increases the efficiency of the particle filter in the Monte Carlo Localization problem by means of preventing sample impoverishment and ensuring it converges towards the most likely particle and simultaneously keeping less likely ones by systematic resampling. Proposed algorithms were developed in the ROS framework, simulation was done in Gazebo environment. Experiments using a differential drive mobile platform with 4 ultrasonic sensors in the office environment show that our approach provides strong improvement over particle filters with fixed sample sizes.

  7. Self-Adaptive Correction of Heading Direction in Stair Climbing for Tracked Mobile Robots Using Visual Servoing Approach

    Science.gov (United States)

    Ji, Peng; Song, Aiguo; Song, Zimo; Liu, Yuqing; Jiang, Guohua; Zhao, Guopu

    2017-02-01

    In this paper, we describe a heading direction correction algorithm for a tracked mobile robot. To save hardware resources as far as possible, the mobile robot’s wrist camera is used as the only sensor, which is rotated to face stairs. An ensemble heading deviation detector is proposed to help the mobile robot correct its heading direction. To improve the generalization ability, a multi-scale Gabor filter is used to process the input image previously. Final deviation result is acquired by applying the majority vote strategy on all the classifiers’ results. The experimental results show that our detector is able to enable the mobile robot to correct its heading direction adaptively while it is climbing the stairs.

  8. Learning for intelligent mobile robots

    Science.gov (United States)

    Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

    2003-10-01

    Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A

  9. Spatiotemporal Aspects of Engagement during Dialogic Storytelling Child–Robot Interaction

    Directory of Open Access Journals (Sweden)

    Scott Heath

    2017-06-01

    Full Text Available The success of robotic agents in close proximity of humans depends on their capacity to engage in social interactions and maintain these interactions over periods of time that are suitable for learning. A critical requirement is the ability to modify the behavior of the robot contingently to the attentional and social cues signaled by the human. A benchmark challenge for an engaging social robot is that of storytelling. In this paper, we present an exploratory study to investigate dialogic storytelling—storytelling with contingent responses—using a child-friendly robot. The aim of the study was to develop an engaging storytelling robot and to develop metrics for evaluating engagement. Ten children listened to an illustrated story told by a social robot during a science fair. The responses of the robot were adapted during the interaction based on the children’s engagement and touches of the pictures displayed by the robot on a tablet embedded in its torso. During the interaction the robot responded contingently to the child, but only when the robot invited the child to interact. We describe the robot architecture used to implement dialogic storytelling and evaluate the quality of human–robot interaction based on temporal (patterns of touch, touch duration and spatial (motions in the space surrounding the robot metrics. We introduce a novel visualization that emphasizes the temporal dynamics of the interaction and analyze the motions of the children in the space surrounding the robot. The study demonstrates that the interaction through invited contingent responses succeeded in engaging children, although the robot missed some opportunities for contingent interaction and the children had to adapt to the task. We conclude that (i the consideration of both temporal and spatial attributes is fundamental for establishing metrics to estimate levels of engagement in real-time, (ii metrics for engagement are sensitive to both the group and

  10. Development of a Dung Beetle Robot and Investigation of Its Dung-Rolling Behavior

    Directory of Open Access Journals (Sweden)

    Jen-Wei Wang

    2018-04-01

    Full Text Available In this study, a bio-inspired dung beetle robot was developed that emulated the dung rolling motion of the dung beetle. Dung beetles, which can roll objects up to 1000 times their own body weight, are one of the strongest insect species in the world. While the locomotion of many insects, such as cockroaches, inchworms, and butterflies, has been studied widely, the locomotion of dung beetles has rarely been given attention. Here, we report on the development of a dung beetle robot made specifically to investigate dung-rolling behavior and to determine and understand the underlying mechanism. Two versions of the robot were built, and the leg trajectories were carefully designed based on kinematic analysis. Cylinder and ball rolling experiments were conducted, and the results showed that the dung beetle robot could successfully and reliably roll objects. This further suggests that the dung beetle robot, with its current morphology, is capable of reliably rolling dung without the need for complex control strategies.

  11. Children's Behavior toward and Understanding of Robotic and Living Dogs

    Science.gov (United States)

    Melson, Gail F.; Kahn, Peter H., Jr.; Beck, Alan; Friedman, Batya; Roberts, Trace; Garrett, Erik; Gill, Brian T.

    2009-01-01

    This study investigated children's reasoning about and behavioral interactions with a computationally sophisticated robotic dog (Sony's AIBO) compared to a live dog (an Australian Shepherd). Seventy-two children from three age groups (7-9 years, 10-12 years, and 13-15 years) participated in this study. Results showed that more children…

  12. A Formation Behavior for Large-Scale Micro-Robot Deployment

    Energy Technology Data Exchange (ETDEWEB)

    Dudenhoeffer, Donald Dean; Jones, Michael Paul

    2000-12-01

    Micro-robots will soon be available for deployment by the thousands. Consequently, controlling and coordinating a force this large to accomplish a prescribed task is of great interest. This paper describes a flexible architecture for modeling thousands of autonomous agents simultaneously. The agents’ behavior is based on a subsumption architecture in which individual behaviors are prioritized with respect to all others. The primary behavior explored in this work is a group formation behavior based on social potential fields (Reif and Wang 1999). This paper extends the social potential field model by introducing a neutral zone within which other behaviors may exhibit themselves. Previous work with social potential fields has been restricted to models of “perfect” autonomous agents. The paper evaluates the effect of social potential fields in the presence of agent death (failure) and imperfect sensory input.

  13. Collective Behaviors of Mobile Robots Beyond the Nearest Neighbor Rules With Switching Topology.

    Science.gov (United States)

    Ning, Boda; Han, Qing-Long; Zuo, Zongyu; Jin, Jiong; Zheng, Jinchuan

    2018-05-01

    This paper is concerned with the collective behaviors of robots beyond the nearest neighbor rules, i.e., dispersion and flocking, when robots interact with others by applying an acute angle test (AAT)-based interaction rule. Different from a conventional nearest neighbor rule or its variations, the AAT-based interaction rule allows interactions with some far-neighbors and excludes unnecessary nearest neighbors. The resulting dispersion and flocking hold the advantages of scalability, connectivity, robustness, and effective area coverage. For the dispersion, a spring-like controller is proposed to achieve collision-free coordination. With switching topology, a new fixed-time consensus-based energy function is developed to guarantee the system stability. An upper bound of settling time for energy consensus is obtained, and a uniform time interval is accordingly set so that energy distribution is conducted in a fair manner. For the flocking, based on a class of generalized potential functions taking nonsmooth switching into account, a new controller is proposed to ensure that the same velocity for all robots is eventually reached. A co-optimizing problem is further investigated to accomplish additional tasks, such as enhancing communication performance, while maintaining the collective behaviors of mobile robots. Simulation results are presented to show the effectiveness of the theoretical results.

  14. Learning motor skills from algorithms to robot experiments

    CERN Document Server

    Kober, Jens

    2014-01-01

    This book presents the state of the art in reinforcement learning applied to robotics both in terms of novel algorithms and applications. It discusses recent approaches that allow robots to learn motor skills and presents tasks that need to take into account the dynamic behavior of the robot and its environment, where a kinematic movement plan is not sufficient. The book illustrates a method that learns to generalize parameterized motor plans which is obtained by imitation or reinforcement learning, by adapting a small set of global parameters, and appropriate kernel-based reinforcement learning algorithms. The presented applications explore highly dynamic tasks and exhibit a very efficient learning process. All proposed approaches have been extensively validated with benchmarks tasks, in simulation, and on real robots. These tasks correspond to sports and games but the presented techniques are also applicable to more mundane household tasks. The book is based on the first author’s doctoral thesis, which wo...

  15. Robots As Intentional Agents: Using Neuroscientific Methods to Make Robots Appear More Social.

    Science.gov (United States)

    Wiese, Eva; Metta, Giorgio; Wykowska, Agnieszka

    2017-01-01

    Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to interact with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user's needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots were able to adequately demonstrate these skills, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye-tracking, electroencephalography, or functional near-infrared spectroscopy embedded in interactive human-robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive processes and mechanisms involved in human-human interactions, and highlight the importance of perceiving others as intentional agents to activate these social brain areas. We then discuss how attribution of intentionality can positively affect human-robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human-robot tasks. Lastly, we describe circumstances under which

  16. Robots As Intentional Agents: Using Neuroscientific Methods to Make Robots Appear More Social

    Science.gov (United States)

    Wiese, Eva; Metta, Giorgio; Wykowska, Agnieszka

    2017-01-01

    Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to interact with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user’s needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots were able to adequately demonstrate these skills, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye-tracking, electroencephalography, or functional near-infrared spectroscopy embedded in interactive human–robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive processes and mechanisms involved in human–human interactions, and highlight the importance of perceiving others as intentional agents to activate these social brain areas. We then discuss how attribution of intentionality can positively affect human–robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human–robot tasks. Lastly, we describe circumstances under

  17. Robots As Intentional Agents: Using Neuroscientific Methods to Make Robots Appear More Social

    Directory of Open Access Journals (Sweden)

    Eva Wiese

    2017-10-01

    Full Text Available Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to interact with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user’s needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots were able to adequately demonstrate these skills, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye-tracking, electroencephalography, or functional near-infrared spectroscopy embedded in interactive human–robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive processes and mechanisms involved in human–human interactions, and highlight the importance of perceiving others as intentional agents to activate these social brain areas. We then discuss how attribution of intentionality can positively affect human–robot interaction by (a fostering feelings of social connection, empathy and prosociality, and by (b enhancing performance on joint human–robot tasks. Lastly, we describe

  18. Soft-Material Robotics

    OpenAIRE

    Wang, L; Nurzaman, SG; Iida, Fumiya

    2017-01-01

    There has been a boost of research activities in robotics using soft materials in the past ten years. It is expected that the use and control of soft materials can help realize robotic systems that are safer, cheaper, and more adaptable than the level that the conventional rigid-material robots can achieve. Contrary to a number of existing review and position papers on soft-material robotics, which mostly present case studies and/or discuss trends and challenges, the review focuses on the fun...

  19. A cognitive robotics system: the symbolic and sub-symbolic robotic intelligence control system (SS-RICS)

    Science.gov (United States)

    Kelley, Troy D.; Avery, Eric

    2010-04-01

    This paper will detail the progress on the development of the Symbolic and Subsymbolic Robotics Intelligence Control System (SS-RICS). The system is a goal oriented production system, based loosely on the cognitive architecture, the Adaptive Control of Thought-Rational (ACT-R) some additions and changes. We have found that in order to simulate complex cognition on a robot, many aspects of cognition (long term memory (LTM), perception) needed to be in place before any generalized intelligent behavior can be produced. In working with ACT-R, we found that it was a good instantiation of working memory, but that we needed to add other aspects of cognition including LTM and perception to have a complete cognitive system. Our progress to date will be noted and the challenges that remain will be addressed.

  20. Put Your Robot In, Put Your Robot Out: Sequencing through Programming Robots in Early Childhood

    Science.gov (United States)

    Kazakoff, Elizabeth R.; Bers, Marina Umaschi

    2014-01-01

    This article examines the impact of programming robots on sequencing ability in early childhood. Thirty-four children (ages 4.5-6.5 years) participated in computer programming activities with a developmentally appropriate tool, CHERP, specifically designed to program a robot's behaviors. The children learned to build and program robots over three…

  1. Dynamic Learning from Adaptive Neural Control of Uncertain Robots with Guaranteed Full-State Tracking Precision

    Directory of Open Access Journals (Sweden)

    Min Wang

    2017-01-01

    Full Text Available A dynamic learning method is developed for an uncertain n-link robot with unknown system dynamics, achieving predefined performance attributes on the link angular position and velocity tracking errors. For a known nonsingular initial robotic condition, performance functions and unconstrained transformation errors are employed to prevent the violation of the full-state tracking error constraints. By combining two independent Lyapunov functions and radial basis function (RBF neural network (NN approximator, a novel and simple adaptive neural control scheme is proposed for the dynamics of the unconstrained transformation errors, which guarantees uniformly ultimate boundedness of all the signals in the closed-loop system. In the steady-state control process, RBF NNs are verified to satisfy the partial persistent excitation (PE condition. Subsequently, an appropriate state transformation is adopted to achieve the accurate convergence of neural weight estimates. The corresponding experienced knowledge on unknown robotic dynamics is stored in NNs with constant neural weight values. Using the stored knowledge, a static neural learning controller is developed to improve the full-state tracking performance. A comparative simulation study on a 2-link robot illustrates the effectiveness of the proposed scheme.

  2. Adaptive neural control for dual-arm coordination of humanoid robot with unknown nonlinearities in output mechanism.

    Science.gov (United States)

    Liu, Zhi; Chen, Ci; Zhang, Yun; Chen, C L P

    2015-03-01

    To achieve an excellent dual-arm coordination of the humanoid robot, it is essential to deal with the nonlinearities existing in the system dynamics. The literatures so far on the humanoid robot control have a common assumption that the problem of output hysteresis could be ignored. However, in the practical applications, the output hysteresis is widely spread; and its existing limits the motion/force performances of the robotic system. In this paper, an adaptive neural control scheme, which takes the unknown output hysteresis and computational efficiency into account, is presented and investigated. In the controller design, the prior knowledge of system dynamics is assumed to be unknown. The motion error is guaranteed to converge to a small neighborhood of the origin by Lyapunov's stability theory. Simultaneously, the internal force is kept bounded and its error can be made arbitrarily small.

  3. Architecture for robot intelligence

    Science.gov (United States)

    Peters, II, Richard Alan (Inventor)

    2004-01-01

    An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

  4. Adaptive Behavior of Children and Adolescents with Visual Impairments

    Science.gov (United States)

    Papadopoulos, Konstantinos; Metsiou, Katerina; Agaliotis, Ioannis

    2011-01-01

    The present study explored the total adaptive behavior of children and adolescents with visual impairments, as well as their adaptive behavior in each of the domains of Communication, Daily Living Skills, and Socialization. Moreover, the predictors of the performance and developmental delay in adaptive behavior were investigated. Instrumentation…

  5. Head Orientation Behavior of Users and Durations in Playful Open-Ended Interactions with an Android Robot

    DEFF Research Database (Denmark)

    Vlachos, Evgenios; Jochum, Elizabeth Ann; Schärfe, Henrik

    2016-01-01

    This paper presents the results of a field-experiment focused on the head orientation behavior of users in short-term dyadic interactions with an android (male) robot in a playful context, as well as on the duration of the interactions. The robotic trials took place in an art exhibition where...... subjects. The findings suggest that androids have the ability to maintain the focus of attention during short-term in-teractions within a playful context. This study provides an insight on how users communicate with an android robot, and on how to design meaningful human robot social interaction for real...

  6. Beyond R2D2 - The design of nonverbal interaction behavior optimized for robot-specific morphologies

    NARCIS (Netherlands)

    Karreman, Daphne Eleonora

    2016-01-01

    It is likely that in the near future we will meet more and more robots that will perform tasks in social environments, such as shopping malls, airports or museums. However, design guidelines that inform the design of effective nonverbal behavior for robots are scarce. This is surprising since the

  7. A low-cost, computer-controlled robotic flower system for behavioral experiments.

    Science.gov (United States)

    Kuusela, Erno; Lämsä, Juho

    2016-04-01

    Human observations during behavioral studies are expensive, time-consuming, and error prone. For this reason, automatization of experiments is highly desirable, as it reduces the risk of human errors and workload. The robotic system we developed is simple and cheap to build and handles feeding and data collection automatically. The system was built using mostly off-the-shelf components and has a novel feeding mechanism that uses servos to perform refill operations. We used the robotic system in two separate behavioral studies with bumblebees (Bombus terrestris): The system was used both for training of the bees and for the experimental data collection. The robotic system was reliable, with no flight in our studies failing due to a technical malfunction. The data recorded were easy to apply for further analysis. The software and the hardware design are open source. The development of cheap open-source prototyping platforms during the recent years has opened up many possibilities in designing of experiments. Automatization not only reduces workload, but also potentially allows experimental designs never done before, such as dynamic experiments, where the system responds to, for example, learning of the animal. We present a complete system with hardware and software, and it can be used as such in various experiments requiring feeders and collection of visitation data. Use of the system is not limited to any particular experimental setup or even species.

  8. Robot Futures

    DEFF Research Database (Denmark)

    Christoffersen, Anja; Grindsted Nielsen, Sally; Jochum, Elizabeth Ann

    Robots are increasingly used in health care settings, e.g., as homecare assistants and personal companions. One challenge for personal robots in the home is acceptance. We describe an innovative approach to influencing the acceptance of care robots using theatrical performance. Live performance...... is a useful testbed for developing and evaluating what makes robots expressive; it is also a useful platform for designing robot behaviors and dialogue that result in believable characters. Therefore theatre is a valuable testbed for studying human-robot interaction (HRI). We investigate how audiences...... perceive social robots interacting with humans in a future care scenario through a scripted performance. We discuss our methods and initial findings, and outline future work....

  9. Executive Function and Adaptive Behavior in Muenke Syndrome.

    Science.gov (United States)

    Yarnell, Colin M P; Addissie, Yonit A; Hadley, Donald W; Guillen Sacoto, Maria J; Agochukwu, Nneamaka B; Hart, Rachel A; Wiggs, Edythe A; Platte, Petra; Paelecke, Yvonne; Collmann, Hartmut; Schweitzer, Tilmann; Kruszka, Paul; Muenke, Maximilian

    2015-08-01

    To investigate executive function and adaptive behavior in individuals with Muenke syndrome using validated instruments with a normative population and unaffected siblings as controls. Participants in this cross-sectional study included individuals with Muenke syndrome (P250R mutation in FGFR3) and their mutation-negative siblings. Participants completed validated assessments of executive functioning (Behavior Rating Inventory of Executive Function [BRIEF]) and adaptive behavior skills (Adaptive Behavior Assessment System, Second Edition [ABAS-II]). Forty-four with a positive FGFR3 mutation, median age 9 years, range 7 months to 52 years were enrolled. In addition, 10 unaffected siblings served as controls (5 males, 5 females; median age, 13 years; range, 3-18 years). For the General Executive Composite scale of the BRIEF, 32.1% of the cohort had scores greater than +1.5 SD, signifying potential clinical significance. For the General Adaptive Composite of the ABAS-II, 28.2% of affected individuals scored in the 3rd-8th percentile of the normative population, and 56.4% were below the average category (General Executive Composite and the ABAS-II General Adaptive Composite. Individuals with Muenke syndrome are at an increased risk for developing adaptive and executive function behavioral changes compared with a normative population and unaffected siblings. Published by Elsevier Inc.

  10. Temporal Memory Reinforcement Learning for the Autonomous Micro-mobile Robot Based-behavior

    Institute of Scientific and Technical Information of China (English)

    Yang Yujun(杨玉君); Cheng Junshi; Chen Jiapin; Li Xiaohai

    2004-01-01

    This paper presents temporal memory reinforcement learning for the autonomous micro-mobile robot based-behavior. Human being has a memory oblivion process, i.e. the earlier to memorize, the earlier to forget, only the repeated thing can be remembered firmly. Enlightening forms this, and the robot need not memorize all the past states, at the same time economizes the EMS memory space, which is not enough in the MPU of our AMRobot. The proposed algorithm is an extension of the Q-learning, which is an incremental reinforcement learning method. The results of simulation have shown that the algorithm is valid.

  11. Analyzing the effects of human-aware motion planning on close-proximity human-robot collaboration.

    Science.gov (United States)

    Lasota, Przemyslaw A; Shah, Julie A

    2015-02-01

    The objective of this work was to examine human response to motion-level robot adaptation to determine its effect on team fluency, human satisfaction, and perceived safety and comfort. The evaluation of human response to adaptive robotic assistants has been limited, particularly in the realm of motion-level adaptation. The lack of true human-in-the-loop evaluation has made it impossible to determine whether such adaptation would lead to efficient and satisfying human-robot interaction. We conducted an experiment in which participants worked with a robot to perform a collaborative task. Participants worked with an adaptive robot incorporating human-aware motion planning and with a baseline robot using shortest-path motions. Team fluency was evaluated through a set of quantitative metrics, and human satisfaction and perceived safety and comfort were evaluated through questionnaires. When working with the adaptive robot, participants completed the task 5.57% faster, with 19.9% more concurrent motion, 2.96% less human idle time, 17.3% less robot idle time, and a 15.1% greater separation distance. Questionnaire responses indicated that participants felt safer and more comfortable when working with an adaptive robot and were more satisfied with it as a teammate than with the standard robot. People respond well to motion-level robot adaptation, and significant benefits can be achieved from its use in terms of both human-robot team fluency and human worker satisfaction. Our conclusion supports the development of technologies that could be used to implement human-aware motion planning in collaborative robots and the use of this technique for close-proximity human-robot collaboration.

  12. Programming Robots with Associative Memories

    Energy Technology Data Exchange (ETDEWEB)

    Touzet, C

    1999-07-10

    Today, there are several drawbacks that impede the necessary and much needed use of robot learning techniques in real applications. First, the time needed to achieve the synthesis of any behavior is prohibitive. Second, the robot behavior during the learning phase is "by definition" bad, it may even be dangerous. Third, except within the lazy learning approach, a new behavior implies a new learning phase. We propose in this paper to use self-organizing maps to encode the non explicit model of the robot-world interaction sampled by the lazy memory, and then generate a robot behavior by means of situations to be achieved, i.e., points on the self-organizing maps. Any behavior can instantaneously be synthesized by the definition of a goal situation. Its performance will be minimal (not evidently bad) and will improve by the mere repetition of the behavior.

  13. Programming Robots with Associative Memories

    International Nuclear Information System (INIS)

    Touzet, C.

    1999-01-01

    Today, there are several drawbacks that impede the necessary and much needed use of robot learning techniques in real applications. First, the time needed to achieve the synthesis of any behavior is prohibitive. Second, the robot behavior during the learning phase is by definition bad, it may even be dangerous. Third, except within the lazy learning approach, a new behavior implies a new learning phase. We propose in this paper to use self-organizing maps to encode the non explicit model of the robot-world interaction sampled by the lazy memory, and then generate a robot behavior by means of situations to be achieved, i.e., points on the self-organizing maps. Any behavior can instantaneously be synthesized by the definition of a goal situation. Its performance will be minimal (not evidently bad) and will improve by the mere repetition of the behavior

  14. Dynamic Modelling and Adaptive Traction Control for Mobile Robots

    Directory of Open Access Journals (Sweden)

    A. Albagul

    2004-09-01

    Full Text Available Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as ‘Low’ level controller. The second level is developed to take care of path planning and trajectory generation.

  15. Flow Behavior Around a Fast-Starting Robotic Fish

    Science.gov (United States)

    Ma, Ganzhong; Currier, Todd; Modarres-Sadeghi, Yahya

    2017-11-01

    A robotic fish is used to study the flow behavior around the body of a fast-starting fish as it experiences a fast-start. The robotic fish is designed and built emulating a Northern Pike, Esox Lucius, which can accelerate at up to 245 m/s2. In previous studies, we had focused on the flow around the tail during the fast-start, by using a tail which acted flexibly in the preparatory stage and rigidly in the propulsive stage. We have extended that study by including the fish body in the experimental setup, where the body can bend into a C-shape, so that the influence of the body motion on the resulting flow around the structure can be understood as well. In the tests, the fish can rotate about a vertical axis, where a multi-axis force sensor measures flow forces acting on the body. Synchronized with the force measurement, flow visualizations using bubble image velocimetry are conducted, and the observed shed vortices are related to the peak forces observed during the maneuver.

  16. Adding memory processing behaviors to the fuzzy behaviorist-based navigation of mobile robots

    Energy Technology Data Exchange (ETDEWEB)

    Pin, F.G.; Bender, S.R.

    1996-05-01

    Most fuzzy logic-based reasoning schemes developed for robot control are fully reactive, i.e., the reasoning modules consist of fuzzy rule bases that represent direct mappings from the stimuli provided by the perception systems to the responses implemented by the motion controllers. Due to their totally reactive nature, such reasoning systems can encounter problems such as infinite loops and limit cycles. In this paper, we proposed an approach to remedy these problems by adding a memory and memory-related behaviors to basic reactive systems. Three major types of memory behaviors are addressed: memory creation, memory management, and memory utilization. These are first presented, and examples of their implementation for the recognition of limit cycles during the navigation of an autonomous robot in a priori unknown environments are then discussed.

  17. An Ultralightweight and Living Legged Robot.

    Science.gov (United States)

    Vo Doan, Tat Thang; Tan, Melvin Y W; Bui, Xuan Hien; Sato, Hirotaka

    2018-02-01

    In this study, we describe the most ultralightweight living legged robot to date that makes it a strong candidate for a search and rescue mission. The robot is a living beetle with a wireless electronic backpack stimulator mounted on its thorax. Inheriting from the living insect, the robot employs a compliant body made of soft actuators, rigid exoskeletons, and flexure hinges. Such structure would allow the robot to easily adapt to any complex terrain due to the benefit of soft interface, self-balance, and self-adaptation of the insect without any complex controller. The antenna stimulation enables the robot to perform not only left/right turning but also backward walking and even cessation of walking. We were also able to grade the turning and backward walking speeds by changing the stimulation frequency. The power required to drive the robot is low as the power consumption of the antenna stimulation is in the order of hundreds of microwatts. In contrast to the traditional legged robots, this robot is of low cost, easy to construct, simple to control, and has ultralow power consumption.

  18. Analyzing the Effects of Human-Aware Motion Planning on Close-Proximity Human–Robot Collaboration

    Science.gov (United States)

    Shah, Julie A.

    2015-01-01

    Objective: The objective of this work was to examine human response to motion-level robot adaptation to determine its effect on team fluency, human satisfaction, and perceived safety and comfort. Background: The evaluation of human response to adaptive robotic assistants has been limited, particularly in the realm of motion-level adaptation. The lack of true human-in-the-loop evaluation has made it impossible to determine whether such adaptation would lead to efficient and satisfying human–robot interaction. Method: We conducted an experiment in which participants worked with a robot to perform a collaborative task. Participants worked with an adaptive robot incorporating human-aware motion planning and with a baseline robot using shortest-path motions. Team fluency was evaluated through a set of quantitative metrics, and human satisfaction and perceived safety and comfort were evaluated through questionnaires. Results: When working with the adaptive robot, participants completed the task 5.57% faster, with 19.9% more concurrent motion, 2.96% less human idle time, 17.3% less robot idle time, and a 15.1% greater separation distance. Questionnaire responses indicated that participants felt safer and more comfortable when working with an adaptive robot and were more satisfied with it as a teammate than with the standard robot. Conclusion: People respond well to motion-level robot adaptation, and significant benefits can be achieved from its use in terms of both human–robot team fluency and human worker satisfaction. Application: Our conclusion supports the development of technologies that could be used to implement human-aware motion planning in collaborative robots and the use of this technique for close-proximity human–robot collaboration. PMID:25790568

  19. Modular robotic applications in nuclear power plant maintenance

    International Nuclear Information System (INIS)

    Glass, S.W.; Ranson, C.C.; Reinholtz, C.F.; Calkins, J.M.

    1996-01-01

    General-purpose factory automation robots have experienced limited use in nuclear maintenance and hazardous-environment work spaces due to demanding requirements on size, weight, mobility and adaptability. Robotic systems in nuclear power plants are frequently custom designed to meet specific space and performance requirements. Examples of these custom configurations include Framatome Technologies COBRA trademark Steam Generator Manipulator and URSULA trademark Reactor Vessel Inspection Manipulator. The use of custom robots in nuclear plants has been limited because of the lead time and expense associated with custom design. Developments in modular robotics and advanced robot control software coupled with more powerful low-cost computers, however, are helping to reduce the cost and schedule for deploying custom robots. A modular robotic system allows custom robot configurations to be implemented using standard (modular) joints and adaptable controllers. This paper discusses Framatome Technologies (FTI) current and planned developments in the area of modular robot system design

  20. Modeling Leadership Styles in Human-Robot Team Dynamics

    Science.gov (United States)

    Cruz, Gerardo E.

    2005-01-01

    The recent proliferation of robotic systems in our society has placed questions regarding interaction between humans and intelligent machines at the forefront of robotics research. In response, our research attempts to understand the context in which particular types of interaction optimize efficiency in tasks undertaken by human-robot teams. It is our conjecture that applying previous research results regarding leadership paradigms in human organizations will lead us to a greater understanding of the human-robot interaction space. In doing so, we adapt four leadership styles prevalent in human organizations to human-robot teams. By noting which leadership style is more appropriately suited to what situation, as given by previous research, a mapping is created between the adapted leadership styles and human-robot interaction scenarios-a mapping which will presumably maximize efficiency in task completion for a human-robot team. In this research we test this mapping with two adapted leadership styles: directive and transactional. For testing, we have taken a virtual 3D interface and integrated it with a genetic algorithm for use in &le-operation of a physical robot. By developing team efficiency metrics, we can determine whether this mapping indeed prescribes interaction styles that will maximize efficiency in the teleoperation of a robot.

  1. Behaviour based Mobile Robot Navigation Technique using AI System: Experimental Investigation on Active Media Pioneer Robot

    Directory of Open Access Journals (Sweden)

    S. Parasuraman, V.Ganapathy

    2012-10-01

    Full Text Available A key issue in the research of an autonomous robot is the design and development of the navigation technique that enables the robot to navigate in a real world environment. In this research, the issues investigated and methodologies established include (a Designing of the individual behavior and behavior rule selection using Alpha level fuzzy logic system  (b Designing of the controller, which maps the sensors input to the motor output through model based Fuzzy Logic Inference System and (c Formulation of the decision-making process by using Alpha-level fuzzy logic system. The proposed method is applied to Active Media Pioneer Robot and the results are discussed and compared with most accepted methods. This approach provides a formal methodology for representing and implementing the human expert heuristic knowledge and perception-based action in mobile robot navigation. In this approach, the operational strategies of the human expert driver are transferred via fuzzy logic to the robot navigation in the form of a set of simple conditional statements composed of linguistic variables.Keywards: Mobile robot, behavior based control, fuzzy logic, alpha level fuzzy logic, obstacle avoidance behavior and goal seek behavior

  2. Distributed Consensus-Based Robust Adaptive Formation Control for Nonholonomic Mobile Robots with Partial Known Dynamics

    Directory of Open Access Journals (Sweden)

    Zhaoxia Peng

    2014-01-01

    Full Text Available This paper investigates the distributed consensus-based robust adaptive formation control for nonholonomic mobile robots with partially known dynamics. Firstly, multirobot formation control problem has been converted into a state consensus problem. Secondly, the practical control strategies, which incorporate the distributed kinematic controllers and the robust adaptive torque controllers, are designed for solving the formation control problem. Thirdly, the specified reference trajectory for the geometric centroid of the formation is assumed as the trajectory of a virtual leader, whose information is available to only a subset of the followers. Finally, numerical results are provided to illustrate the effectiveness of the proposed control approaches.

  3. Context recognition and situation assessment in autonomous mobile robots

    Science.gov (United States)

    Yavnai, Arie

    1993-05-01

    The capability to recognize the operating context and to assess the situation in real-time is needed, if a high functionality autonomous mobile robot has to react properly and effectively to continuously changing situations and events, either external or internal, while the robot is performing its assigned tasks. A new approach and architecture for context recognition and situation assessment module (CORSA) is presented in this paper. CORSA is a multi-level information processing module which consists of adaptive decision and classification algorithms. It performs dynamic mapping from the data space to the context space, and dynamically decides on the context class. Learning mechanism is employed to update the decision variables so as to minimize the probability of misclassification. CORSA is embedded within the Mission Manager module of the intelligent autonomous hyper-controller (IAHC) of the mobile robot. The information regarding operating context, events and situation is then communicated to other modules of the IAHC where it is used to: (a) select the appropriate action strategy; (b) support the processes to arbitration and conflict resolution between reflexive behaviors and reasoning-driven behaviors; (c) predict future events and situations; and (d) determine criteria and priorities for planning, replanning, and decision making.

  4. Development and Standardization of the Diagnostic Adaptive Behavior Scale: Application of Item Response Theory to the Assessment of Adaptive Behavior

    Science.gov (United States)

    Tassé, Marc J.; Schalock, Robert L.; Thissen, David; Balboni, Giulia; Bersani, Henry, Jr.; Borthwick-Duffy, Sharon A.; Spreat, Scott; Widaman, Keith F.; Zhang, Dalun; Navas, Patricia

    2016-01-01

    The Diagnostic Adaptive Behavior Scale (DABS) was developed using item response theory (IRT) methods and was constructed to provide the most precise and valid adaptive behavior information at or near the cutoff point of making a decision regarding a diagnosis of intellectual disability. The DABS initial item pool consisted of 260 items. Using IRT…

  5. Evolving and Controlling Perimeter, Rendezvous, and Foraging Behaviors in a Computation-Free Robot Swarm

    Science.gov (United States)

    2016-04-01

    in extreme environments. Categories and Subject Descriptors I.2.11 [ Artificial Intelligence ]: Distributed Artificial In- telligence—multiagent systems...coherence and coordination; I.2.9 [ Artificial Intelligence ]: Robotics— intelligent vehi- cles Keywords swarm robotics, evolutionary algorithms...collective behaviors. Rubenstein et al. [12] studied how to collectively transport items using a simple control signals and behaviors. Others have looked

  6. Leadership Behaviors of Management for Complex Adaptive Systems

    Science.gov (United States)

    2010-04-01

    Leadership Behaviors of Management for Complex Adaptive Systems Systems and Software Technology Conference April 2010 Dr. Suzette S. Johnson...2010 2. REPORT TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Leadership Behaviors of Management for Complex Adaptive...as they evolve – Control is dispersed and decentralized – Simple rules and governance used to direct behavior • Complexity Leadership Theory – Built on

  7. Endogenous Nuclear RNAi Mediates Behavioral Adaptation to Odor

    DEFF Research Database (Denmark)

    Juang, Bi-Tzen; Gu, Chen; Starnes, Linda

    2013-01-01

    , an in vitro substrate of the EGL-4 kinase that promotes adaption, is necessary and sufficient for behavioral adaptation. Thus, environmental stimulation amplifies an endo-siRNA negative feedback loop to dynamically repress cognate gene expression and shape behavior. This class of siRNA may act broadly...

  8. Effectiveness of social behaviors for autonomous wheelchair robot to support elderly people in Japan.

    Directory of Open Access Journals (Sweden)

    Masahiro Shiomi

    Full Text Available We developed a wheelchair robot to support the movement of elderly people and specifically implemented two functions to enhance their intention to use it: speaking behavior to convey place/location related information and speed adjustment based on individual preferences. Our study examines how the evaluations of our wheelchair robot differ when compared with human caregivers and a conventional autonomous wheelchair without the two proposed functions in a moving support context. 28 senior citizens participated in the experiment to evaluate three different conditions. Our measurements consisted of questionnaire items and the coding of free-style interview results. Our experimental results revealed that elderly people evaluated our wheelchair robot higher than the wheelchair without the two functions and the human caregivers for some items.

  9. Longitudinal Profiles of Adaptive Behavior in Fragile X Syndrome

    Science.gov (United States)

    Quintin, Eve-Marie; Jo, Booil; Lightbody, Amy A.; Hazlett, Heather Cody; Piven, Joseph; Hall, Scott S.; Reiss, Allan L.

    2014-01-01

    OBJECTIVE: To examine longitudinally the adaptive behavior patterns in fragile X syndrome. METHOD: Caregivers of 275 children and adolescents with fragile X syndrome and 225 typically developing children and adolescents (2–18 years) were interviewed with the Vineland Adaptive Behavior Scales every 2 to 4 years as part of a prospective longitudinal study. RESULTS: Standard scores of adaptive behavior in people with fragile X syndrome are marked by a significant decline over time in all domains for males and in communication for females. Socialization skills are a relative strength as compared with the other domains for males with fragile X syndrome. Females with fragile X syndrome did not show a discernible pattern of developmental strengths and weaknesses. CONCLUSIONS: This is the first large-scale longitudinal study to show that the acquisition of adaptive behavior slows as individuals with fragile X syndrome age. It is imperative to ensure that assessments of adaptive behavior skills are part of intervention programs focusing on childhood and adolescence in this condition. PMID:25070318

  10. Molecular Robots Obeying Asimov's Three Laws of Robotics.

    Science.gov (United States)

    Kaminka, Gal A; Spokoini-Stern, Rachel; Amir, Yaniv; Agmon, Noa; Bachelet, Ido

    2017-01-01

    Asimov's three laws of robotics, which were shaped in the literary work of Isaac Asimov (1920-1992) and others, define a crucial code of behavior that fictional autonomous robots must obey as a condition for their integration into human society. While, general implementation of these laws in robots is widely considered impractical, limited-scope versions have been demonstrated and have proven useful in spurring scientific debate on aspects of safety and autonomy in robots and intelligent systems. In this work, we use Asimov's laws to examine these notions in molecular robots fabricated from DNA origami. We successfully programmed these robots to obey, by means of interactions between individual robots in a large population, an appropriately scoped variant of Asimov's laws, and even emulate the key scenario from Asimov's story "Runaround," in which a fictional robot gets into trouble despite adhering to the laws. Our findings show that abstract, complex notions can be encoded and implemented at the molecular scale, when we understand robots on this scale on the basis of their interactions.

  11. How do walkers behave when crossing the way of a mobile robot that replicates human interaction rules?

    Science.gov (United States)

    Vassallo, Christian; Olivier, Anne-Hélène; Souères, Philippe; Crétual, Armel; Stasse, Olivier; Pettré, Julien

    2018-02-01

    Previous studies showed the existence of implicit interaction rules shared by human walkers when crossing each other. Especially, each walker contributes to the collision avoidance task and the crossing order, as set at the beginning, is preserved along the interaction. This order determines the adaptation strategy: the first arrived increases his/her advance by slightly accelerating and changing his/her heading, whereas the second one slows down and moves in the opposite direction. In this study, we analyzed the behavior of human walkers crossing the trajectory of a mobile robot that was programmed to reproduce this human avoidance strategy. In contrast with a previous study, which showed that humans mostly prefer to give the way to a non-reactive robot, we observed similar behaviors between human-human avoidance and human-robot avoidance when the robot replicates the human interaction rules. We discuss this result in relation with the importance of controlling robots in a human-like way in order to ease their cohabitation with humans. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Sociable mobile robots through self-maintained energy

    DEFF Research Database (Denmark)

    Ngo, Trung Dung; Schiøler, Henrik

    2006-01-01

    society, collecting and sharing are experimentally recognized as the highest property. This paper issues an approach to sociable robots using self-maintained energy in robot society, which is naturally inspired from swarm behavior of honey-bee and ant. Typically, autonomous mobile robots are usually......Research of sociable robots has emphasized interaction and coordination of mobile robots with inspiration from natural behavior of birds, insects, and fish: flocking, foraging, collecting, sharing and so forth. However, the animal behaviors are looking for food towards survival. In an animal...... equipped with a finite energy, thus they can operate in a finite time. To overcome the limitation, we describe practical deployment of a group of mobile robot with the possibility of carrying and exchanging fuel, e.g. battery to other robots. Early implementation that includes modular hardware and control...

  13. Robot development for nuclear material processing

    International Nuclear Information System (INIS)

    Pedrotti, L.R.; Armantrout, G.A.; Allen, D.C.; Sievers, R.H. Sr.

    1991-07-01

    The Department of Energy is seeking to modernize its special nuclear material (SNM) production facilities and concurrently reduce radiation exposures and process and incidental radioactive waste generated. As part of this program, Lawrence Livermore National Laboratory (LLNL) lead team is developing and adapting generic and specific applications of commercial robotic technologies to SNM pyrochemical processing and other operations. A working gantry robot within a sealed processing glove box and a telerobot control test bed are manifestations of this effort. This paper describes the development challenges and progress in adapting processing, robotic, and nuclear safety technologies to the application. 3 figs

  14. Heart Motion Prediction in Robotic-Assisted Beating Heart Surgery: A Nonlinear Fast Adaptive Approach

    Directory of Open Access Journals (Sweden)

    Fan Liang

    2013-01-01

    Full Text Available Off-pump Coronary Artery Bypass Graft (CABG surgery outperforms traditional on-pump surgery because the assisted robotic tools can alleviate the relative motion between the beating heart and robotic tools. Therefore, it is possible for the surgeon to operate on the beating heart and thus lessens post surgery complications for the patients. Due to the highly irregular and non-stationary nature of heart motion, it is critical that the beating heart motion is predicted in the model-based track control procedures. It is technically preferable to model heart motion in a nonlinear way because the characteristic analysis of 3D heart motion data through Bi-spectral analysis and Fourier methods demonstrates the involved nonlinearity of heart motion. We propose an adaptive nonlinear heart motion model based on the Volterra Series in this paper. We also design a fast lattice structure to achieve computational-efficiency for real-time online predictions. We argue that the quadratic term of the Volterra Series can improve the prediction accuracy by covering sharp change points and including the motion with sufficient detail. The experiment results indicate that the adaptive nonlinear heart motion prediction algorithm outperforms the autoregressive (AR and the time-varying Fourier-series models in terms of the root mean square of the prediction error and the prediction error in extreme cases.

  15. Value-driven behavior generation for an autonomous mobile ground robot

    Science.gov (United States)

    Balakirsky, Stephen B.; Lacaze, Alberto

    2002-07-01

    In this paper, we will describe a value-driven graph search technique that is capable of generating a rich variety of single and multiple vehicle behaviors. The generation of behaviors depends on cost and benefit computations that may involve terrain characteristics, line of sight to enemy positions, and cost, benefit, and risk of traveling on roads. Depending on mission priorities and cost values, real-time planners can autonomously build appropriate behaviors on the fly that include road following, cross-country movement, stealthily movement, formation keeping, and bounding overwatch. This system follows NIST's 4D/RCS architecture, and a discussion of the world model, value judgment, and behavior generation components is provided. In addition, techniques for collapsing a multidimensional model space into a cost space and planning graph constraints are discussed. The work described in this paper has been performed under the Army Research Laboratory's Robotics Demo III program.

  16. Interactions With Robots: The Truths We Reveal About Ourselves.

    Science.gov (United States)

    Broadbent, Elizabeth

    2017-01-03

    In movies, robots are often extremely humanlike. Although these robots are not yet reality, robots are currently being used in healthcare, education, and business. Robots provide benefits such as relieving loneliness and enabling communication. Engineers are trying to build robots that look and behave like humans and thus need comprehensive knowledge not only of technology but also of human cognition, emotion, and behavior. This need is driving engineers to study human behavior toward other humans and toward robots, leading to greater understanding of how humans think, feel, and behave in these contexts, including our tendencies for mindless social behaviors, anthropomorphism, uncanny feelings toward robots, and the formation of emotional attachments. However, in considering the increased use of robots, many people have concerns about deception, privacy, job loss, safety, and the loss of human relationships. Human-robot interaction is a fascinating field and one in which psychologists have much to contribute, both to the development of robots and to the study of human behavior.

  17. Information-Fusion Methods Based Simultaneous Localization and Mapping for Robot Adapting to Search and Rescue Postdisaster Environments

    Directory of Open Access Journals (Sweden)

    Hongling Wang

    2018-01-01

    Full Text Available The first application of utilizing unique information-fusion SLAM (IF-SLAM methods is developed for mobile robots performing simultaneous localization and mapping (SLAM adapting to search and rescue (SAR environments in this paper. Several fusion approaches, parallel measurements filtering, exploration trajectories fusing, and combination sensors’ measurements and mobile robots’ trajectories, are proposed. The novel integration particle filter (IPF and optimal improved EKF (IEKF algorithms are derived for information-fusion systems to perform SLAM task in SAR scenarios. The information-fusion architecture consists of multirobots and multisensors (MAM; multiple robots mount on-board laser range finder (LRF sensors, localization sonars, gyro odometry, Kinect-sensor, RGB-D camera, and other proprioceptive sensors. This information-fusion SLAM (IF-SLAM is compared with conventional methods, which indicates that fusion trajectory is more consistent with estimated trajectories and real observation trajectories. The simulations and experiments of SLAM process are conducted in both cluttered indoor environment and outdoor collapsed unstructured scenario, and experimental results validate the effectiveness of the proposed information-fusion methods in improving SLAM performances adapting to SAR scenarios.

  18. Soft Legged Wheel-Based Robot with Terrestrial Locomotion Abilities

    Directory of Open Access Journals (Sweden)

    Ali Sadeghi

    2016-12-01

    Full Text Available In recent years robotics has been influenced by a new approach, soft-robotics, bringing the idea that safe interaction with user and more adaptation to the environment can be achieved by exploiting easily deformable materials and flexible components in the structure of robots. In 2016, the soft-robotics community has promoted a new robotics challenge, named RoboSoft Grand Challenge, with the aim of bringing together different opinions on the usefulness and applicability of softness and compliancy in robotics. In this paper we describe the design and implementation of a terrestrial robot based on two soft legged wheels. The tasks predefined by the challenge were set as targets in the robot design, which finally succeeded to accomplish all the tasks. The wheels of the robot can passively climb over stairs and adapt to slippery grounds using two soft legs embedded in their structure. The soft legs, fabricated by integration of soft and rigid materials and mounted on the circumference of a conventional wheel, succeed to enhance its functionality and easily adapt to unknown grounds. The robot has a semi stiff tail that helps in the stabilization and climbing of stairs. An active wheel is embedded at the extremity of the tail in order to increase the robot maneuverability in narrow environments. Moreover two parallelogram linkages let the robot to reconfigure and shrink its size allowing entering inside gates smaller than its initial dimensions.

  19. Automatic Specialization of Modular Robot Limbs

    Data.gov (United States)

    National Aeronautics and Space Administration — Modular robotic systems have the potential to be adapted to varying tasks using a single platform and enable customizable robots to be developed faster and more...

  20. Sociable Robots Through Self-Maintained Energy

    Directory of Open Access Journals (Sweden)

    Trung Dung Ngo

    2006-12-01

    Full Text Available Research of autonomous mobile robots has mostly emphasized interaction and coordination that are natually inspired from biological behavior of birds, insects, and fish: flocking, foraging, collecting, and sharing. However, most research has been only focused on autonomous behaviors in order to perform robots like animals, whereas it is lacked of determinant to those behaviours: energy. Approaching to clusted amimal and the higher, collective and sharing food among individuals are major activity to keep society being. This paper issues an approach to sociable robots using self-maintained energy in cooperative mobile robots, which is dominantly inspired from swarm behavior of collecting and sharing food of honey-bee and ant. Autonomous mobile robots are usually equipped with a finite energy, thus they can operate in a finite time. To overcome the finitude, we describe practical deployment of mobile robots that are capable of carrying and exchanging fuel to other robots. Mechanism implementation including modular hardware and control architecture to demonstrate the capabicities of the approach is presented. Subsequently, the battery exchange algorithm basically based on probabilistic modeling of total energy on each robot located in its local vicinity is described. The paper is concluded with challenging works of chain of mobile robots, rescue, repair, and relation of heterogeneous robots.

  1. Sociable Robots through Self-maintained Energy

    Directory of Open Access Journals (Sweden)

    Henrik Schioler

    2008-11-01

    Full Text Available Research of autonomous mobile robots has mostly emphasized interaction and coordination that are natually inspired from biological behavior of birds, insects, and fish: flocking, foraging, collecting, and sharing. However, most research has been only focused on autonomous behaviors in order to perform robots like animals, whereas it is lacked of determinant to those behaviours: energy. Approaching to clusted amimal and the higher, collective and sharing food among individuals are major activity to keep society being. This paper issues an approach to sociable robots using self-maintained energy in cooperative mobile robots, which is dominantly inspired from swarm behavior of collecting and sharing food of honey-bee and ant. Autonomous mobile robots are usually equipped with a finite energy, thus they can operate in a finite time. To overcome the finitude, we describe practical deployment of mobile robots that are capable of carrying and exchanging fuel to other robots. Mechanism implementation including modular hardware and control architecture to demonstrate the capabicities of the approach is presented. Subsequently, the battery exchange algorithm basically based on probabilistic modeling of total energy on each robot located in its local vicinity is described. The paper is concluded with challenging works of chain of mobile robots, rescue, repair, and relation of heterogeneous robots.

  2. Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

    Science.gov (United States)

    Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

    2018-04-01

    In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

  3. Adaptive Control for Revolute Joints Robot Manipulator with Uncertain/Unknown Dynamic Parameters and in Presence of Disturbance in Control Input

    DEFF Research Database (Denmark)

    Seyed Sakha, Masoud; Shaker, Hamid Reza

    2017-01-01

    This paper presents an effective adaptive controller for revolute joints robot manipulator where the control input is accompanied with a random disturbance (with unknown PSD). It is clear that, disturbance can compromise the overall performance of the system. To cope with this problem, a control...... technique is proposed which uses the concept of exponential practical stability. Unlike other counterparts, the proposed method does not need information such as the physical parameters of robot and gravitational acceleration. The results show that the proposed controller achieves an excellent performance...

  4. Special Issue on Intelligent Robots

    Directory of Open Access Journals (Sweden)

    Genci Capi

    2013-08-01

    Full Text Available The research on intelligent robots will produce robots that are able to operate in everyday life environments, to adapt their program according to environment changes, and to cooperate with other team members and humans. Operating in human environments, robots need to process, in real time, a large amount of sensory data—such as vision, laser, microphone—in order to determine the best action. Intelligent algorithms have been successfully applied to link complex sensory data to robot action. This editorial briefly summarizes recent findings in the field of intelligent robots as described in the articles published in this special issue.

  5. Behavioral and neural Darwinism: selectionist function and mechanism in adaptive behavior dynamics.

    Science.gov (United States)

    McDowell, J J

    2010-05-01

    An evolutionary theory of behavior dynamics and a theory of neuronal group selection share a common selectionist framework. The theory of behavior dynamics instantiates abstractly the idea that behavior is selected by its consequences. It implements Darwinian principles of selection, reproduction, and mutation to generate adaptive behavior in virtual organisms. The behavior generated by the theory has been shown to be quantitatively indistinguishable from that of live organisms. The theory of neuronal group selection suggests a mechanism whereby the abstract principles of the evolutionary theory may be implemented in the nervous systems of biological organisms. According to this theory, groups of neurons subserving behavior may be selected by synaptic modifications that occur when the consequences of behavior activate value systems in the brain. Together, these theories constitute a framework for a comprehensive account of adaptive behavior that extends from brain function to the behavior of whole organisms in quantitative detail. Copyright (c) 2009 Elsevier B.V. All rights reserved.

  6. Soft computing in advanced robotics

    CERN Document Server

    Kobayashi, Ichiro; Kim, Euntai

    2014-01-01

    Intelligent system and robotics are inevitably bound up; intelligent robots makes embodiment of system integration by using the intelligent systems. We can figure out that intelligent systems are to cell units, while intelligent robots are to body components. The two technologies have been synchronized in progress. Making leverage of the robotics and intelligent systems, applications cover boundlessly the range from our daily life to space station; manufacturing, healthcare, environment, energy, education, personal assistance, logistics. This book aims at presenting the research results in relevance with intelligent robotics technology. We propose to researchers and practitioners some methods to advance the intelligent systems and apply them to advanced robotics technology. This book consists of 10 contributions that feature mobile robots, robot emotion, electric power steering, multi-agent, fuzzy visual navigation, adaptive network-based fuzzy inference system, swarm EKF localization and inspection robot. Th...

  7. Applying commercial robotic technology to radioactive material processing

    International Nuclear Information System (INIS)

    Grasz, E.L.; Sievers, R.H. Jr.

    1990-11-01

    The development of robotic systems for glove box process automation is motivated by the need to reduce operator radiation dosage, minimize the generation of process waste, and to improve the security of nuclear materials. Commercial robotic systems are available with the required capabilities but are not compatible with a glove box environment. Alpha radiation, concentrated dust, a dry atmosphere and restricted work space result in the need for unique adaptations to commercial robotics. Implementation of these adaptations to commercial robotics require performance trade-offs. A design and development effort has been initiated to evaluate the feasibility of using a commercial overhead gantry robot for glove box processing. This paper will present the initial results and observations for this development effort. 1 ref

  8. Traveling Robots and Their Cultural Baggage

    DEFF Research Database (Denmark)

    Blond, Lasse

    When social robots are imported from Asia to Europe they bring along with them a cultural luggage consisting of foreign sociotechnical imaginary. The effort to adopt the robot Silbot to Nordic social services exposed unfamiliar and cultural-dependent views of care, cognition, health and human...... nature. Studying Silbot in “the wild” highlighted these issues as well as the human-robot interaction and the adaptation of the robot to real life praxis. The importance of comprehending robots as parts of sociotechnical ensembles is emphasized as well as the observance of how robots are shaped...... by the cultural context in the recipient countries....

  9. Self-Organizing Robots

    CERN Document Server

    Murata, Satoshi

    2012-01-01

    It is man’s ongoing hope that a machine could somehow adapt to its environment by reorganizing itself. This is what the notion of self-organizing robots is based on. The theme of this book is to examine the feasibility of creating such robots within the limitations of current mechanical engineering. The topics comprise the following aspects of such a pursuit: the philosophy of design of self-organizing mechanical systems; self-organization in biological systems; the history of self-organizing mechanical systems; a case study of a self-assembling/self-repairing system as an autonomous distributed system; a self-organizing robot that can create its own shape and robotic motion; implementation and instrumentation of self-organizing robots; and the future of self-organizing robots. All topics are illustrated with many up-to-date examples, including those from the authors’ own work. The book does not require advanced knowledge of mathematics to be understood, and will be of great benefit to students in the rob...

  10. Information theory and robotics meet to study predator-prey interactions

    Science.gov (United States)

    Neri, Daniele; Ruberto, Tommaso; Cord-Cruz, Gabrielle; Porfiri, Maurizio

    2017-07-01

    Transfer entropy holds promise to advance our understanding of animal behavior, by affording the identification of causal relationships that underlie animal interactions. A critical step toward the reliable implementation of this powerful information-theoretic concept entails the design of experiments in which causal relationships could be systematically controlled. Here, we put forward a robotics-based experimental approach to test the validity of transfer entropy in the study of predator-prey interactions. We investigate the behavioral response of zebrafish to a fear-evoking robotic stimulus, designed after the morpho-physiology of the red tiger oscar and actuated along preprogrammed trajectories. From the time series of the positions of the zebrafish and the robotic stimulus, we demonstrate that transfer entropy correctly identifies the influence of the stimulus on the focal subject. Building on this evidence, we apply transfer entropy to study the interactions between zebrafish and a live red tiger oscar. The analysis of transfer entropy reveals a change in the direction of the information flow, suggesting a mutual influence between the predator and the prey, where the predator adapts its strategy as a function of the movement of the prey, which, in turn, adjusts its escape as a function of the predator motion. Through the integration of information theory and robotics, this study posits a new approach to study predator-prey interactions in freshwater fish.

  11. A Behavior-Based Approach for Educational Robotics Activities

    Science.gov (United States)

    De Cristoforis, P.; Pedre, S.; Nitsche, M.; Fischer, T.; Pessacg, F.; Di Pietro, C.

    2013-01-01

    Educational robotics proposes the use of robots as a teaching resource that enables inexperienced students to approach topics in fields unrelated to robotics. In recent years, these activities have grown substantially in elementary and secondary school classrooms and also in outreach experiences to interest students in science, technology,…

  12. Adaptive Controller Effects on Pilot Behavior

    Science.gov (United States)

    Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

    2014-01-01

    Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

  13. Architecture for Multiple Interacting Robot Intelligences

    Science.gov (United States)

    Peters, Richard Alan, II (Inventor)

    2008-01-01

    An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a database associative memory (DBAM) that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

  14. Collision-free motion coordination of heterogeneous robots

    Energy Technology Data Exchange (ETDEWEB)

    Ko, Nak Yong [Chosun University, Gwangju (Korea, Republic of); Seo, Dong Jin [RedOne Technologies, Gwangju (Korea, Republic of); Simmons, Reid G. [Carnegie Mellon University, Pennsylvania (United States)

    2008-11-15

    This paper proposes a method to coordinate the motion of multiple heterogeneous robots on a network. The proposed method uses prioritization and avoidance. Priority is assigned to each robot; a robot with lower priority avoids the robots of higher priority. To avoid collision with other robots, elastic force and potential field force are used. Also, the method can be applied separately to the motion planning of a part of a robot from that of the other parts of the robot. This is useful for application to the robots of the type mobile manipulator or highly redundant robots. The method is tested by simulation, and it results in smooth and adaptive coordination in an environment with multiple heterogeneous robots

  15. Collision-free motion coordination of heterogeneous robots

    International Nuclear Information System (INIS)

    Ko, Nak Yong; Seo, Dong Jin; Simmons, Reid G.

    2008-01-01

    This paper proposes a method to coordinate the motion of multiple heterogeneous robots on a network. The proposed method uses prioritization and avoidance. Priority is assigned to each robot; a robot with lower priority avoids the robots of higher priority. To avoid collision with other robots, elastic force and potential field force are used. Also, the method can be applied separately to the motion planning of a part of a robot from that of the other parts of the robot. This is useful for application to the robots of the type mobile manipulator or highly redundant robots. The method is tested by simulation, and it results in smooth and adaptive coordination in an environment with multiple heterogeneous robots

  16. Foraging behavior analysis of swarm robotics system

    Directory of Open Access Journals (Sweden)

    Sakthivelmurugan E.

    2018-01-01

    Full Text Available Swarm robotics is a number of small robots that are synchronically works together to accomplish a given task. Swarm robotics faces many problems in performing a given task. The problems are pattern formation, aggregation, Chain formation, self-assembly, coordinated movement, hole avoidance, foraging and self-deployment. Foraging is most essential part in swarm robotics. Foraging is the task to discover the item and get back into the shell. The researchers conducted foraging experiments with random-movement of robots and they have end up with unique solutions. Most of the researchers have conducted experiments using the circular arena. The shell is placed at the centre of the arena and environment boundary is well known. In this study, an attempt is made to different strategic movements like straight line approach, parallel line approach, divider approach, expanding square approach, and parallel sweep approach. All these approaches are to be simulated by using player/stage open-source simulation software based on C and C++ programming language in Linux operating system. Finally statistical comparison will be done with task completion time of all these strategies using ANOVA to identify the significant searching strategy.

  17. Emotion based human-robot interaction

    Directory of Open Access Journals (Sweden)

    Berns Karsten

    2018-01-01

    Full Text Available Human-machine interaction is a major challenge in the development of complex humanoid robots. In addition to verbal communication the use of non-verbal cues such as hand, arm and body gestures or mimics can improve the understanding of the intention of the robot. On the other hand, by perceiving such mechanisms of a human in a typical interaction scenario the humanoid robot can adapt its interaction skills in a better way. In this work, the perception system of two social robots, ROMAN and ROBIN of the RRLAB of the TU Kaiserslautern, is presented in the range of human-robot interaction.

  18. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

    Science.gov (United States)

    Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

    2016-01-01

    In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion.

  19. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation

    Science.gov (United States)

    Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

    2016-01-01

    In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion. PMID:26881743

  20. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

    Directory of Open Access Journals (Sweden)

    Luka Peternel

    Full Text Available In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion.

  1. Perspectives of construction robots

    Science.gov (United States)

    Stepanov, M. A.; Gridchin, A. M.

    2018-03-01

    This article is an overview of construction robots features, based on formulating the list of requirements for different types of construction robots in relation to different types of construction works.. It describes a variety of construction works and ways to construct new or to adapt existing robot designs for a construction process. Also, it shows the prospects of AI-controlled machines, implementation of automated control systems and networks on construction sites. In the end, different ways to develop and improve, including ecological aspect, the construction process through the wide robotization, creating of data communication networks and, in perspective, establishing of fully AI-controlled construction complex are formulated.

  2. Embodying a cognitive model in a mobile robot

    Science.gov (United States)

    Benjamin, D. Paul; Lyons, Damian; Lonsdale, Deryle

    2006-10-01

    The ADAPT project is a collaboration of researchers in robotics, linguistics and artificial intelligence at three universities to create a cognitive architecture specifically designed to be embodied in a mobile robot. There are major respects in which existing cognitive architectures are inadequate for robot cognition. In particular, they lack support for true concurrency and for active perception. ADAPT addresses these deficiencies by modeling the world as a network of concurrent schemas, and modeling perception as problem solving. Schemas are represented using the RS (Robot Schemas) language, and are activated by spreading activation. RS provides a powerful language for distributed control of concurrent processes. Also, The formal semantics of RS provides the basis for the semantics of ADAPT's use of natural language. We have implemented the RS language in Soar, a mature cognitive architecture originally developed at CMU and used at a number of universities and companies. Soar's subgoaling and learning capabilities enable ADAPT to manage the complexity of its environment and to learn new schemas from experience. We describe the issues faced in developing an embodied cognitive architecture, and our implementation choices.

  3. Learning-based adaptive prescribed performance control of postcapture space robot-target combination without inertia identifications

    Science.gov (United States)

    Wei, Caisheng; Luo, Jianjun; Dai, Honghua; Bian, Zilin; Yuan, Jianping

    2018-05-01

    In this paper, a novel learning-based adaptive attitude takeover control method is investigated for the postcapture space robot-target combination with guaranteed prescribed performance in the presence of unknown inertial properties and external disturbance. First, a new static prescribed performance controller is developed to guarantee that all the involved attitude tracking errors are uniformly ultimately bounded by quantitatively characterizing the transient and steady-state performance of the combination. Then, a learning-based supplementary adaptive strategy based on adaptive dynamic programming is introduced to improve the tracking performance of static controller in terms of robustness and adaptiveness only utilizing the input/output data of the combination. Compared with the existing works, the prominent advantage is that the unknown inertial properties are not required to identify in the development of learning-based adaptive control law, which dramatically decreases the complexity and difficulty of the relevant controller design. Moreover, the transient and steady-state performance is guaranteed a priori by designer-specialized performance functions without resorting to repeated regulations of the controller parameters. Finally, the three groups of illustrative examples are employed to verify the effectiveness of the proposed control method.

  4. Autonomous mobile robot teams

    Science.gov (United States)

    Agah, Arvin; Bekey, George A.

    1994-01-01

    This paper describes autonomous mobile robot teams performing tasks in unstructured environments. The behavior and the intelligence of the group is distributed, and the system does not include a central command base or leader. The novel concept of the Tropism-Based Cognitive Architecture is introduced, which is used by the robots in order to produce behavior transforming their sensory information to proper action. The results of a number of simulation experiments are presented. These experiments include worlds where the robot teams must locate, decompose, and gather objects, and defend themselves against hostile predators, while navigating around stationary and mobile obstacles.

  5. Cognitive and sociocultural aspects of robotized technology: innovative processes of adaptation

    Science.gov (United States)

    Kvesko, S. B.; Kvesko, B. B.; Kornienko, M. A.; Nikitina, Y. A.; Pankova, N. M.

    2018-05-01

    The paper dwells upon interaction between socio-cultural phenomena and cognitive characteristics of robotized technology. The interdisciplinary approach was employed in order to cast light on the manifold and multilevel identity of scientific advance in terms of robotized technology within the mental realm. Analyzing robotized technology from the viewpoint of its significance for the modern society is one of the upcoming trends in the contemporary scientific realm. The robots under production are capable of interacting with people; this results in a growing necessity for the studies on social status of robotized technological items. Socio-cultural aspect of cognitive robotized technology is reflected in the fact that the nature becomes ‘aware’ of itself via human brain, a human being tends to strives for perfection in their intellectual and moral dimensions.

  6. Evolving self-assembly in autonomous homogeneous robots: experiments with two physical robots.

    Science.gov (United States)

    Ampatzis, Christos; Tuci, Elio; Trianni, Vito; Christensen, Anders Lyhne; Dorigo, Marco

    2009-01-01

    This research work illustrates an approach to the design of controllers for self-assembling robots in which the self-assembly is initiated and regulated by perceptual cues that are brought forth by the physical robots through their dynamical interactions. More specifically, we present a homogeneous control system that can achieve assembly between two modules (two fully autonomous robots) of a mobile self-reconfigurable system without a priori introduced behavioral or morphological heterogeneities. The controllers are dynamic neural networks evolved in simulation that directly control all the actuators of the two robots. The neurocontrollers cause the dynamic specialization of the robots by allocating roles between them based solely on their interaction. We show that the best evolved controller proves to be successful when tested on a real hardware platform, the swarm-bot. The performance achieved is similar to the one achieved by existing modular or behavior-based approaches, also due to the effect of an emergent recovery mechanism that was neither explicitly rewarded by the fitness function, nor observed during the evolutionary simulation. Our results suggest that direct access to the orientations or intentions of the other agents is not a necessary condition for robot coordination: Our robots coordinate without direct or explicit communication, contrary to what is assumed by most research works in collective robotics. This work also contributes to strengthening the evidence that evolutionary robotics is a design methodology that can tackle real-world tasks demanding fine sensory-motor coordination.

  7. Velocity-curvature patterns limit human-robot physical interaction.

    Science.gov (United States)

    Maurice, Pauline; Huber, Meghan E; Hogan, Neville; Sternad, Dagmar

    2018-01-01

    Physical human-robot collaboration is becoming more common, both in industrial and service robotics. Cooperative execution of a task requires intuitive and efficient interaction between both actors. For humans, this means being able to predict and adapt to robot movements. Given that natural human movement exhibits several robust features, we examined whether human-robot physical interaction is facilitated when these features are considered in robot control. The present study investigated how humans adapt to biological and non-biological velocity patterns in robot movements. Participants held the end-effector of a robot that traced an elliptic path with either biological (two-thirds power law) or non-biological velocity profiles. Participants were instructed to minimize the force applied on the robot end-effector. Results showed that the applied force was significantly lower when the robot moved with a biological velocity pattern. With extensive practice and enhanced feedback, participants were able to decrease their force when following a non-biological velocity pattern, but never reached forces below those obtained with the 2/3 power law profile. These results suggest that some robust features observed in natural human movements are also a strong preference in guided movements. Therefore, such features should be considered in human-robot physical collaboration.

  8. Robust controller with adaptation within the boundary layer: application to nuclear underwater inspection robot

    International Nuclear Information System (INIS)

    Park, Gee Yong; Yoon, Ji Sup; Hong, Dong Hee; Jeong, Jae Hoo

    2002-01-01

    In this paper, the robust control scheme with the improved control performance within the boundary layer is proposed. In the control scheme, the robust controller based on the traditional variable structure control method is modified to have the adaptation within the boundary layer. From this controller, the width of the boundary layer where the robust control input is smoothened out can be given by an appropriate value. But the improve control performance within the boundary layer can be achieved without the so-called control chattering because the role of adaptive control is to compensate for the uncovered portions of the robust control occurred from the continuous approximation within the boundary layer. Simulation tests for circular navigation of an underwater wall-ranging robot developed for inspection of wall surfaces in the research reactor, TRIGA MARK III, confirm the performance improvement

  9. Robot Games for Elderly

    DEFF Research Database (Denmark)

    Hansen, Søren Tranberg

    2011-01-01

    improve a person’s overall health, and this thesis investigates how games based on an autonomous, mobile robot platform, can be used to motivate elderly to move physically while playing. The focus of the investigation is on the development of games for an autonomous, mobile robot based on algorithms using...... spatio-temporal information about player behaviour - more specifically, I investigate three types of games each using a different control strategy. The first game is based on basic robot control which allows the robot to detect and follow a person. A field study in a rehabilitation centre and a nursing....... The robot facilitates interaction, and the study suggests that robot based games potentially can be used for training balance and orientation. The second game consists in an adaptive game algorithm which gradually adjusts the game challenge to the mobility skills of the player based on spatio...

  10. [Effects of family cohesion and adaptability on behavioral problems in preschool children].

    Science.gov (United States)

    Wang, Yan-Ni; Xue, Hong-Li; Chen, Qian

    2016-05-01

    To investigate the effects of family cohesion and adaptability on behavioral problems in preschool children. The stratified cluster multistage sampling method was used to perform a questionnaire survey in the parents of 1 284 children aged 3-6 years in the urban area of Lanzhou, China. The general status questionnaire, Conners Child Behavior Checklist (Parent Symptom Question), and Family Adaptability and Cohesion Scale, Second edition, Chinese version (FACESII-CV) were used to investigate behavioral problems and family cohesion and adaptability. The overall detection rate of behavioral problems in preschool children was 17.13%. The children with different types of family cohesion had different detection rates of behavioral problems, and those with free-type family cohesion showed the highest detection rate of behavioral problems (40.2%). The children with different types of family adaptability also had different detection rates of behavioral problems, and those with stiffness type showed the highest detection rate of behavioral problems (25.1%). The behavioral problems in preschool children were negatively correlated with family cohesion and adaptability. During the growth of preschool children, family cohesion and adaptability have certain effects on the mental development of preschool children.

  11. Investigating positioning and gaze behaviors of social robots : people's preferences, perceptions, and behaviors

    NARCIS (Netherlands)

    Joosse, Michiel Pieter

    2017-01-01

    As technology advances, application areas for robots are no longer limited to the factories where they perform repetitive tasks behind fences. Robots are envisioned to provide services to us in everyday public spaces - in which they will encounter and interact with people. These types of robots can

  12. Fable: Socially Interactive Modular Robot

    DEFF Research Database (Denmark)

    Magnússon, Arnþór; Pacheco, Moises; Moghadam, Mikael

    2013-01-01

    Modular robots have a significant potential as user-reconfigurable robotic playware, but often lack sufficient sensing for social interaction. We address this issue with the Fable modular robotic system by exploring the use of smart sensor modules that has a better ability to sense the behavior...

  13. Vision Guided Intelligent Robot Design And Experiments

    Science.gov (United States)

    Slutzky, G. D.; Hall, E. L.

    1988-02-01

    The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

  14. Structured control for autonomous robots

    International Nuclear Information System (INIS)

    Simmons, R.G.

    1994-01-01

    To operate in rich, dynamic environments, autonomous robots must be able to effectively utilize and coordinate their limited physical and occupational resources. As complexity increases, it becomes necessary to impose explicit constraints on the control of planning, perception, and action to ensure that unwanted interactions between behaviors do not occur. This paper advocates developing complex robot systems by layering reactive behaviors onto deliberative components. In this structured control approach, the deliberative components handle normal situations and the reactive behaviors, which are explicitly constrained as to when and how they are activated, handle exceptional situations. The Task Control Architecture (TCA) has been developed to support this approach. TCA provides an integrated set of control constructs useful for implementing deliberative and reactive behaviors. The control constructs facilitate modular and evolutionary system development: they are used to integrate and coordinate planning, perception, and execution, and to incrementally improve the efficiency and robustness of the robot systems. To date, TCA has been used in implementing a half-dozen mobile robot systems, including an autonomous six-legged rover and indoor mobile manipulator

  15. Adaptive robotic control driven by a versatile spiking cerebellar network.

    Directory of Open Access Journals (Sweden)

    Claudia Casellato

    Full Text Available The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning, a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.

  16. Adaptive robotic control driven by a versatile spiking cerebellar network.

    Science.gov (United States)

    Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio

    2014-01-01

    The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions.

  17. Multi-robot Cooperation Behavior Decision Based on Psychological Values

    Directory of Open Access Journals (Sweden)

    Jian JIANG

    2014-01-01

    Full Text Available The method based on psychology concept has been proved to be a successful tool used for human-robot interaction. But its related research in multi-robot cooperation has remained scarce until recent studies. To solve the problem, a decision-making mechanism based on psychological values is presented to be regarded as the basis of the multi-robot cooperation. Robots give birth to psychological values based on the estimations of environment, teammates and themselves. The mapping relationship between psychological values and cooperation tendency threshold values is set up with artificial neural network. Robots can make decision on the bases of these threshold values in cooperation scenes. Experiments show that the multi-robot cooperation method presented in the paper not only can ensure the rationality of robots’ decision-making, but also can ensure the speediness of robots’ decision-making.

  18. Fuzzy Logic Controller Design for Intelligent Robots

    Directory of Open Access Journals (Sweden)

    Ching-Han Chen

    2017-01-01

    Full Text Available This paper presents a fuzzy logic controller by which a robot can imitate biological behaviors such as avoiding obstacles or following walls. The proposed structure is implemented by integrating multiple ultrasonic sensors into a robot to collect data from a real-world environment. The decisions that govern the robot’s behavior and autopilot navigation are driven by a field programmable gate array- (FPGA- based fuzzy logic controller. The validity of the proposed controller was demonstrated by simulating three real-world scenarios to test the bionic behavior of a custom-built robot. The results revealed satisfactorily intelligent performance of the proposed fuzzy logic controller. The controller enabled the robot to demonstrate intelligent behaviors in complex environments. Furthermore, the robot’s bionic functions satisfied its design objectives.

  19. Autism and social robotics: A systematic review.

    Science.gov (United States)

    Pennisi, Paola; Tonacci, Alessandro; Tartarisco, Gennaro; Billeci, Lucia; Ruta, Liliana; Gangemi, Sebastiano; Pioggia, Giovanni

    2016-02-01

    Social robotics could be a promising method for Autism Spectrum Disorders (ASD) treatment. The aim of this article is to carry out a systematic literature review of the studies on this topic that were published in the last 10 years. We tried to address the following questions: can social robots be a useful tool in autism therapy? We followed the PRISMA guidelines, and the protocol was registered within PROSPERO database (CRD42015016158). We found many positive implications in the use of social robots in therapy as for example: ASD subjects often performed better with a robot partner rather than a human partner; sometimes, ASD patients had, toward robots, behaviors that TD patients had toward human agents; ASDs had a lot of social behaviors toward robots; during robotic sessions, ASDs showed reduced repetitive and stereotyped behaviors and, social robots manage to improve spontaneous language during therapy sessions. Therefore, robots provide therapists and researchers a means to connect with autistic subjects in an easier way, but studies in this area are still insufficient. It is necessary to clarify whether sex, intelligence quotient, and age of participants affect the outcome of therapy and whether any beneficial effects only occur during the robotic session or if they are still observable outside the clinical/experimental context. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

  20. An Integrated Framework for Human-Robot Collaborative Manipulation.

    Science.gov (United States)

    Sheng, Weihua; Thobbi, Anand; Gu, Ye

    2015-10-01

    This paper presents an integrated learning framework that enables humanoid robots to perform human-robot collaborative manipulation tasks. Specifically, a table-lifting task performed jointly by a human and a humanoid robot is chosen for validation purpose. The proposed framework is split into two phases: 1) phase I-learning to grasp the table and 2) phase II-learning to perform the manipulation task. An imitation learning approach is proposed for phase I. In phase II, the behavior of the robot is controlled by a combination of two types of controllers: 1) reactive and 2) proactive. The reactive controller lets the robot take a reactive control action to make the table horizontal. The proactive controller lets the robot take proactive actions based on human motion prediction. A measure of confidence of the prediction is also generated by the motion predictor. This confidence measure determines the leader/follower behavior of the robot. Hence, the robot can autonomously switch between the behaviors during the task. Finally, the performance of the human-robot team carrying out the collaborative manipulation task is experimentally evaluated on a platform consisting of a Nao humanoid robot and a Vicon motion capture system. Results show that the proposed framework can enable the robot to carry out the collaborative manipulation task successfully.

  1. Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction.

    Science.gov (United States)

    Kim, Su Kyoung; Kirchner, Elsa Andrea; Stefes, Arne; Kirchner, Frank

    2017-12-14

    Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, it is very demanding and tiresome for a human to continuously and explicitly generate feedback. Therefore, the development of implicit approaches is of high relevance. In this paper, we used an error-related potential (ErrP), an event-related activity in the human electroencephalogram (EEG), as an intrinsically generated implicit feedback (rewards) for RL. Initially we validated our approach with seven subjects in a simulated robot learning scenario. ErrPs were detected online in single trial with a balanced accuracy (bACC) of 91%, which was sufficient to learn to recognize gestures and the correct mapping between human gestures and robot actions in parallel. Finally, we validated our approach in a real robot scenario, in which seven subjects freely chose gestures and the real robot correctly learned the mapping between gestures and actions (ErrP detection (90% bACC)). In this paper, we demonstrated that intrinsically generated EEG-based human feedback in RL can successfully be used to implicitly improve gesture-based robot control during human-robot interaction. We call our approach intrinsic interactive RL.

  2. Improving the transparency of a rehabilitation robot by exploiting the cyclic behaviour of walking.

    Science.gov (United States)

    van Dijk, W; van der Kooij, H; Koopman, B; van Asseldonk, E H F; van der Kooij, H

    2013-06-01

    To promote active participation of neurological patients during robotic gait training, controllers, such as "assist as needed" or "cooperative control", are suggested. Apart from providing support, these controllers also require that the robot should be capable of resembling natural, unsupported, walking. This means that they should have a transparent mode, where the interaction forces between the human and the robot are minimal. Traditional feedback-control algorithms do not exploit the cyclic nature of walking to improve the transparency of the robot. The purpose of this study was to improve the transparent mode of robotic devices, by developing two controllers that use the rhythmic behavior of gait. Both controllers use adaptive frequency oscillators and kernel-based non-linear filters. Kernelbased non-linear filters can be used to estimate signals and their time derivatives, as a function of the gait phase. The first controller learns the motor angle, associated with a certain joint angle pattern, and acts as a feed-forward controller to improve the torque tracking (including the zero-torque mode). The second controller learns the state of the mechanical system and compensates for the dynamical effects (e.g. the acceleration of robot masses). Both controllers have been tested separately and in combination on a small subject population. Using the feedforward controller resulted in an improved torque tracking of at least 52 percent at the hip joint, and 61 percent at the knee joint. When both controllers were active simultaneously, the interaction power between the robot and the human leg was reduced by at least 40 percent at the thigh, and 43 percent at the shank. These results indicate that: if a robotic task is cyclic, the torque tracking and transparency can be improved by exploiting the predictions of adaptive frequency oscillator and kernel-based nonlinear filters.

  3. Reconciling White-Box and Black-Box Perspectives on Behavioral Self-adaptation

    DEFF Research Database (Denmark)

    Bruni, Roberto; Corradini, Andrea; Gadducci, Fabio

    2015-01-01

    This paper proposes to reconcile two perspectives on behavioral adaptation commonly taken at different stages of the engineering of autonomic computing systems. Requirements engineering activities often take a black-box perspective: A system is considered to be adaptive with respect to an environ......This paper proposes to reconcile two perspectives on behavioral adaptation commonly taken at different stages of the engineering of autonomic computing systems. Requirements engineering activities often take a black-box perspective: A system is considered to be adaptive with respect...... to an environment whenever the system is able to satisfy its goals irrespectively of the environment perturbations. Modeling and programming engineering activities often take a white-box perspective: A system is equipped with suitable adaptation mechanisms and its behavior is classified as adaptive depending...

  4. Studying Robots Outside the Lab

    DEFF Research Database (Denmark)

    Blond, Lasse

    and ethnographic studies will enhance understandings of the dynamics of HRI. Furthermore, the paper emphasizes how users and the context of use matters to integration of robots, as it is shown how roboticists are unable to control how their designs are implemented in practice and that the sociality of social...... robots is inscribed by its users in social practice. This paper can be seen as a contribution to studies of long-term HRI. It presents the challenges of robot adaptation in practice and discusses the limitations of the present conceptual understanding of human-robotic relations. The ethnographic data......As more and more robots enter our social world there is a strong need for further field studies of human-robotic interaction. Based on a two-year ethnographic study of the implementation of the South Korean socially assistive robot in Danish elderly care this paper argues that empirical...

  5. Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

    Science.gov (United States)

    Rodriguez, Guillermo (Editor)

    1990-01-01

    Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

  6. An embodied biologically constrained model of foraging: from classical and operant conditioning to adaptive real-world behavior in DAC-X.

    Science.gov (United States)

    Maffei, Giovanni; Santos-Pata, Diogo; Marcos, Encarni; Sánchez-Fibla, Marti; Verschure, Paul F M J

    2015-12-01

    Animals successfully forage within new environments by learning, simulating and adapting to their surroundings. The functions behind such goal-oriented behavior can be decomposed into 5 top-level objectives: 'how', 'why', 'what', 'where', 'when' (H4W). The paradigms of classical and operant conditioning describe some of the behavioral aspects found in foraging. However, it remains unclear how the organization of their underlying neural principles account for these complex behaviors. We address this problem from the perspective of the Distributed Adaptive Control theory of mind and brain (DAC) that interprets these two paradigms as expressing properties of core functional subsystems of a layered architecture. In particular, we propose DAC-X, a novel cognitive architecture that unifies the theoretical principles of DAC with biologically constrained computational models of several areas of the mammalian brain. DAC-X supports complex foraging strategies through the progressive acquisition, retention and expression of task-dependent information and associated shaping of action, from exploration to goal-oriented deliberation. We benchmark DAC-X using a robot-based hoarding task including the main perceptual and cognitive aspects of animal foraging. We show that efficient goal-oriented behavior results from the interaction of parallel learning mechanisms accounting for motor adaptation, spatial encoding and decision-making. Together, our results suggest that the H4W problem can be solved by DAC-X building on the insights from the study of classical and operant conditioning. Finally, we discuss the advantages and limitations of the proposed biologically constrained and embodied approach towards the study of cognition and the relation of DAC-X to other cognitive architectures. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Using robots to understand animal cognition.

    Science.gov (United States)

    Frohnwieser, Anna; Murray, John C; Pike, Thomas W; Wilkinson, Anna

    2016-01-01

    In recent years, robotic animals and humans have been used to answer a variety of questions related to behavior. In the case of animal behavior, these efforts have largely been in the field of behavioral ecology. They have proved to be a useful tool for this enterprise as they allow the presentation of naturalistic social stimuli whilst providing the experimenter with full control of the stimulus. In interactive experiments, the behavior of robots can be controlled in a manner that is impossible with real animals, making them ideal instruments for the study of social stimuli in animals. This paper provides an overview of the current state of the field and considers the impact that the use of robots could have on fundamental questions related to comparative psychology: namely, perception, spatial cognition, social cognition, and early cognitive development. We make the case that the use of robots to investigate these key areas could have an important impact on the field of animal cognition. © 2016 Society for the Experimental Analysis of Behavior.

  8. Robots show us how to teach them: feedback from robots shapes tutoring behavior during action learning.

    Science.gov (United States)

    Vollmer, Anna-Lisa; Mühlig, Manuel; Steil, Jochen J; Pitsch, Karola; Fritsch, Jannik; Rohlfing, Katharina J; Wrede, Britta

    2014-01-01

    Robot learning by imitation requires the detection of a tutor's action demonstration and its relevant parts. Current approaches implicitly assume a unidirectional transfer of knowledge from tutor to learner. The presented work challenges this predominant assumption based on an extensive user study with an autonomously interacting robot. We show that by providing feedback, a robot learner influences the human tutor's movement demonstrations in the process of action learning. We argue that the robot's feedback strongly shapes how tutors signal what is relevant to an action and thus advocate a paradigm shift in robot action learning research toward truly interactive systems learning in and benefiting from interaction.

  9. In Pipe Robot with Hybrid Locomotion System

    Directory of Open Access Journals (Sweden)

    Cristian Miclauş

    2015-06-01

    Full Text Available The first part of the paper covers aspects concerning in pipe robots and their components, such as hybrid locomotion systems and the adapting mechanisms used. The second part describes the inspection robot that was developed, which combines tracked and wheeled locomotion (hybrid locomotion. The end of the paper presents the advantages and disadvantages of the proposed robot.

  10. Design of an Action Selection Mechanism for Cooperative Soccer Robots Based on Fuzzy Decision Making Algorithm

    Directory of Open Access Journals (Sweden)

    S. Alireza Mohades Kasaei

    2010-04-01

    Full Text Available Robocup is an international competition for multi agent research and related subject like: Artificial intelligence, Image processing, machine learning, robot path planning, control, and
    obstacle avoidance. In a soccer robot game, the environment is highly competitive and dynamic. In order to work in the dynamically changing environment, the decision-making system of a soccer robot system should have the features of flexibility and real-time adaptation. In this paper we will
    focus on the Middle Size Soccer Robot league (MSL and new hierarchical hybrid fuzzy methods for decision making and action selection of a robot in Middle Size Soccer Robot league (MSL are presented. First, the behaviors of an agent are introduced, implemented and classified in two layers,
    the Low_Level_Behaviors and the High_Level_Behaviors. In the second layer, a two phase mechanism for decision making is introduced. In phase one, some useful methods are implemented which check the robot’s situation for performing required behaviors. In the next phase, the team strategy, team formation, robot’s role and the robot’s positioning system are introduced. A fuzzy logical approach is employed to recognize the team strategy and further more to tell the player the
    best position to move. We believe that a Dynamic role engine is necessary for a successful team. Dynamic role engine and formation control during offensive or defensive play, help us to prevent collision avoidance among own players when attacking the ball and obstacle avoidance of the opponents. At last, we comprised our implemented algorithm in the Robocup 2007 and 2008 and results showed the efficiency of the introduced methodology. The results are satisfactory which has already been successfully implemented in ADRO RoboCup team. This project is still in progress and some new interesting methods are described in the current report.

  11. Designing the robot inclusive space challenge

    Directory of Open Access Journals (Sweden)

    Rajesh Elara Mohan

    2015-11-01

    Full Text Available A novel robotic challenge, namely the robot inclusive spaces (RIS challenge, is proposed in this paper, which is a cross disciplinary and design focused initiative. It aims to foster the roboticists, architects, and designers towards realizing robot friendly social spaces. Contrary to conventional robotics competitions focusing on designing robots and its component technologies, robot inclusive spaces challenge adopts an interdisciplinary “design for robots” strategy to overcome the traditional research problem in real world deployments of social robots. In order to realize the RIS, various architectural elements must be adapted including: design principles for inclusive spaces, lighting schemes, furniture choices and arrangement, wall and floor surfaces, pathways among others. This paper introduces the format and design principles of RIS challenge, presents a first run of the challenge, and gives the corresponding analysis.

  12. Sensor fusion for mobile robot navigation

    International Nuclear Information System (INIS)

    Kam, M.; Zhu, X.; Kalata, P.

    1997-01-01

    The authors review techniques for sensor fusion in robot navigation, emphasizing algorithms for self-location. These find use when the sensor suite of a mobile robot comprises several different sensors, some complementary and some redundant. Integrating the sensor readings, the robot seeks to accomplish tasks such as constructing a map of its environment, locating itself in that map, and recognizing objects that should be avoided or sought. The review describes integration techniques in two categories: low-level fusion is used for direct integration of sensory data, resulting in parameter and state estimates; high-level fusion is used for indirect integration of sensory data in hierarchical architectures, through command arbitration and integration of control signals suggested by different modules. The review provides an arsenal of tools for addressing this (rather ill-posed) problem in machine intelligence, including Kalman filtering, rule-based techniques, behavior based algorithms and approaches that borrow from information theory, Dempster-Shafer reasoning, fuzzy logic and neural networks. It points to several further-research needs, including: robustness of decision rules; simultaneous consideration of self-location, motion planning, motion control and vehicle dynamics; the effect of sensor placement and attention focusing on sensor fusion; and adaptation of techniques from biological sensor fusion

  13. Basic emotions and adaptation. A computational and evolutionary model.

    Directory of Open Access Journals (Sweden)

    Daniela Pacella

    Full Text Available The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual "sensations" based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual's life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then

  14. Basic emotions and adaptation. A computational and evolutionary model.

    Science.gov (United States)

    Pacella, Daniela; Ponticorvo, Michela; Gigliotta, Onofrio; Miglino, Orazio

    2017-01-01

    The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual "sensations" based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual's life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then switching their behavior

  15. Learning Direction of Attention for a Social Robot in Noisy Environments

    DEFF Research Database (Denmark)

    Thomsen, Nicolai Bæk; Tan, Zheng-Hua; Lindberg, Børge

    2015-01-01

    It is essential for social robots to be able to locate and direct attention towards communicating persons, however the operating environments can be challenging. When using sound source localization (SSL) acoustic noise sources can distract the robot, which interrupts the desired interaction...... with people. Since the noise sources can be of many different kinds, it is important for the robot to adapt to any environment. In this paper we present a simple strategy for a robot to adapt to the environment using feedback from a face detection routine, thus eventually only directing attention towards...

  16. Adaptive Control of a Wearable Exoskeleton for Upper-Extremity Neurorehabilitation

    Directory of Open Access Journals (Sweden)

    Sivakumar Balasubramanian

    2012-01-01

    Full Text Available The paper describes the implementation and testing of two adaptive controllers developed for a wearable, underactuated upper extremity therapy robot – RUPERT (Robotic Upper Extremity Repetitive Trainer. The controllers developed in this study were used to implement two adaptive robotic therapy modes – the adaptive co-operative mode and the adaptive active-assist mode – that are based on two different approaches for providing robotic assistance for task practice. The adaptive active-assist mode completes therapy tasks when a subject is unable to do so voluntarily. This robotic therapy mode is a novel implementation of the idea of an active-assist therapy mode; it utilizes the measure of a subject’s motor ability, along with their real-time movement kinematics to initiate robotic assistance at the appropriate time during a movement trial. The adaptive co-operative mode, on the other hand, is based on the idea of enabling task completion instead of completing the task for the subject. Both these therapy modes were designed to adapt to a stroke subject's motor ability, and thus encourage voluntary participation from the stroke subject. The two controllers were tested on three stroke subjects practicing robot-assisted reaching movements. The results from this testing demonstrate that an underactuated wearable exoskeleton, such as RUPERT, can be used for administering robot-assisted therapy, in a manner that encourages voluntary participation from the subject undergoing therapy.

  17. Avatar Robot for Crew Performance and Behavioral Health

    Data.gov (United States)

    National Aeronautics and Space Administration — This project investigates the effectiveness of using an avatar robotic platform as a crew assistant and a family member substitute. This type of avatar robot is...

  18. To kill a mockingbird robot

    NARCIS (Netherlands)

    Bartneck, C.; Verbunt, M.N.C.; Mubin, O.; Al Mahmud, A.

    2007-01-01

    Robots are being introduced in our society but their social status is still unclear. A critical issue is if the robot's exhibition of intelligent life-like behavior leads to the users' perception of animacy. The ultimate test for the life-likeness of a robot is to kill it. We therefore conducted an

  19. Twitching in sensorimotor development from sleeping rats to robots.

    Science.gov (United States)

    Blumberg, Mark S; Marques, Hugo Gravato; Iida, Fumiya

    2013-06-17

    It is still not known how the 'rudimentary' movements of fetuses and infants are transformed into the coordinated, flexible and adaptive movements of adults. In addressing this important issue, we consider a behavior that has been perennially viewed as a functionless by-product of a dreaming brain: the jerky limb movements called myoclonic twitches. Recent work has identified the neural mechanisms that produce twitching as well as those that convey sensory feedback from twitching limbs to the spinal cord and brain. In turn, these mechanistic insights have helped inspire new ideas about the functional roles that twitching might play in the self-organization of spinal and supraspinal sensorimotor circuits. Striking support for these ideas is coming from the field of developmental robotics: when twitches are mimicked in robot models of the musculoskeletal system, the basic neural circuitry undergoes self-organization. Mutually inspired biological and synthetic approaches promise not only to produce better robots, but also to solve fundamental problems concerning the developmental origins of sensorimotor maps in the spinal cord and brain. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Adaptive control of manipulators handling hazardous waste

    International Nuclear Information System (INIS)

    Colbaugh, R.; Glass, K.

    1994-01-01

    This article focuses on developing a robot control system capable of meeting hazardous waste handling application requirements, and presents as a solution an adaptive strategy for controlling the mechanical impedance of kinematically redundant manipulators. The proposed controller is capable of accurate end-effector impedance control and effective redundancy utilization, does not require knowledge of the complex robot dynamic model or parameter values for the robot or the environment, and is implemented without calculation of the robot inverse transformation. Computer simulation results are given for a four degree of freedom redundant robot under adaptive impedance control. These results indicate that the proposed controller is capable of successfully performing important tasks in robotic waste handling applications. (author) 3 figs., 39 refs

  1. Evolutionary robotics simulations help explain why reciprocity is rare in nature.

    Science.gov (United States)

    André, Jean-Baptiste; Nolfi, Stefano

    2016-09-12

    The relative rarity of reciprocity in nature, contrary to theoretical predictions that it should be widespread, is currently one of the major puzzles in social evolution theory. Here we use evolutionary robotics to solve this puzzle. We show that models based on game theory are misleading because they neglect the mechanics of behavior. In a series of experiments with simulated robots controlled by artificial neural networks, we find that reciprocity does not evolve, and show that this results from a general constraint that likely also prevents it from evolving in the wild. Reciprocity can evolve if it requires very few mutations, as is usually assumed in evolutionary game theoretic models, but not if, more realistically, it requires the accumulation of many adaptive mutations.

  2. Exploration and Learning for Cognitive Robots

    NARCIS (Netherlands)

    Rudinac, M.

    2013-01-01

    Before a future with household robots is really feasible, those robots need to be easily adaptable to novel environments and users, be able to apply previously acquired knowledge, and able to learn from perceiving and interacting with the world and users around them. This thesis proposes a cognitive

  3. Markovian robots: Minimal navigation strategies for active particles

    Science.gov (United States)

    Nava, Luis Gómez; Großmann, Robert; Peruani, Fernando

    2018-04-01

    We explore minimal navigation strategies for active particles in complex, dynamical, external fields, introducing a class of autonomous, self-propelled particles which we call Markovian robots (MR). These machines are equipped with a navigation control system (NCS) that triggers random changes in the direction of self-propulsion of the robots. The internal state of the NCS is described by a Boolean variable that adopts two values. The temporal dynamics of this Boolean variable is dictated by a closed Markov chain—ensuring the absence of fixed points in the dynamics—with transition rates that may depend exclusively on the instantaneous, local value of the external field. Importantly, the NCS does not store past measurements of this value in continuous, internal variables. We show that despite the strong constraints, it is possible to conceive closed Markov chain motifs that lead to nontrivial motility behaviors of the MR in one, two, and three dimensions. By analytically reducing the complexity of the NCS dynamics, we obtain an effective description of the long-time motility behavior of the MR that allows us to identify the minimum requirements in the design of NCS motifs and transition rates to perform complex navigation tasks such as adaptive gradient following, detection of minima or maxima, or selection of a desired value in a dynamical, external field. We put these ideas in practice by assembling a robot that operates by the proposed minimalistic NCS to evaluate the robustness of MR, providing a proof of concept that is possible to navigate through complex information landscapes with such a simple NCS whose internal state can be stored in one bit. These ideas may prove useful for the engineering of miniaturized robots.

  4. A ROBOT AND A METHOD OF CONTROLLING A ROBOT

    DEFF Research Database (Denmark)

    2017-01-01

    The present invention relates to a robot comprising a horizontal or horizontally slanted transparent experiment layer being adapted to support items at arbitrary positions on or in the experiment layer, and a moveable sensor arranged below the transparent experimental layer said sensor being...

  5. Adaptive Hierarchical Control for the Muscle Strength Training of Stroke Survivors in Robot-Aided Upper-Limb Rehabilitation

    Directory of Open Access Journals (Sweden)

    Guozheng Xu

    2012-10-01

    Full Text Available Muscle strength training for stroke patients is of vital importance for helping survivors to progressively restore muscle strength and improve the performance of their activities in daily living (ADL. An adaptive hierarchical therapy control framework which integrates the patient's real biomechanical state estimation with task-performance quantitative evaluation is proposed. Firstly, a high-level progressive resistive supervisory controller is designed to determine the resistive force base for each training session based on the patient's online task-performance evaluation. Then, a low-level adaptive resistive force triggered controller is presented to further regulate the interactive resistive force corresponding to the patient's real-time biomechanical state – characterized by the patient's bio-damping and bio-stiffness in the course of one training session, so that the patient is challenged in a moderate but engaging and motivating way. Finally, a therapeutic robot system using a Barrett WAM™ compliant manipulator is set up. We recruited eighteen inpatient and outpatient stroke participants who were randomly allocated in experimental (robot-aided and control (conventional physical therapy groups and enrolled for sixteen weeks of progressive resistance training. The preliminary results show that the proposed therapy control strategies can enhance the recovery of strength and motor control ability.

  6. Toward cognitive robotics

    Science.gov (United States)

    Laird, John E.

    2009-05-01

    Our long-term goal is to develop autonomous robotic systems that have the cognitive abilities of humans, including communication, coordination, adapting to novel situations, and learning through experience. Our approach rests on the recent integration of the Soar cognitive architecture with both virtual and physical robotic systems. Soar has been used to develop a wide variety of knowledge-rich agents for complex virtual environments, including distributed training environments and interactive computer games. For development and testing in robotic virtual environments, Soar interfaces to a variety of robotic simulators and a simple mobile robot. We have recently made significant extensions to Soar that add new memories and new non-symbolic reasoning to Soar's original symbolic processing, which should significantly improve Soar abilities for control of robots. These extensions include episodic memory, semantic memory, reinforcement learning, and mental imagery. Episodic memory and semantic memory support the learning and recalling of prior events and situations as well as facts about the world. Reinforcement learning provides the ability of the system to tune its procedural knowledge - knowledge about how to do things. Mental imagery supports the use of diagrammatic and visual representations that are critical to support spatial reasoning. We speculate on the future of unmanned systems and the need for cognitive robotics to support dynamic instruction and taskability.

  7. Enhancing the effectiveness of human-robot teaming with a closed-loop system.

    Science.gov (United States)

    Teo, Grace; Reinerman-Jones, Lauren; Matthews, Gerald; Szalma, James; Jentsch, Florian; Hancock, Peter

    2018-02-01

    With technological developments in robotics and their increasing deployment, human-robot teams are set to be a mainstay in the future. To develop robots that possess teaming capabilities, such as being able to communicate implicitly, the present study implemented a closed-loop system. This system enabled the robot to provide adaptive aid without the need for explicit commands from the human teammate, through the use of multiple physiological workload measures. Such measures of workload vary in sensitivity and there is large inter-individual variability in physiological responses to imposed taskload. Workload models enacted via closed-loop system should accommodate such individual variability. The present research investigated the effects of the adaptive robot aid vs. imposed aid on performance and workload. Results showed that adaptive robot aid driven by an individualized workload model for physiological response resulted in greater improvements in performance compared to aid that was simply imposed by the system. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Multi-robot team design for real-world applications

    Energy Technology Data Exchange (ETDEWEB)

    Parker, L.E.

    1996-10-01

    Many of these applications are in dynamic environments requiring capabilities distributed in functionality, space, or time, and therefore often require teams of robots to work together. While much research has been done in recent years, current robotics technology is still far from achieving many of the real world applications. Two primary reasons for this technology gap are that (1) previous work has not adequately addressed the issues of fault tolerance and adaptivity in multi-robot teams, and (2) existing robotics research is often geared at specific applications and is not easily generalized to different, but related, applications. This paper addresses these issues by first describing the design issues of key importance in these real-world cooperative robotics applications: fault tolerance, reliability, adaptivity, and coherence. We then present a general architecture addressing these design issues (called ALLIANCE) that facilities multi-robot cooperation of small- to medium-sized teams in dynamic environments, performing missions composed of loosely coupled subtasks. We illustrate an implementation of ALLIANCE in a real-world application, called Bounding Overwatch, and then discuss how this architecture addresses our key design issues.

  9. Semiotics and Human-Robot Interaction

    OpenAIRE

    Sequeira, Joao; Ribeiro, M.Isabel

    2007-01-01

    The social barriers that still constrain the use of robots in modern societies will tend to vanish with the sophistication increase of interaction strategies. Communication and interaction between people and robots occurring in a friendly manner and being accessible to everyone, independent of their skills in robotics issues, will certainly foster the breaking of barriers. Socializing behaviors, such as following people, are relatively easy to obtain with current state of the art robotics. Ho...

  10. Evolutionary Fuzzy Control and Navigation for Two Wheeled Robots Cooperatively Carrying an Object in Unknown Environments.

    Science.gov (United States)

    Juang, Chia-Feng; Lai, Min-Ge; Zeng, Wan-Ting

    2015-09-01

    This paper presents a method that allows two wheeled, mobile robots to navigate unknown environments while cooperatively carrying an object. In the navigation method, a leader robot and a follower robot cooperatively perform either obstacle boundary following (OBF) or target seeking (TS) to reach a destination. The two robots are controlled by fuzzy controllers (FC) whose rules are learned through an adaptive fusion of continuous ant colony optimization and particle swarm optimization (AF-CACPSO), which avoids the time-consuming task of manually designing the controllers. The AF-CACPSO-based evolutionary fuzzy control approach is first applied to the control of a single robot to perform OBF. The learning approach is then applied to achieve cooperative OBF with two robots, where an auxiliary FC designed with the AF-CACPSO is used to control the follower robot. For cooperative TS, a rule for coordination of the two robots is developed. To navigate cooperatively, a cooperative behavior supervisor is introduced to select between cooperative OBF and cooperative TS. The performance of the AF-CACPSO is verified through comparisons with various population-based optimization algorithms for the OBF learning problem. Simulations and experiments verify the effectiveness of the approach for cooperative navigation of two robots.

  11. Specifying and testing the design rationale of social robots for behavior change in children

    NARCIS (Netherlands)

    Looije, R.; Neerincx, M.A.; Hindriks, K.V.

    2016-01-01

    We are developing a social robot that helps children with diabetes Type 1 to acquire self-management skills and routines. There is a diversity of Behavior Change Techniques (BCTs) and guidelines that seem to be useful for the development of such support, but it is not yet clear how to work out the

  12. Bureaucratization and Adaptive Behavior in the Higher Education

    Directory of Open Access Journals (Sweden)

    Vyacheslav V. Volchik

    2016-12-01

    Full Text Available The paper is devoted to researching the economic behavior of individuals in the higher education in the term of increasing bureaucratization. Reasons of bureaucracy and inefficiencies generated by it are considered on the example of the higher education sector. Constant changes in the bureaucratic system requirements need to be adapted in the behavior of actors. The authors highlight approaches to adaptation within the framework of the Austrian school of economics. Austrian approaches to adapt and the adaptive rationality concept in institutional economics are compared. The role of rationality in the process of adaptation is shown in the research. The empirical basis of the study is represented by the transcripts of 50 in-depth interviews conducted in 2015 with students, lecturers and heads of higher education institutions of the Rostov region. The main objective of the interview is the allocation of institutional change in higher education. Bureaucratization was named by respondents as one of the most important changes. The paper systematizes the respondents' answers on the impact of bureaucracy and carries out typology of adapting ways to the formal innovations. Imitating practices as a form of adaptation to the growth of the formal requirements are considered clearly. The authors display the negative impact of this adaptation form to the quality of educational activities and organizational culture.

  13. To Err Is Robot: How Humans Assess and Act toward an Erroneous Social Robot

    Directory of Open Access Journals (Sweden)

    Nicole Mirnig

    2017-05-01

    Full Text Available We conducted a user study for which we purposefully programmed faulty behavior into a robot’s routine. It was our aim to explore if participants rate the faulty robot different from an error-free robot and which reactions people show in interaction with a faulty robot. The study was based on our previous research on robot errors where we detected typical error situations and the resulting social signals of our participants during social human–robot interaction. In contrast to our previous work, where we studied video material in which robot errors occurred unintentionally, in the herein reported user study, we purposefully elicited robot errors to further explore the human interaction partners’ social signals following a robot error. Our participants interacted with a human-like NAO, and the robot either performed faulty or free from error. First, the robot asked the participants a set of predefined questions and then it asked them to complete a couple of LEGO building tasks. After the interaction, we asked the participants to rate the robot’s anthropomorphism, likability, and perceived intelligence. We also interviewed the participants on their opinion about the interaction. Additionally, we video-coded the social signals the participants showed during their interaction with the robot as well as the answers they provided the robot with. Our results show that participants liked the faulty robot significantly better than the robot that interacted flawlessly. We did not find significant differences in people’s ratings of the robot’s anthropomorphism and perceived intelligence. The qualitative data confirmed the questionnaire results in showing that although the participants recognized the robot’s mistakes, they did not necessarily reject the erroneous robot. The annotations of the video data further showed that gaze shifts (e.g., from an object to the robot or vice versa and laughter are typical reactions to unexpected robot behavior

  14. Biological Soft Robotics.

    Science.gov (United States)

    Feinberg, Adam W

    2015-01-01

    In nature, nanometer-scale molecular motors are used to generate force within cells for diverse processes from transcription and transport to muscle contraction. This adaptability and scalability across wide temporal, spatial, and force regimes have spurred the development of biological soft robotic systems that seek to mimic and extend these capabilities. This review describes how molecular motors are hierarchically organized into larger-scale structures in order to provide a basic understanding of how these systems work in nature and the complexity and functionality we hope to replicate in biological soft robotics. These span the subcellular scale to macroscale, and this article focuses on the integration of biological components with synthetic materials, coupled with bioinspired robotic design. Key examples include nanoscale molecular motor-powered actuators, microscale bacteria-controlled devices, and macroscale muscle-powered robots that grasp, walk, and swim. Finally, the current challenges and future opportunities in the field are addressed.

  15. Physician behavioral adaptability: A model to outstrip a "one size fits all" approach.

    Science.gov (United States)

    Carrard, Valérie; Schmid Mast, Marianne

    2015-10-01

    Based on a literature review, we propose a model of physician behavioral adaptability (PBA) with the goal of inspiring new research. PBA means that the physician adapts his or her behavior according to patients' different preferences. The PBA model shows how physicians infer patients' preferences and adapt their interaction behavior from one patient to the other. We claim that patients will benefit from better outcomes if their physicians show behavioral adaptability rather than a "one size fits all" approach. This literature review is based on a literature search of the PsycINFO(®) and MEDLINE(®) databases. The literature review and first results stemming from the authors' research support the validity and viability of parts of the PBA model. There is evidence suggesting that physicians are able to show behavioral flexibility when interacting with their different patients, that a match between patients' preferences and physician behavior is related to better consultation outcomes, and that physician behavioral adaptability is related to better consultation outcomes. Training of physicians' behavioral flexibility and their ability to infer patients' preferences can facilitate physician behavioral adaptability and positive patient outcomes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  16. From Autonomous Robots to Artificial Ecosystems

    Science.gov (United States)

    Mastrogiovanni, Fulvio; Sgorbissa, Antonio; Zaccaria, Renato

    During the past few years, starting from the two mainstream fields of Ambient Intelligence [2] and Robotics [17], several authors recognized the benefits of the socalled Ubiquitous Robotics paradigm. According to this perspective, mobile robots are no longer autonomous, physically situated and embodied entities adapting themselves to a world taliored for humans: on the contrary, they are able to interact with devices distributed throughout the environment and get across heterogeneous information by means of communication technologies. Information exchange, coupled with simple actuation capabilities, is meant to replace physical interaction between robots and their environment. Two benefits are evident: (i) smart environments overcome inherent limitations of mobile platforms, whereas (ii) mobile robots offer a mobility dimension unknown to smart environments.

  17. Robustly stable adaptive control of a tandem of master-slave robotic manipulators with force reflection by using a multiestimation scheme.

    Science.gov (United States)

    Ibeas, Asier; de la Sen, Manuel

    2006-10-01

    The problem of controlling a tandem of robotic manipulators composing a teleoperation system with force reflection is addressed in this paper. The final objective of this paper is twofold: 1) to design a robust control law capable of ensuring closed-loop stability for robots with uncertainties and 2) to use the so-obtained control law to improve the tracking of each robot to its corresponding reference model in comparison with previously existing controllers when the slave is interacting with the obstacle. In this way, a multiestimation-based adaptive controller is proposed. Thus, the master robot is able to follow more accurately the constrained motion defined by the slave when interacting with an obstacle than when a single-estimation-based controller is used, improving the transparency property of the teleoperation scheme. The closed-loop stability is guaranteed if a minimum residence time, which might be updated online when unknown, between different controller parameterizations is respected. Furthermore, the analysis of the teleoperation and stability capabilities of the overall scheme is carried out. Finally, some simulation examples showing the working of the multiestimation scheme complete this paper.

  18. Assistant Personal Robot (APR: Conception and Application of a Tele-Operated Assisted Living Robot

    Directory of Open Access Journals (Sweden)

    Eduard Clotet

    2016-04-01

    Full Text Available This paper presents the technical description, mechanical design, electronic components, software implementation and possible applications of a tele-operated mobile robot designed as an assisted living tool. This robotic concept has been named Assistant Personal Robot (or APR for short and has been designed as a remotely telecontrolled robotic platform built to provide social and assistive services to elderly people and those with impaired mobility. The APR features a fast high-mobility motion system adapted for tele-operation in plain indoor areas, which incorporates a high-priority collision avoidance procedure. This paper presents the mechanical architecture, electrical fundaments and software implementation required in order to develop the main functionalities of an assistive robot. The APR uses a tablet in order to implement the basic peer-to-peer videoconference and tele-operation control combined with a tactile graphic user interface. The paper also presents the development of some applications proposed in the framework of an assisted living robot.

  19. Plants : Adaptive behavior, root-brains, and minimal cognition

    NARCIS (Netherlands)

    Calvo Garzon, Paco; Keijzer, Fred

    Plant intelligence has gone largely unnoticed within the field of animal and human adaptive behavior. In this context, we will introduce current work on plant intelligence as a new set of relevant phenomena that deserves attention and also discuss its potential relevance for the study of adaptive

  20. Hedonic quality or reward? A study of basic pleasure in homeostasis and decision making of a motivated autonomous robot.

    Science.gov (United States)

    Lewis, Matthew; Cañamero, Lola

    2016-10-01

    We present a robot architecture and experiments to investigate some of the roles that pleasure plays in the decision making (action selection) process of an autonomous robot that must survive in its environment. We have conducted three sets of experiments to assess the effect of different types of pleasure-related versus unrelated to the satisfaction of physiological needs-under different environmental circumstances. Our results indicate that pleasure, including pleasure unrelated to need satisfaction, has value for homeostatic management in terms of improved viability and increased flexibility in adaptive behavior.

  1. Sistem Kontrol Robot Arm 5 DOF Berbasis Pengenalan Pola Suara Menggunakan Mel-Frequency Cepstrum Coefficients (MFCC dan Adaptive Neuro-Fuzzy Inference System (ANFIS

    Directory of Open Access Journals (Sweden)

    WS Mada Sanjaya

    2016-12-01

    Full Text Available Telah dilakukan penelitian yang menggambarkan implementasi pengenalan pola suara untuk mengontrol gerak robot arm 5 DoF dalam mengambil dan menyimpan benda. Dalam penelitian ini metode yang digunakan adalah Mel-Frequency Cepstrum Coefficients (MFCC dan Adaptive Neuro-Fuzzy Inferense System (ANFIS. Metode MFCC digunakan untuk ekstraksi ciri sinyal suara, sedangkan ANFIS digunakan sebagai metode pembelajaran untuk pengenalan pola suara. Pada proses pembelajaran ANFIS data latih yang digunakan sebanyak 6 ciri. Data suara terlatih dan data suara tak terlatih digunakan untuk pengujian sistem pengenalan pola suara. Hasil pengujian menunjukkan tingkat keberhasilan, untuk data suara terlatih sebesar 87,77% dan data tak terlatih sebesar 78,53%. Sistem pengenalan pola suara ini telah diaplikasikan dengan baik untuk mengerakan robot arm 5 DoF berbasis mikrokontroler Arduino. Have been implemented of sound pattern recognition to control 5 DoF of Arm Robot to pick and place an object. In this research used Mel-Frequency Cepstrum Coefficients (MFCC and Adaptive Neuro-Fuzzy Interferense System (ANFIS methods. MFCC method used for features extraction of sound signal, meanwhile ANFIS used to learn sound pattern recognition. On ANFIS method data learning use 6 features. Trained and not trained data used to examine the system of sound pattern identification. The result show the succesfull level, for trained data 87.77% and for not trained data 78.53%. Sound pattern identification system was appliedto controlled 5 DoF arm robot based Arduino microcontroller.

  2. An adaptive Cartesian control scheme for manipulators

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

  3. Behavioral ecology of captive species: using behavioral adaptations to assess and enhance welfare of nonhuman zoo animals.

    Science.gov (United States)

    Koene, Paul

    2013-01-01

    This project aimed to estimate a species' adaptations in nature and in captivity, assess welfare, suggest environmental changes, and find species characteristics that underlie welfare problems in nonhuman animals in the zoo. First, the current status of zoo animal welfare assessment was reviewed, and the behavioral ecology approach was outlined. In this approach, databases of species characteristics were developed using (a) literature of natural behavior and (b) captive behavior. Species characteristics were grouped in 8 functional behavioral ecological fitness-related categories: space, time, metabolic, safety, reproductive, comfort, social, and information adaptations. Assessments of the strength of behavioral adaptations in relation to environmental demands were made based on the results available from the literature. The databases with literature at the species level were coupled with databases of (c) behavioral observations and (d) welfare assessments under captive conditions. Observation and welfare assessment methods were adapted from the animal on the farm realm and applied to zoo species. It was expected that the comparison of the repertoire of behaviors in natural and captive environments would highlight welfare problems, provide solutions to welfare problems by environmental changes, and identify species characteristics underlying zoo animal welfare problems.

  4. Visual perception system and method for a humanoid robot

    Science.gov (United States)

    Wells, James W. (Inventor); Mc Kay, Neil David (Inventor); Chelian, Suhas E. (Inventor); Linn, Douglas Martin (Inventor); Wampler, II, Charles W. (Inventor); Bridgwater, Lyndon (Inventor)

    2012-01-01

    A robotic system includes a humanoid robot with robotic joints each moveable using an actuator(s), and a distributed controller for controlling the movement of each of the robotic joints. The controller includes a visual perception module (VPM) for visually identifying and tracking an object in the field of view of the robot under threshold lighting conditions. The VPM includes optical devices for collecting an image of the object, a positional extraction device, and a host machine having an algorithm for processing the image and positional information. The algorithm visually identifies and tracks the object, and automatically adapts an exposure time of the optical devices to prevent feature data loss of the image under the threshold lighting conditions. A method of identifying and tracking the object includes collecting the image, extracting positional information of the object, and automatically adapting the exposure time to thereby prevent feature data loss of the image.

  5. Understanding of Android-Based Robotic and Game Structure

    Science.gov (United States)

    Phongtraychack, A.; Syryamkin, V.

    2018-05-01

    The development of an android with impressive lifelike appearance and behavior has been a long-standing goal in robotics and a new and exciting approach of smartphone-based robotics for research and education. Recent years have been progressive for many technologies, which allowed creating such androids. There are different examples including the autonomous Erica android system capable of conversational interaction and speech synthesis technologies. The behavior of Android-based robot could be running on the phone as the robot performed a task outdoors. In this paper, we present an overview and understanding of the platform of Android-based robotic and game structure for research and education.

  6. Motion based segmentation for robot vision using adapted EM algorithm

    NARCIS (Netherlands)

    Zhao, Wei; Roos, Nico

    2016-01-01

    Robots operate in a dynamic world in which objects are often moving. The movement of objects may help the robot to segment the objects from the background. The result of the segmentation can subsequently be used to identify the objects. This paper investigates the possibility of segmenting objects

  7. ARTIE: An Integrated Environment for the Development of Affective Robot Tutors.

    Science.gov (United States)

    Imbernón Cuadrado, Luis-Eduardo; Manjarrés Riesco, Ángeles; De La Paz López, Félix

    2016-01-01

    Over the last decade robotics has attracted a great deal of interest from teachers and researchers as a valuable educational tool from preschool to highschool levels. The implementation of social-support behaviors in robot tutors, in particular in the emotional dimension, can make a significant contribution to learning efficiency. With the aim of contributing to the rising field of affective robot tutors we have developed ARTIE (Affective Robot Tutor Integrated Environment). We offer an architectural pattern which integrates any given educational software for primary school children with a component whose function is to identify the emotional state of the students who are interacting with the software, and with the driver of a robot tutor which provides personalized emotional pedagogical support to the students. In order to support the development of affective robot tutors according to the proposed architecture, we also provide a methodology which incorporates a technique for eliciting pedagogical knowledge from teachers, and a generic development platform. This platform contains a component for identiying emotional states by analysing keyboard and mouse interaction data, and a generic affective pedagogical support component which specifies the affective educational interventions (including facial expressions, body language, tone of voice,…) in terms of BML (a Behavior Model Language for virtual agent specification) files which are translated into actions of a robot tutor. The platform and the methodology are both adapted to primary school students. Finally, we illustrate the use of this platform to build a prototype implementation of the architecture, in which the educational software is instantiated with Scratch and the robot tutor with NAO. We also report on a user experiment we carried out to orient the development of the platform and of the prototype. We conclude from our work that, in the case of primary school students, it is possible to identify, without

  8. Adaptive Robotic Fabrication for Conditions of Material Inconsistency

    DEFF Research Database (Denmark)

    Nicholas, Paul; Zwierzycki, Mateusz; Clausen Nørgaard, Esben

    2017-01-01

    This paper describes research that addresses the variable behaviour of industrial quality metals and the extension of computational techniques into the fabrication process. It describes the context of robotic incremental sheet metal forming, a freeform method for imparting 3D form onto a 2D thin ...... is an offline predictive strategy based on machine learning. Rigidisation of thin metal skins......This paper describes research that addresses the variable behaviour of industrial quality metals and the extension of computational techniques into the fabrication process. It describes the context of robotic incremental sheet metal forming, a freeform method for imparting 3D form onto a 2D thin...

  9. Toward understanding social cues and signals in human?robot interaction: effects of robot gaze and proxemic behavior

    OpenAIRE

    Fiore, Stephen M.; Wiltshire, Travis J.; Lobato, Emilio J. C.; Jentsch, Florian G.; Huang, Wesley H.; Axelrod, Benjamin

    2013-01-01

    As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human–robot interaction (HRI). We then discuss the need to examine the relatio...

  10. Apparatus for multiprocessor-based control of a multiagent robot

    Science.gov (United States)

    Peters, II, Richard Alan (Inventor)

    2009-01-01

    An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

  11. Determination Of Adaptive Control Parameter Using Fuzzy Logic Controller

    Directory of Open Access Journals (Sweden)

    Omur Can Ozguney

    2017-08-01

    Full Text Available The robot industry has developed along with the increasing the use of robots in industry. This has led to increase the studies on robots. The most important part of these studies is that the robots must be work with minimum tracking trajectory error. But it is not easy for robots to track the desired trajectory because of the external disturbances and parametric uncertainty. Therefore adaptive and robust controllers are used to decrease tracking error. The aim of this study is to increase the tracking performance of the robot and minimize the trajectory tracking error. For this purpose adaptive control law for robot manipulator is identified and fuzzy logic controller is applied to find the accurate values for adaptive control parameter. Based on the Lyapunov theory stability of the uncertain system is guaranteed. In this study robot parameters are assumed to be unknown. This controller is applied to a robot model and the results of simulations are given. Controller with fuzzy logic and without fuzzy logic are compared with each other. Simulation results show that the fuzzy logic controller has improved the results.

  12. Development of constrained motion control for robot handling of hazardous waste

    International Nuclear Information System (INIS)

    Starr, G.P.

    1993-01-01

    Handling and archiving of hazardous waste is an area where automation and robotics can be of significant benefit, by removing the human operator from the workplace and its associated hazards. For reasons of safety, throughput, and reduced setup time, force-controlled robots are well-suited for hazardous materials handling. The focus of this investigation is the development of advanced force control techniques for commercial industrial robots in the surface sampling of hazardous waste containers. Two particular control strategies are considered, (1) preview control, and (2) adaptive control. Preview control uses a sensor which can ''look ahead'' and thereby reduce the effect of surface irregularity on contact force control. Adaptive control allows the robot controller to compensate for changes in the robot characteristics as it changes position, and likewise improves performance. The resulting control algorithms will be applied to a two-dimensional contour-following task using a PUMA robot at the Robotics Research Laboratory at The University of New Mexico. (author) 9 figs., 13 refs

  13. Models of behavioral change and adaptation

    NARCIS (Netherlands)

    Rasouli, S.; Timmermans, H.J.P.; Zhang, J.

    2017-01-01

    This chapter explains and summarizes models of behavioral change and adaptation, which have received less application in the life choice analysis associated with urban policy. Related to various life choices, life trajectory events are major decisions with a relatively long-lasting impact, such as

  14. A crawling robot driven by multi-stable origami

    Science.gov (United States)

    Pagano, Alexander; Yan, Tongxi; Chien, Brian; Wissa, A.; Tawfick, S.

    2017-09-01

    Using origami folding to construct and actuate mechanisms and machines offers attractive opportunities from small, scalable, and cheap robots to deployable adaptive structures. This paper presents the design of a bio-inspired origami crawling robot constructed by folding sheets of paper. The origami building block structure is based on the Kresling crease pattern (CP), a chiral tower with a polygonal base, which expands and contracts through coupled longitudinal and rotational motion similar to a screw. We design the origami to have multi-stable structural equilibria which can be tuned by changing the folding CP. Kinematic analysis of these structures based on rigid-plates and hinges at fold lines precludes the shape transformation associated with the bistability of the physical models. To capture the kinematics of the bi-stable origami, the panels’ deformation behavior is modeled utilizing principles of virtual folds. Virtual folds approximate material bending by hinged, rigid panels, which facilitates the development of a kinematic solution via rigid-plate rotation analysis. As such, the kinetics and stability of folded structures are investigated by assigning suitable torsional spring constants to the fold lines. The results presented demonstrate the effect of fold-pattern geometries on the snapping behavior of the bi-stable origami structure based on the Kresling pattern. The crawling robot is presented as a case study for the use of this origami structure to mimic crawling locomotion. The robot is comprised of two origami towers nested inside a paper bellow, and connected by 3D printed end plates. DC motors are used to actuate the expansion and contraction of the internal origami structures to achieve forward locomotion and steering. Beyond locomotion, this simple design can find applications in manipulators, booms, and active structures.

  15. Acropolis: A Fast Protoyping Robotic Application

    Directory of Open Access Journals (Sweden)

    Vincent Zalzal

    2009-03-01

    Full Text Available Acropolis is an open source middleware robotic framework for fast software prototyping and reuse of program codes. It is made up of a core software and a collection of several extension modules called plugins. Each plugin encapsulates a specific functionality needed for robotic applications. To design a robot behavior, a circuit of the involved plugins is built with a graphical user interface. A high degree of decoupling between components and a graph-based representation allow the user to build complex robot behaviors with minimal need for code writing. In addition, the Acropolis core is hardware platform independent. Well-known design patterns and layered software architecture are its key features. Through the description of three applications, we illustrate some of its usability.

  16. An adaptive PID like controller using mix locally recurrent neural network for robotic manipulator with variable payload.

    Science.gov (United States)

    Sharma, Richa; Kumar, Vikas; Gaur, Prerna; Mittal, A P

    2016-05-01

    Being complex, non-linear and coupled system, the robotic manipulator cannot be effectively controlled using classical proportional-integral-derivative (PID) controller. To enhance the effectiveness of the conventional PID controller for the nonlinear and uncertain systems, gains of the PID controller should be conservatively tuned and should adapt to the process parameter variations. In this work, a mix locally recurrent neural network (MLRNN) architecture is investigated to mimic a conventional PID controller which consists of at most three hidden nodes which act as proportional, integral and derivative node. The gains of the mix locally recurrent neural network based PID (MLRNNPID) controller scheme are initialized with a newly developed cuckoo search algorithm (CSA) based optimization method rather than assuming randomly. A sequential learning based least square algorithm is then investigated for the on-line adaptation of the gains of MLRNNPID controller. The performance of the proposed controller scheme is tested against the plant parameters uncertainties and external disturbances for both links of the two link robotic manipulator with variable payload (TL-RMWVP). The stability of the proposed controller is analyzed using Lyapunov stability criteria. A performance comparison is carried out among MLRNNPID controller, CSA optimized NNPID (OPTNNPID) controller and CSA optimized conventional PID (OPTPID) controller in order to establish the effectiveness of the MLRNNPID controller. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Evolutionary Robotics: What, Why, and Where to

    Directory of Open Access Journals (Sweden)

    Stephane eDoncieux

    2015-03-01

    Full Text Available Evolutionary robotics applies the selection, variation, and heredity principles of natural evolution to the design of robots with embodied intelligence. It can be considered as a subfield of robotics that aims to create more robust and adaptive robots. A pivotal feature of the evolutionary approach is that it considers the whole robot at once, and enables the exploitation of robot features in a holistic manner. Evolutionary robotics can also be seen as an innovative approach to the study of evolution based on a new kind of experimentalism. The use of robots as a substrate can help address questions that are difficult, if not impossible, to investigate through computer simulations or biological studies. In this paper we consider the main achievements of evolutionary robotics, focusing particularly on its contributions to both engineering and biology. We briefly elaborate on methodological issues, review some of the most interesting findings, and discuss important open issues and promising avenues for future work.

  18. Evaluation of modular robot system for maintenance tasks in hot cell

    Energy Technology Data Exchange (ETDEWEB)

    Pagala, Prithvi Sekhar, E-mail: ps.pagala@upm.es [Centre for Automation and Robotics UPM-CSIC (Spain); Ferre, Manuel, E-mail: m.ferre@upm.es [Centre for Automation and Robotics UPM-CSIC (Spain); Orona, Luis, E-mail: l.orona@gsi.de [GSI Helmholtzzentrum für Schwerionenforschung (Germany)

    2014-10-15

    Highlights: •Modular robot deployment inside hot cell for remote manipulation evaluated. •Flexible and adaptable system for variety of tasks presented. •Uses in large workspaces and evolving requirements shown. -- Abstract: This work assesses the use of a modular robot system to perform maintenance and inspection tasks such as, remote flexible inspection, manipulation and cooperation with deployed systems inside the hot cell. A flexible modular solution for the inclusion in maintenance operations is presented. The proposed heterogeneous modular robotic system is evaluated using simulations of the prototype across selected robot configuration to perform tasks. Results obtained show the advantages and ability of the modular robot to perform the necessary tasks as well as its ability to adapt and evolve depending on the need. The simulation test case inside hot cell shows modular robot configuration, a two modular arm to perform tele-operation tasks in the workspace and a wheeled platform for inspection collaborating to perform tasks. The advantage of using re-configurable modular robot over conventional robot platforms is shown.

  19. Characteristic Symptoms and Adaptive Behaviors of Children with Autism

    International Nuclear Information System (INIS)

    Rauf, N. K.; Haq, A.; Aslam, N.; Anjum, U.

    2014-01-01

    Objective: To determine the characteristic symptoms and adaptive behaviors of children with autism, as well as the distribution of autism severity groups across gender. Study Design: Cross-sectional observational study. Place and Duration of Study: Special Education Schools of Rawalpindi and Islamabad, from September 2011 to January 2012. Methodology: Thirty nine children of either gender, aged 3 - 16 years and enrolled in special education schools, fulfilled the DSM-IV-TR criteria of autism. Among those, were identified as meeting the criteria of autism. The childhood autism rating scale-2 (CARS-2) was used to study the characteristics and severity of symptoms of autism. Later, adaptive behavior scale (school edition: 2) ABS-S: 2, was administered on children (n=21) to formulate the level of adaptive functioning. Results: There were 15 boys and 8 girls with mean age of 10.6 +- 2.97 years. They showed marked impairment in verbal communication (mean=3.17 +- 0.90) followed by relating to people (mean=2.75 +- 0.83) and general impression (mean=2.73 +- 0.7). Most of the children showed average to below average adaptive behaviors on number and time (n=19, 90.5%), independent functioning (n=17, 81.0%), self direction (n=17, 81.0%), physical development (n=13, 61.9%), responsibility (n=12, 57.1%) and socialization (n=13, 61.9%) as well as poor to very poor adaptive behaviors on prevocational skill (n=15, 71.4%), language development (n=13, 61.9%) and economic development (n=13, 61.9%). The frequency of boys with autism was more towards moderate to severely impaired spectrum, without gender differences in any symptom associated with autism. Conclusion: Comprehension of the presentation of characteristic symptoms of children with autism will be helpful in devising the indigenous intervention plans that are congruent with the level of adaptive functioning. (author)

  20. Self-protection Method for Flying Robots to Avoid Collision

    OpenAIRE

    Guosheng Wu; Luning Wang; Changyuan Fan; Xi Zhu

    2008-01-01

    This paper provides a new approach to solve the motion planning problems of flying robots in uncertain 3D dynamic environments. The robots controlled by this method can adaptively choose the fast way to avoid collision without information about the shapes and trajectories of obstacles. Based on sphere coordinates the new method accomplishes collision avoidance of flying robots without any other auxiliary positioning systems. The Self-protection System gives robots self-protection abilities to...

  1. Interacting With Robots to Investigate the Bases of Social Interaction.

    Science.gov (United States)

    Sciutti, Alessandra; Sandini, Giulio

    2017-12-01

    Humans show a great natural ability at interacting with each other. Such efficiency in joint actions depends on a synergy between planned collaboration and emergent coordination, a subconscious mechanism based on a tight link between action execution and perception. This link supports phenomena as mutual adaptation, synchronization, and anticipation, which cut drastically the delays in the interaction and the need of complex verbal instructions and result in the establishment of joint intentions, the backbone of social interaction. From a neurophysiological perspective, this is possible, because the same neural system supporting action execution is responsible of the understanding and the anticipation of the observed action of others. Defining which human motion features allow for such emergent coordination with another agent would be crucial to establish more natural and efficient interaction paradigms with artificial devices, ranging from assistive and rehabilitative technology to companion robots. However, investigating the behavioral and neural mechanisms supporting natural interaction poses substantial problems. In particular, the unconscious processes at the basis of emergent coordination (e.g., unintentional movements or gazing) are very difficult-if not impossible-to restrain or control in a quantitative way for a human agent. Moreover, during an interaction, participants influence each other continuously in a complex way, resulting in behaviors that go beyond experimental control. In this paper, we propose robotics technology as a potential solution to this methodological problem. Robots indeed can establish an interaction with a human partner, contingently reacting to his actions without losing the controllability of the experiment or the naturalness of the interactive scenario. A robot could represent an "interactive probe" to assess the sensory and motor mechanisms underlying human-human interaction. We discuss this proposal with examples from our

  2. Adaptive Control Of Remote Manipulator

    Science.gov (United States)

    Seraji, Homayoun

    1989-01-01

    Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

  3. An Electromechanical Pendulum Robot Arm in Action: Dynamics and Control

    Directory of Open Access Journals (Sweden)

    A. Notué Kadjie

    2017-01-01

    Full Text Available The authors numerically investigate the dynamics and control of an electromechanical robot arm consisting of a pendulum coupled to an electrical circuit via an electromagnetic mechanism. The analysis of the dynamical behavior of the electromechanical device powered by a sinusoidal power source is carried out when the effects of the loads on the arm are neglected. It is found that the device exhibits period-n T oscillations and high amplitude oscillations when the electric current is at its smallest value. The specific case which considers the effects of the impulsive contact force caused by an external load mass pushed by the arm is also studied. It is found that the amplitude of the impulse force generates several behaviors such as jump of amplitude and distortions of the mechanical vibration and electrical signal. For more efficient functioning of the device, both piezoelectric and adaptive backstepping controls are applied on the system. It is found that the control strategies are able to mitigate the signal distortion and restore the dynamical behavior to its normal state or reduce the effects of perturbations such as a short time variation of one component or when the robot system is subject to noises.

  4. Biofeedback for robotic gait rehabilitation

    Directory of Open Access Journals (Sweden)

    Colombo Gery

    2007-01-01

    Full Text Available Abstract Background Development and increasing acceptance of rehabilitation robots as well as advances in technology allow new forms of therapy for patients with neurological disorders. Robot-assisted gait therapy can increase the training duration and the intensity for the patients while reducing the physical strain for the therapist. Optimal training effects during gait therapy generally depend on appropriate feedback about performance. Compared to manual treadmill therapy, there is a loss of physical interaction between therapist and patient with robotic gait retraining. Thus, it is difficult for the therapist to assess the necessary feedback and instructions. The aim of this study was to define a biofeedback system for a gait training robot and test its usability in subjects without neurological disorders. Methods To provide an overview of biofeedback and motivation methods applied in gait rehabilitation, previous publications and results from our own research are reviewed. A biofeedback method is presented showing how a rehabilitation robot can assess the patients' performance and deliver augmented feedback. For validation, three subjects without neurological disorders walked in a rehabilitation robot for treadmill training. Several training parameters, such as body weight support and treadmill speed, were varied to assess the robustness of the biofeedback calculation to confounding factors. Results The biofeedback values correlated well with the different activity levels of the subjects. Changes in body weight support and treadmill velocity had a minor effect on the biofeedback values. The synchronization of the robot and the treadmill affected the biofeedback values describing the stance phase. Conclusion Robot-aided assessment and feedback can extend and improve robot-aided training devices. The presented method estimates the patients' gait performance with the use of the robot's existing sensors, and displays the resulting biofeedback

  5. The perception of animacy and intelligence based on a robot's embodiment

    NARCIS (Netherlands)

    Bartneck, C.; Kanda, T.; Mubin, O.; Al Mahmud, A.

    2007-01-01

    Robots exhibit life-like behavior by performing intelligent actions. To enhance human-robot interaction it is necessary to investigate and understand how end-users perceive such animate behavior. In this paper, we report an experiment to investigate how people perceived different robot embodiments

  6. Interaction dynamics of multiple mobile robots with simple navigation strategies

    Science.gov (United States)

    Wang, P. K. C.

    1989-01-01

    The global dynamic behavior of multiple interacting autonomous mobile robots with simple navigation strategies is studied. Here, the effective spatial domain of each robot is taken to be a closed ball about its mass center. It is assumed that each robot has a specified cone of visibility such that interaction with other robots takes place only when they enter its visibility cone. Based on a particle model for the robots, various simple homing and collision-avoidance navigation strategies are derived. Then, an analysis of the dynamical behavior of the interacting robots in unbounded spatial domains is made. The article concludes with the results of computer simulations studies of two or more interacting robots.

  7. Virtual reality and robotics for stroke rehabilitation: where do we go from here?

    Science.gov (United States)

    Wade, Eric; Winstein, Carolee J

    2011-01-01

    Promoting functional recovery after stroke requires collaborative and innovative approaches to neurorehabilitation research. Task-oriented training (TOT) approaches that include challenging, adaptable, and meaningful activities have led to successful outcomes in several large-scale multisite definitive trials. This, along with recent technological advances of virtual reality and robotics, provides a fertile environment for furthering clinical research in neurorehabilitation. Both virtual reality and robotics make use of multimodal sensory interfaces to affect human behavior. In the therapeutic setting, these systems can be used to quantitatively monitor, manipulate, and augment the users' interaction with their environment, with the goal of promoting functional recovery. This article describes recent advances in virtual reality and robotics and the synergy with best clinical practice. Additionally, we describe the promise shown for automated assessments and in-home activity-based interventions. Finally, we propose a broader approach to ensuring that technology-based assessment and intervention complement evidence-based practice and maintain a patient-centered perspective.

  8. Contextual analysis of human non-verbal guide behaviors to inform the development of FROG, the Fun Robotic Outdoor Guide

    NARCIS (Netherlands)

    Karreman, Daphne Eleonora; van Dijk, Elisabeth M.A.G.; Evers, Vanessa

    2012-01-01

    This paper reports the first step in a series of studies to design the interaction behaviors of an outdoor robotic guide. We describe and report the use case development carried out to identify effective human tour guide behaviors. In this paper we focus on non-verbal communication cues in gaze,

  9. The Relation Between Intellectual Functioning and Adaptive Behavior in the Diagnosis of Intellectual Disability.

    Science.gov (United States)

    Tassé, Marc J; Luckasson, Ruth; Schalock, Robert L

    2016-12-01

    Intellectual disability originates during the developmental period and is characterized by significant limitations both in intellectual functioning and in adaptive behavior as expressed in conceptual, social, and practical adaptive skills. In this article, we present a brief history of the diagnostic criteria of intellectual disability for both the DSM-5 and AAIDD. The article also (a) provides an update of the understanding of adaptive behavior, (b) dispels two thinking errors regarding mistaken temporal or causal link between intellectual functioning and adaptive behavior, (c) explains that there is a strong correlational, but no causative, relation between intellectual functioning and adaptive behavior, and (d) asserts that once a question of determining intellectual disability is raised, both intellectual functioning and adaptive behavior are assessed and considered jointly and weighed equally in the diagnosis of intellectual disability. We discuss the problems created by an inaccurate statement that appears in the DSM-5 regarding a causal link between deficits in intellectual functioning and adaptive behavior and propose an immediate revision to remove this erroneous and confounding statement.

  10. Invariant ankle moment patterns when walking with and without a robotic ankle exoskeleton.

    Science.gov (United States)

    Kao, Pei-Chun; Lewis, Cara L; Ferris, Daniel P

    2010-01-19

    To guide development of robotic lower limb exoskeletons, it is necessary to understand how humans adapt to powered assistance. The purposes of this study were to quantify joint moments while healthy subjects adapted to a robotic ankle exoskeleton and to determine if the period of motor adaptation is dependent on the magnitude of robotic assistance. The pneumatically powered ankle exoskeleton provided plantar flexor torque controlled by the wearer's soleus electromyography (EMG). Eleven naïve individuals completed two 30-min sessions walking on a split-belt instrumented treadmill at 1.25m/s while wearing the ankle exoskeleton. After two sessions of practice, subjects reduced their soleus EMG activation by approximately 36% and walked with total ankle moment patterns similar to their unassisted gait (r(2)=0.98+/-0.02, THSD, p>0.05). They had substantially different ankle kinematic patterns compared to their unassisted gait (r(2)=0.79+/-0.12, THSD, probotic ankle exoskeleton (Gordon and Ferris, 2007). Our results strongly suggest that humans aim for similar joint moment patterns when walking with robotic assistance rather than similar kinematic patterns. In addition, greater robotic assistance provided during initial use results in a longer adaptation process than lesser robotic assistance. Copyright 2009 Elsevier Ltd. All rights reserved.

  11. Passive mapping and intermittent exploration for mobile robots

    Science.gov (United States)

    Engleson, Sean P.

    1994-01-01

    An adaptive state space architecture is combined with diktiometric representation to provide the framework for designing a robot mapping system with flexible navigation planning tasks. This involves indexing waypoints described as expectations, geometric indexing, and perceptual indexing. Matching and updating the robot's projected position and sensory inputs with indexing waypoints involves matchers, dynamic priorities, transients, and waypoint restructuring. The robot's map learning can be opganized around the principles of passive mapping.

  12. External force/velocity control for an autonomous rehabilitation robot

    Science.gov (United States)

    Saekow, Peerayuth; Neranon, Paramin; Smithmaitrie, Pruittikorn

    2018-01-01

    Stroke is a primary cause of death and the leading cause of permanent disability in adults. There are many stroke survivors, who live with a variety of levels of disability and always need rehabilitation activities on daily basis. Several studies have reported that usage of rehabilitation robotic devices shows the better improvement outcomes in upper-limb stroke patients than the conventional therapy-nurses or therapists actively help patients with exercise-based rehabilitation. This research focuses on the development of an autonomous robotic trainer designed to guide a stroke patient through an upper-limb rehabilitation task. The robotic device was designed and developed to automate the reaching exercise as mentioned. The designed robotic system is made up of a four-wheel omni-directional mobile robot, an ATI Gamma multi-axis force/torque sensor used to measure contact force and a microcontroller real-time operating system. Proportional plus Integral control was adapted to control the overall performance and stability of the autonomous assistive robot. External force control was successfully implemented to establish the behavioral control strategy for the robot force and velocity control scheme. In summary, the experimental results indicated satisfactorily stable performance of the robot force and velocity control can be considered acceptable. The gain tuning for proportional integral (PI) velocity control algorithms was suitably estimated using the Ziegler-Nichols method in which the optimized proportional and integral gains are 0.45 and 0.11, respectively. Additionally, the PI external force control gains were experimentally tuned using the trial and error method based on a set of experiments which allow a human participant moves the robot along the constrained circular path whilst attempting to minimize the radial force. The performance was analyzed based on the root mean square error (E_RMS) of the radial forces, in which the lower the variation in radial

  13. Swarming Robot Design, Construction and Software Implementation

    Science.gov (United States)

    Stolleis, Karl A.

    2014-01-01

    In this paper is presented an overview of the hardware design, construction overview, software design and software implementation for a small, low-cost robot to be used for swarming robot development. In addition to the work done on the robot, a full simulation of the robotic system was developed using Robot Operating System (ROS) and its associated simulation. The eventual use of the robots will be exploration of evolving behaviors via genetic algorithms and builds on the work done at the University of New Mexico Biological Computation Lab.

  14. An indirect adaptive neural control of a visual-based quadrotor robot for pursuing a moving target.

    Science.gov (United States)

    Shirzadeh, Masoud; Amirkhani, Abdollah; Jalali, Aliakbar; Mosavi, Mohammad R

    2015-11-01

    This paper aims to use a visual-based control mechanism to control a quadrotor type aerial robot which is in pursuit of a moving target. The nonlinear nature of a quadrotor, on the one hand, and the difficulty of obtaining an exact model for it, on the other hand, constitute two serious challenges in designing a controller for this UAV. A potential solution for such problems is the use of intelligent control methods such as those that rely on artificial neural networks and other similar approaches. In addition to the two mentioned problems, another problem that emerges due to the moving nature of a target is the uncertainty that exists in the target image. By employing an artificial neural network with a Radial Basis Function (RBF) an indirect adaptive neural controller has been designed for a quadrotor robot in search of a moving target. The results of the simulation for different paths show that the quadrotor has efficiently tracked the moving target. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  15. See You See Me: the Role of Eye Contact in Multimodal Human-Robot Interaction.

    Science.gov (United States)

    Xu, Tian Linger; Zhang, Hui; Yu, Chen

    2016-05-01

    We focus on a fundamental looking behavior in human-robot interactions - gazing at each other's face. Eye contact and mutual gaze between two social partners are critical in smooth human-human interactions. Therefore, investigating at what moments and in what ways a robot should look at a human user's face as a response to the human's gaze behavior is an important topic. Toward this goal, we developed a gaze-contingent human-robot interaction system, which relied on momentary gaze behaviors from a human user to control an interacting robot in real time. Using this system, we conducted an experiment in which human participants interacted with the robot in a joint attention task. In the experiment, we systematically manipulated the robot's gaze toward the human partner's face in real time and then analyzed the human's gaze behavior as a response to the robot's gaze behavior. We found that more face looks from the robot led to more look-backs (to the robot's face) from human participants and consequently created more mutual gaze and eye contact between the two. Moreover, participants demonstrated more coordinated and synchronized multimodal behaviors between speech and gaze when more eye contact was successfully established and maintained.

  16. Survival of falling robots

    Science.gov (United States)

    Cameron, Jonathan M.; Arkin, Ronald C.

    1992-01-01

    As mobile robots are used in more uncertain and dangerous environments, it will become important to design them so that they can survive falls. In this paper, we examine a number of mechanisms and strategies that animals use to withstand these potentially catastrophic events and extend them to the design of robots. A brief survey of several aspects of how common cats survive falls provides an understanding of the issues involved in preventing traumatic injury during a falling event. After outlining situations in which robots might fall, a number of factors affecting their survival are described. From this background, several robot design guidelines are derived. These include recommendations for the physical structure of the robot as well as requirements for the robot control architecture. A control architecture is proposed based on reactive control techniques and action-oriented perception that is geared to support this form of survival behavior.

  17. Survival of falling robots

    Science.gov (United States)

    Cameron, Jonathan M.; Arkin, Ronald C.

    1992-02-01

    As mobile robots are used in more uncertain and dangerous environments, it will become important to design them so that they can survive falls. In this paper, we examine a number of mechanisms and strategies that animals use to withstand these potentially catastrophic events and extend them to the design of robots. A brief survey of several aspects of how common cats survive falls provides an understanding of the issues involved in preventing traumatic injury during a falling event. After outlining situations in which robots might fall, a number of factors affecting their survival are described. From this background, several robot design guidelines are derived. These include recommendations for the physical structure of the robot as well as requirements for the robot control architecture. A control architecture is proposed based on reactive control techniques and action-oriented perception that is geared to support this form of survival behavior.

  18. A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots

    Directory of Open Access Journals (Sweden)

    Fang Wu

    2017-05-01

    Full Text Available Due to their efficient locomotion and natural tolerance to hazardous environments, spherical robots have wide applications in security surveillance, exploration of unknown territory and emergency response. Numerous studies have been conducted on the driving mechanism, motion planning and trajectory tracking methods of spherical robots, yet very limited studies have been conducted regarding the obstacle avoidance capability of spherical robots. Most of the existing spherical robots rely on the “hit and run” technique, which has been argued to be a reasonable strategy because spherical robots have an inherent ability to recover from collisions. Without protruding components, they will not become stuck and can simply roll back after running into bstacles. However, for small scale spherical robots that contain sensitive surveillance sensors and cannot afford to utilize heavy protective shells, the absence of obstacle avoidance solutions would leave the robot at the mercy of potentially dangerous obstacles. In this paper, a compact magnetic field-based obstacle detection and avoidance system has been developed for miniature spherical robots. It utilizes a passive magnetic field so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle, therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance the obstacle detection performance and detailed avoidance strategies are devised. Experimental results are also presented for validation purposes.

  19. Adaptive control of robotic manipulators

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.

  20. Self-organization via active exploration in robotic applications

    Science.gov (United States)

    Ogmen, H.; Prakash, R. V.

    1992-01-01

    We describe a neural network based robotic system. Unlike traditional robotic systems, our approach focussed on non-stationary problems. We indicate that self-organization capability is necessary for any system to operate successfully in a non-stationary environment. We suggest that self-organization should be based on an active exploration process. We investigated neural architectures having novelty sensitivity, selective attention, reinforcement learning, habit formation, flexible criteria categorization properties and analyzed the resulting behavior (consisting of an intelligent initiation of exploration) by computer simulations. While various computer vision researchers acknowledged recently the importance of active processes (Swain and Stricker, 1991), the proposed approaches within the new framework still suffer from a lack of self-organization (Aloimonos and Bandyopadhyay, 1987; Bajcsy, 1988). A self-organizing, neural network based robot (MAVIN) has been recently proposed (Baloch and Waxman, 1991). This robot has the capability of position, size rotation invariant pattern categorization, recognition and pavlovian conditioning. Our robot does not have initially invariant processing properties. The reason for this is the emphasis we put on active exploration. We maintain the point of view that such invariant properties emerge from an internalization of exploratory sensory-motor activity. Rather than coding the equilibria of such mental capabilities, we are seeking to capture its dynamics to understand on the one hand how the emergence of such invariances is possible and on the other hand the dynamics that lead to these invariances. The second point is crucial for an adaptive robot to acquire new invariances in non-stationary environments, as demonstrated by the inverting glass experiments of Helmholtz. We will introduce Pavlovian conditioning circuits in our future work for the precise objective of achieving the generation, coordination, and internalization

  1. iCub-HRI: A Software Framework for Complex Human–Robot Interaction Scenarios on the iCub Humanoid Robot

    Directory of Open Access Journals (Sweden)

    Tobias Fischer

    2018-03-01

    Full Text Available Generating complex, human-like behavior in a humanoid robot like the iCub requires the integration of a wide range of open source components and a scalable cognitive architecture. Hence, we present the iCub-HRI library which provides convenience wrappers for components related to perception (object recognition, agent tracking, speech recognition, and touch detection, object manipulation (basic and complex motor actions, and social interaction (speech synthesis and joint attention exposed as a C++ library with bindings for Java (allowing to use iCub-HRI within Matlab and Python. In addition to previously integrated components, the library allows for simple extension to new components and rapid prototyping by adapting to changes in interfaces between components. We also provide a set of modules which make use of the library, such as a high-level knowledge acquisition module and an action recognition module. The proposed architecture has been successfully employed for a complex human–robot interaction scenario involving the acquisition of language capabilities, execution of goal-oriented behavior and expression of a verbal narrative of the robot’s experience in the world. Accompanying this paper is a tutorial which allows a subset of this interaction to be reproduced. The architecture is aimed at researchers familiarizing themselves with the iCub ecosystem, as well as expert users, and we expect the library to be widely used in the iCub community.

  2. Inventing Japan's 'robotics culture': the repeated assembly of science, technology, and culture in social robotics.

    Science.gov (United States)

    Sabanović, Selma

    2014-06-01

    Using interviews, participant observation, and published documents, this article analyzes the co-construction of robotics and culture in Japan through the technical discourse and practices of robotics researchers. Three cases from current robotics research--the seal-like robot PARO, the Humanoid Robotics Project HRP-2 humanoid, and 'kansei robotics' - show the different ways in which scientists invoke culture to provide epistemological grounding and possibilities for social acceptance of their work. These examples show how the production and consumption of social robotic technologies are associated with traditional crafts and values, how roboticists negotiate among social, technical, and cultural constraints while designing robots, and how humans and robots are constructed as cultural subjects in social robotics discourse. The conceptual focus is on the repeated assembly of cultural models of social behavior, organization, cognition, and technology through roboticists' narratives about the development of advanced robotic technologies. This article provides a picture of robotics as the dynamic construction of technology and culture and concludes with a discussion of the limits and possibilities of this vision in promoting a culturally situated understanding of technology and a multicultural view of science.

  3. Dynamic electronic institutions in agent oriented cloud robotic systems.

    Science.gov (United States)

    Nagrath, Vineet; Morel, Olivier; Malik, Aamir; Saad, Naufal; Meriaudeau, Fabrice

    2015-01-01

    The dot-com bubble bursted in the year 2000 followed by a swift movement towards resource virtualization and cloud computing business model. Cloud computing emerged not as new form of computing or network technology but a mere remoulding of existing technologies to suit a new business model. Cloud robotics is understood as adaptation of cloud computing ideas for robotic applications. Current efforts in cloud robotics stress upon developing robots that utilize computing and service infrastructure of the cloud, without debating on the underlying business model. HTM5 is an OMG's MDA based Meta-model for agent oriented development of cloud robotic systems. The trade-view of HTM5 promotes peer-to-peer trade amongst software agents. HTM5 agents represent various cloud entities and implement their business logic on cloud interactions. Trade in a peer-to-peer cloud robotic system is based on relationships and contracts amongst several agent subsets. Electronic Institutions are associations of heterogeneous intelligent agents which interact with each other following predefined norms. In Dynamic Electronic Institutions, the process of formation, reformation and dissolution of institutions is automated leading to run time adaptations in groups of agents. DEIs in agent oriented cloud robotic ecosystems bring order and group intellect. This article presents DEI implementations through HTM5 methodology.

  4. Direct adaptive control of manipulators in Cartesian space

    Science.gov (United States)

    Seraji, H.

    1987-01-01

    A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

  5. Transformers: Shape-Changing Space Systems Built with Robotic Textiles

    Science.gov (United States)

    Stoica, Adrian

    2013-01-01

    Prior approaches to transformer-like robots had only very limited success. They suffer from lack of reliability, ability to integrate large surfaces, and very modest change in overall shape. Robots can now be built from two-dimensional (2D) layers of robotic fabric. These transformers, a new kind of robotic space system, are dramatically different from current systems in at least two ways. First, the entire transformer is built from a single, thin sheet; a flexible layer of a robotic fabric (ro-fabric); or robotic textile (ro-textile). Second, the ro-textile layer is foldable to small volume and self-unfolding to adapt shape and function to mission phases.

  6. Robots for use in autism research.

    Science.gov (United States)

    Scassellati, Brian; Admoni, Henny; Matarić, Maja

    2012-01-01

    Autism spectrum disorders are a group of lifelong disabilities that affect people's ability to communicate and to understand social cues. Research into applying robots as therapy tools has shown that robots seem to improve engagement and elicit novel social behaviors from people (particularly children and teenagers) with autism. Robot therapy for autism has been explored as one of the first application domains in the field of socially assistive robotics (SAR), which aims to develop robots that assist people with special needs through social interactions. In this review, we discuss the past decade's work in SAR systems designed for autism therapy by analyzing robot design decisions, human-robot interactions, and system evaluations. We conclude by discussing challenges and future trends for this young but rapidly developing research area.

  7. Sensory Robot Gripper

    DEFF Research Database (Denmark)

    Drimus, Alin

    The project researches and proposes a tactile sensor system for equipping robotic grippers, thus giving them a sense of touch. We start by reviewing work that covers the building of tactile sensors and we focus on the flexible sensors with multiple sensing elements. As the piezoresistive, capacit......The project researches and proposes a tactile sensor system for equipping robotic grippers, thus giving them a sense of touch. We start by reviewing work that covers the building of tactile sensors and we focus on the flexible sensors with multiple sensing elements. As the piezoresistive......, such as establishing of contact, release of contact or slip. The proposed applications are just a few examples of the advantages of equipping robotic grippers with such a tactile sensor system, that is robust, fast, affordable, adaptable to any kind of gripper and has properties similar to the human sense of touch....... Based on experimental validation, we are confident that our proposed tactile sensor solution can be successfully employed in other application areas like reactive grasping, exploration of unknown objects, slip avoidance, dexterous manipulation or service robotics....

  8. Contact Estimation in Robot Interaction

    Directory of Open Access Journals (Sweden)

    Filippo D'Ippolito

    2014-07-01

    Full Text Available In the paper, safety issues are examined in a scenario in which a robot manipulator and a human perform the same task in the same workspace. During the task execution, the human should be able to physically interact with the robot, and in this case an estimation algorithm for both interaction forces and a contact point is proposed in order to guarantee safety conditions. The method, starting from residual joint torque estimation, allows both direct and adaptive computation of the contact point and force, based on a principle of equivalence of the contact forces. At the same time, all the unintended contacts must be avoided, and a suitable post-collision strategy is considered to move the robot away from the collision area or else to reduce impact effects. Proper experimental tests have demonstrated the applicability in practice of both the post-impact strategy and the estimation algorithms; furthermore, experiments demonstrate the different behaviour resulting from the adaptation of the contact point as opposed to direct calculation.

  9. Open Issues in Evolutionary Robotics.

    Science.gov (United States)

    Silva, Fernando; Duarte, Miguel; Correia, Luís; Oliveira, Sancho Moura; Christensen, Anders Lyhne

    2016-01-01

    One of the long-term goals in evolutionary robotics is to be able to automatically synthesize controllers for real autonomous robots based only on a task specification. While a number of studies have shown the applicability of evolutionary robotics techniques for the synthesis of behavioral control, researchers have consistently been faced with a number of issues preventing the widespread adoption of evolutionary robotics for engineering purposes. In this article, we review and discuss the open issues in evolutionary robotics. First, we analyze the benefits and challenges of simulation-based evolution and subsequent deployment of controllers versus evolution on real robotic hardware. Second, we discuss specific evolutionary computation issues that have plagued evolutionary robotics: (1) the bootstrap problem, (2) deception, and (3) the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks. Finally, we address the absence of standard research practices in the field. We also discuss promising avenues of research. Our underlying motivation is the reduction of the current gap between evolutionary robotics and mainstream robotics, and the establishment of evolutionary robotics as a canonical approach for the engineering of autonomous robots.

  10. Lessons Learned in Designing User-configurable Modular Robotics

    DEFF Research Database (Denmark)

    Lund, Henrik Hautop

    2013-01-01

    User-configurable robotics allows users to easily configure robotic systems to perform task-fulfilling behaviors as desired by the users. With a user configurable robotic system, the user can easily modify the physical and func-tional aspect in terms of hardware and software components of a robotic...... with the semi-autonomous com-ponents of the user-configurable robotic system in interaction with the given environment. Components constituting such a user-configurable robotic system can be characterized as modules in a modular robotic system. Several factors in the definition and implementation...

  11. Analysis of Lamarckian Evolution in Morphologically Evolving Robots

    NARCIS (Netherlands)

    Jelisavcic, Milan; Kiesel, Rafael; Glette, Kyrre; Haasdijk, Evert; Eiben, A.E.

    Evolving robot morphologies implies the need for lifetime learning so that newborn robots can learn to manipulate their bodies. An individual’s morphology will obviously combine traits of all its parents; it must adapt its own controller to suit its morphology, and cannot rely on the controller of

  12. Automatic Modeling and Simulation of Modular Robots

    Science.gov (United States)

    Jiang, C.; Wei, H.; Zhang, Y.

    2018-03-01

    The ability of reconfiguration makes modular robots have the ability of adaptable, low-cost, self-healing and fault-tolerant. It can also be applied to a variety of mission situations. In this manuscript, a robot platform which relied on the module library was designed, based on the screw theory and module theory. Then, the configuration design method of the modular robot was proposed. And the different configurations of modular robot system have been built, including industrial mechanical arms, the mobile platform, six-legged robot and 3D exoskeleton manipulator. Finally, the simulation and verification of one system among them have been made, using the analyses of screw kinematics and polynomial planning. The results of experiments demonstrate the feasibility and superiority of this modular system.

  13. Telemanipulation of cooperative robots: a case of study

    Science.gov (United States)

    Pliego-Jiménez, Javier; Arteaga-Pérez, Marco

    2018-06-01

    This article addresses the problem of dexterous robotic grasping by means of a telemanipulation system composed of a single master and two slave robot manipulators. The slave robots are analysed as a cooperative system where it is assumed that the robots can push but not pull the object. In order to achieve a stable rigid grasp, a centralised adaptive position-force control algorithm for the slave robots is proposed. On the other hand, a linear velocity observer for the master robot is developed to avoid numerical differentiation. A set of experiments with different human operators were carried out to show the good performance and capabilities of the proposed control-observer algorithm. In addition, the dynamic model and closed-loop dynamics of the telemanipulation is presented.

  14. Human-like Compliance for Dexterous Robot Hands

    Science.gov (United States)

    Jau, Bruno M.

    1995-01-01

    This paper describes the Active Electromechanical Compliance (AEC) system that was developed for the Jau-JPL anthropomorphic robot. The AEC system imitates the functionality of the human muscle's secondary function, which is to control the joint's stiffness: AEC is implemented through servo controlling the joint drive train's stiffness. The control strategy, controlling compliant joints in teleoperation, is described. It enables automatic hybrid position and force control through utilizing sensory feedback from joint and compliance sensors. This compliant control strategy is adaptable for autonomous robot control as well. Active compliance enables dual arm manipulations, human-like soft grasping by the robot hand, and opens the way to many new robotics applications.

  15. Biological Immune System Applications on Mobile Robot for Disabled People

    Directory of Open Access Journals (Sweden)

    Songmin Jia

    2014-01-01

    Full Text Available To improve the service quality of service robots for the disabled, immune system is applied on robot for its advantages such as diversity, dynamic, parallel management, self-organization, and self-adaptation. According to the immune system theory, local environment condition sensed by robot is considered an antigen while robot is regarded as B-cell and possible node as antibody, respectively. Antibody-antigen affinity is employed to choose the optimal possible node to ensure the service robot can pass through the optimal path. The paper details the immune system applications on service robot and gives experimental results.

  16. Creating and maintaining chemical artificial life by robotic symbiosis

    DEFF Research Database (Denmark)

    Hanczyc, Martin M.; Parrilla, Juan M.; Nicholson, Arwen

    2015-01-01

    We present a robotic platform based on the open source RepRap 3D printer that can print and maintain chemical artificial life in the form of a dynamic, chemical droplet. The robot uses computer vision, a self-organizing map, and a learning program to automatically categorize the behavior of the d......We present a robotic platform based on the open source RepRap 3D printer that can print and maintain chemical artificial life in the form of a dynamic, chemical droplet. The robot uses computer vision, a self-organizing map, and a learning program to automatically categorize the behavior...... confluence of chemical, artificial intelligence, and robotic approaches to artificial life....

  17. Creating and Maintaining Chemical Artificial Life by Robotic Symbiosis

    DEFF Research Database (Denmark)

    Hanczyc, Martin; Parrilla, Juan M.; Nicholson, Arwen

    2015-01-01

    We present a robotic platform based on the open source RepRap 3D printer that can print and maintain chemical artificial life in the form of a dynamic, chemical droplet. The robot uses computer vision, a self-organizing map, and a learning program to automatically categorize the behavior of the d......We present a robotic platform based on the open source RepRap 3D printer that can print and maintain chemical artificial life in the form of a dynamic, chemical droplet. The robot uses computer vision, a self-organizing map, and a learning program to automatically categorize the behavior...... confluence of chemical, artificial intelligence, and robotic approaches to artificial life....

  18. A Plug and Produce Framework for Industrial Collaborative Robots

    DEFF Research Database (Denmark)

    Schou, Casper; Madsen, Ole

    2017-01-01

    Collaborative robots are today ever more interesting in response to the increasing need for agile manufacturing equipment. Contrary to traditional industrial robots, collaborative robots are intended for working in dynamic environments alongside the production staff. To cope with the dynamic...... environment and workflow, new configuration and control methods are needed compared to those of traditional industrial robots. The new methods should enable shop floor operators to reconfigure the robot. This article presents a plug and produce framework for industrial collaborative robots. The article...... focuses on the control framework enabling quick and easy exchange of hardware modules as an approach to achieving plug and produce. To solve this, an agent-based system is proposed building on top of the robot operating system. The framework enables robot operating system packages to be adapted...

  19. Soft Dielectric Elastomer Oscillators Driving Bioinspired Robots.

    Science.gov (United States)

    Henke, E-F Markus; Schlatter, Samuel; Anderson, Iain A

    2017-12-01

    Entirely soft robots with animal-like behavior and integrated artificial nervous systems will open up totally new perspectives and applications. To produce them, we must integrate control and actuation in the same soft structure. Soft actuators (e.g., pneumatic and hydraulic) exist but electronics are hard and stiff and remotely located. We present novel soft, electronics-free dielectric elastomer oscillators, which are able to drive bioinspired robots. As a demonstrator, we present a robot that mimics the crawling motion of the caterpillar, with an integrated artificial nervous system, soft actuators and without any conventional stiff electronic parts. Supplied with an external DC voltage, the robot autonomously generates all signals that are necessary to drive its dielectric elastomer actuators, and it translates an in-plane electromechanical oscillation into a crawling locomotion movement. Therefore, all functional and supporting parts are made of polymer materials and carbon. Besides the basic design of this first electronic-free, biomimetic robot, we present prospects to control the general behavior of such robots. The absence of conventional stiff electronics and the exclusive use of polymeric materials will provide a large step toward real animal-like robots, compliant human machine interfaces, and a new class of distributed, neuron-like internal control for robotic systems.

  20. Ethorobotics: A New Approach to Human-Robot Relationship

    Directory of Open Access Journals (Sweden)

    Ádám Miklósi

    2017-06-01

    Full Text Available Here we aim to lay the theoretical foundations of human-robot relationship drawing upon insights from disciplines that govern relevant human behaviors: ecology and ethology. We show how the paradox of the so called “uncanny valley hypothesis” can be solved by applying the “niche” concept to social robots, and relying on the natural behavior of humans. Instead of striving to build human-like social robots, engineers should construct robots that are able to maximize their performance in their niche (being optimal for some specific functions, and if they are endowed with appropriate form of social competence then humans will eventually interact with them independent of their embodiment. This new discipline, which we call ethorobotics, could change social robotics, giving a boost to new technical approaches and applications.

  1. Ethorobotics: A New Approach to Human-Robot Relationship

    Science.gov (United States)

    Miklósi, Ádám; Korondi, Péter; Matellán, Vicente; Gácsi, Márta

    2017-01-01

    Here we aim to lay the theoretical foundations of human-robot relationship drawing upon insights from disciplines that govern relevant human behaviors: ecology and ethology. We show how the paradox of the so called “uncanny valley hypothesis” can be solved by applying the “niche” concept to social robots, and relying on the natural behavior of humans. Instead of striving to build human-like social robots, engineers should construct robots that are able to maximize their performance in their niche (being optimal for some specific functions), and if they are endowed with appropriate form of social competence then humans will eventually interact with them independent of their embodiment. This new discipline, which we call ethorobotics, could change social robotics, giving a boost to new technical approaches and applications. PMID:28649213

  2. Adaptive locomotor behavior in larval zebrafish.

    Science.gov (United States)

    Portugues, Ruben; Engert, Florian

    2011-01-01

    In this study we report that larval zebrafish display adaptive locomotor output that can be driven by unexpected visual feedback. We develop a new assay that addresses visuomotor integration in restrained larval zebrafish. The assay involves a closed-loop environment in which the visual feedback a larva receives depends on its own motor output in a way that resembles freely swimming conditions. The experimenter can control the gain of this closed feedback loop, so that following a given motor output the larva experiences more or less visual feedback depending on whether the gain is high or low. We show that increases and decreases in this gain setting result in adaptive changes in behavior that lead to a generalized decrease or increase of motor output, respectively. Our behavioral analysis shows that both the duration and tail beat frequency of individual swim bouts can be modified, as well as the frequency with which bouts are elicited. These changes can be implemented rapidly, following an exposure to a new gain of just 175 ms. In addition, modifications in some behavioral parameters accumulate over tens of seconds and effects last for at least 30 s from trial to trial. These results suggest that larvae establish an internal representation of the visual feedback expected from a given motor output and that the behavioral modifications are driven by an error signal that arises from the discrepancy between this expectation and the actual visual feedback. The assay we develop presents a unique possibility for studying visuomotor integration using imaging techniques available in the larval zebrafish.

  3. Factors Influencing Maternal Behavioral Adaptability: Maternal Depressive Symptoms and Child Negative Affect.

    Science.gov (United States)

    Hummel, Alexandra C; Kiel, Elizabeth J

    2016-01-01

    In early childhood, parents play an important role in children's socioemotional development. As such, parent training is a central component of many psychological interventions for young children (Reyno & McGrath, 2006). Maternal depressive symptoms have consistently been linked to maladaptive parenting behaviors (e.g., disengagement, intrusiveness), as well as to lower parent training efficacy in the context of child psychological intervention, suggesting that mothers with higher symptomatology may be less able to be adapt their behavior according to situational demands. The goal of the current study was to examine both maternal and child factors that may influence maternal behavioral adaptability. Ninety-one mothers and their toddlers ( M = 23.93 months, 59% male) participated in a laboratory visit during which children engaged in a variety of novelty episodes designed to elicit individual differences in fear/withdrawal behaviors. Mothers also completed a questionnaire battery. Maternal behavioral adaptability was operationalized as the difference in scores for maternal involvement, comforting, and protective behavior between episodes in which mothers were instructed to refrain from interaction and those in which they were instructed to act naturally. Results indicated that when children displayed high levels of negative affect in the restricted episodes, mothers with higher levels of depressive symptoms were less able to adapt their involved behavior because they exhibited low rates of involvement across episodes regardless of instruction given. The current study serves as an intermediary step in understanding how maternal depressive symptoms may influence daily interactions with their children as well as treatment implementation and outcomes, and provides initial evidence that maternal internalizing symptoms may contribute to lower behavioral adaptability in the context of certain child behaviors due to consistent low involvement.

  4. What makes robots social? : A user’s perspective on characteristics for social human-robot interaction

    NARCIS (Netherlands)

    de Graaf, M.M.A.; Ben Allouch, Soumaya

    2015-01-01

    A common description of a social robot is for it to be capable of communicating in a humanlike manner. However, a description of what communicating in a ‘humanlike manner’ means often remains unspecified. This paper provides a set of social behaviors and certain specific features social robots

  5. A study on autonomous maintenance robot, 7

    International Nuclear Information System (INIS)

    Fukuda, Toshio; Hosokai, Hidemi; Shimasaka, Naoki; Kaneshige, Masanori; Iwasaki, Shinnosuke.

    1990-01-01

    This paper deals with the new mechanism of a new maintenance robot, Mark IV, following the previous reports on pipeline inspection and maintenance robots of Mark I, II, and III. The Mark IV has a mechanism capable of inspecting surfaces of storage tanks as well as pipeline outer surfaces, which is another capability of the maintenance robots, different from the previous ones. The main features of Mark IV are as follows, (i) The robot has a multijoint structure, so that it has better adaptability to the curvartures of pipelines and storage tanks. (ii) The joint of the robot has SMA actuators to make the robot lighter in weight. Some actuator shape characteristics are also examined for the robot structure and control. (iii) The robot has suckers at both ends so that the robot can climb up along the wall from the ground. (iv) A robot with the inch worm mechanisms has many functional motions, such that it can pass over flanges and T-joints, and transfer to adjacent pipelines with a wider range of pipe diameters. (v) A control method is given for the mobile motion control. Thus, the functional level of the maintenance robot has been greatly improved by the introduction of the Mark IV robot. (author)

  6. Controlling maximum evaluation duration in on-line and on-board evolutionary robotics

    NARCIS (Netherlands)

    Atta-ul-Qayyum, A.; Nedev, D.G.; Haasdijk, E.W.

    2014-01-01

    On-line evolution of robot controllers allows robots to adapt while they perform their proper tasks. In our investigations, robots contain their own self-sufficient evolutionary algorithm (known as the encapsulated approach) where individual solutions are evaluated by means of a time sharing scheme:

  7. Task path planning, scheduling and learning for free-ranging robot systems

    Science.gov (United States)

    Wakefield, G. Steve

    1987-01-01

    The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.

  8. Does the design of a robot influence its animacy and perceived intelligence?

    NARCIS (Netherlands)

    Bartneck, C.; Kanda, T.; Mubin, O.; Al Mahmud, A.

    2009-01-01

    Robots exhibit life-like behavior by performing intelligent actions. To enhance human-robot interaction it is necessary to investigate and understand how end-users perceive such animate behavior. In this paper, we report an experiment to investigate how people perceived different designs of robot

  9. Model reference adaptive control of flexible robots in the presence of sudden load changes

    Science.gov (United States)

    Steinvorth, Rodrigo; Kaufman, Howard; Neat, Gregory

    1991-01-01

    Direct command generator tracker based model reference adaptive control (MRAC) algorithms are applied to the dynamics for a flexible-joint arm in the presence of sudden load changes. Because of the need to satisfy a positive real condition, such MRAC procedures are designed so that a feedforward augmented output follows the reference model output, thus, resulting in an ultimately bounded rather than zero output error. Thus, modifications are suggested and tested that: (1) incorporate feedforward into the reference model's output as well as the plant's output, and (2) incorporate a derivative term into only the process feedforward loop. The results of these simulations give a response with zero steady state model following error, and thus encourage further use of MRAC for more complex flexibile robotic systems.

  10. Designing interruptive behaviors of a public environmental monitoring robot

    NARCIS (Netherlands)

    Evers, V.; de Vries, R.; Alvito, P.

    2011-01-01

    This paper reports ongoing research to inform the design of a social robot to monitor levels of pollutant gasses in the air. Next to licensed environmental agents and immobile chemical sensors, mobile technologies such as robotic agents are needed to collect complaints and smell descriptions from

  11. Spanish adaptation of the Participatory Behaviors Scale (PBS

    Directory of Open Access Journals (Sweden)

    Alejandro Magallares

    2016-04-01

    Full Text Available The aim of this study was to adapt the Participatory Behaviors Scale (PBS and validate the results for use among the Spanish population. Using snowball sampling methodology, 501 individuals from all areas of Spain were selected to participate in the study. The Participatory Behaviors Scale (PBS and questionnaires that measure a sense of community, belief in a just world and Machiavellianism were used to analyze the criterion validity of the adapted scale. A confirmatory factor analysis indicated that the items on the questionnaire fit a second-order model with four factors, which corresponded to the four dimensions proposed by the original authors, namely, disengagement, civil participation, formal political participation and activism. Additionally, it has been found that the scale is related to a sense of community, belief in a just world and Machiavellianism. In light of these results, we concluded that the questionnaire is methodologically valid and can be used by the scientific community to measure participatory behavior.

  12. The Creation of a Multi-Human, Multi-Robot Interactive Jam Session

    OpenAIRE

    Weinberg, Gil; Blosser, Brian; Mallikarjuna, Trishul; Raman, Aparna

    2009-01-01

    This paper presents an interactive and improvisational jam session, including human players and two robotic musicians. The project was developed in an effort to create novel and inspiring music through human-robot collaboration. The jam session incorporates Shimon, a newly-developed socially-interactive robotic marimba player, and Haile, a perceptual robotic percussionist developed in previous work. The paper gives an overview of the musical perception modules, adaptive improvisation modes an...

  13. Self-repairing control for damaged robotic manipulators

    International Nuclear Information System (INIS)

    Eisler, G.R.; Robinett, R.D.; Dohrmann, C.R.; Driessen, B.J.

    1997-03-01

    Algorithms have been developed allowing operation of robotic systems under damaged conditions. Specific areas addressed were optimal sensor location, adaptive nonlinear control, fault-tolerant robot design, and dynamic path-planning. A seven-degree-of-freedom, hydraulic manipulator, with fault-tolerant joint design was also constructed and tested. This report completes this project which was funded under the Laboratory Directed Research and Development program

  14. Dynamic Behavior Sequencing in a Hybrid Robot Architecture

    Science.gov (United States)

    2008-03-01

    robots to represent and execute procedures, scripts , and plans in dynamic environ- ments [24]. Ingrand et al. describe the PRS as the link between the...based language in a similar style to Java that follows a model-based programming approach. A model-based programming approach refers to embedded...refers to the angular orientation of the robot from its initial heading. Therefore, the θ parameter value of zero (0) indicates that the desired

  15. Introduction to humanoid robotics

    CERN Document Server

    Kajita, Shuuji; Harada, Kensuke; Yokoi, Kazuhito

    2014-01-01

    This book is for researchers, engineers, and students who are willing to understand how humanoid robots move and be controlled. The book starts with an overview of the humanoid robotics research history and state of the art. Then it explains the required mathematics and physics such as kinematics of multi-body system, Zero-Moment Point (ZMP) and its relationship with body motion. Biped walking control is discussed in depth, since it is one of the main interests of humanoid robotics. Various topics of the whole body motion generation are also discussed. Finally multi-body dynamics is presented to simulate the complete dynamic behavior of a humanoid robot. Throughout the book, Matlab codes are shown to test the algorithms and to help the reader´s understanding.

  16. Sensory Integration with Articulated Motion on a Humanoid Robot

    Directory of Open Access Journals (Sweden)

    J. Rojas

    2005-01-01

    Full Text Available This paper describes the integration of articulated motion with auditory and visual sensory information that enables a humanoid robot to achieve certain reflex actions that mimic those of people. Reflexes such as reach-and-grasp behavior enables the robot to learn, through experience, its own state and that of the world. A humanoid robot with binaural audio input, stereo vision, and pneumatic arms and hands exhibited tightly coupled sensory-motor behaviors in four different demonstrations. The complexity of successive demonstrations was increased to show that the reflexive sensory-motor behaviors combine to perform increasingly complex tasks. The humanoid robot executed these tasks effectively and established the groundwork for the further development of hardware and software systems, sensory-motor vector-space representations, and coupling with higher-level cognition.

  17. Model analysis of adaptive car driving behavior

    NARCIS (Netherlands)

    Wewerinke, P.H.

    1996-01-01

    This paper deals with two modeling approaches to car driving. The first one is a system theoretic approach to describe adaptive human driving behavior. The second approach utilizes neural networks. As an illustrative example the overtaking task is considered and modeled in system theoretic terms.

  18. Developing Creative Behavior in Elementary School Students with Robotics

    Science.gov (United States)

    Nemiro, Jill; Larriva, Cesar; Jawaharlal, Mariappan

    2017-01-01

    The School Robotics Initiative (SRI), a problem-based robotics program for elementary school students, was developed with the objective of reaching students early on to instill an interest in Science, Technology, Engineering, and Math disciplines. The purpose of this exploratory, observational study was to examine how the SRI fosters student…

  19. Pneumatic artificial muscle actuators for compliant robotic manipulators

    Science.gov (United States)

    Robinson, Ryan Michael

    Robotic systems are increasingly being utilized in applications that require interaction with humans. In order to enable safe physical human-robot interaction, light weight and compliant manipulation are desirable. These requirements are problematic for many conventional actuation systems, which are often heavy, and typically use high stiffness to achieve high performance, leading to large impact forces upon collision. However, pneumatic artificial muscles (PAMs) are actuators that can satisfy these safety requirements while offering power-to-weight ratios comparable to those of conventional actuators. PAMs are extremely lightweight actuators that produce force in response to pressurization. These muscles demonstrate natural compliance, but have a nonlinear force-contraction profile that complicates modeling and control. This body of research presents solutions to the challenges associated with the implementation of PAMs as actuators in robotic manipulators, particularly with regard to modeling, design, and control. An existing PAM force balance model was modified to incorporate elliptic end geometry and a hyper-elastic constitutive relationship, dramatically improving predictions of PAM behavior at high contraction. Utilizing this improved model, two proof-of-concept PAM-driven manipulators were designed and constructed; design features included parallel placement of actuators and a tendon-link joint design. Genetic algorithm search heuristics were employed to determine an optimal joint geometry; allowing a manipulator to achieve a desired torque profile while minimizing the required PAM pressure. Performance of the manipulators was evaluated in both simulation and experiment employing various linear and nonlinear control strategies. These included output feedback techniques, such as proportional-integral-derivative (PID) and fuzzy logic, a model-based control for computed torque, and more advanced controllers, such as sliding mode, adaptive sliding mode, and

  20. Human-Like Behavior of Robot Arms: General Considerations and the Handwriting Task-Part I: Mathematical Description of Human-Like Motion: Distributed Positioning and Virtual Fatigue

    NARCIS (Netherlands)

    Potkonjak, V.; Tzafestas, S.; Kostic, D.; Djordjevic, G.

    2001-01-01

    This two-part paper is concerned with the analysis and achievement of human-like behavior by robot arms (manipulators). The analysis involves three issues: (i) the resolution of the inverse kinematics problem of redundant robots, (ii) the separation of the end-effector's motion into two components,

  1. Modelling and testing proxemic behaviour for humanoid robots

    NARCIS (Netherlands)

    Torta, E.; Cuijpers, R.H.; Juola, J.F.; Pol, van der D.

    2012-01-01

    Humanoid robots that share the same space with humans need to be socially acceptable and effective as they interact with people. In this paper we focus our attention on the definition of a behavior-based robotic architecture that (1) allows the robot to navigate safely in a cluttered and dynamically

  2. Hierarchical Motion Control for a Team of Humanoid Soccer Robots

    Directory of Open Access Journals (Sweden)

    Seung-Joon Yi

    2016-02-01

    Full Text Available Robot soccer has become an effective benchmarking problem for robotics research as it requires many aspects of robotics including perception, self localization, motion planning and distributed coordination to work in uncertain and adversarial environments. Especially with humanoid robots that lack inherent stability, a capable and robust motion controller is crucial for generating walking and kicking motions without losing balance. In this paper, we describe the details of a motion controller to control a team of humanoid soccer robots, which consists of a hierarchy of controllers with different time frames and abstraction levels. A low level controller governs the real time control of each joint angle, either using target joint angles or target endpoint transforms. A mid-level controller handles bipedal locomotion and balancing of the robot. A high level controller decides the long term behavior of the robot, and finally the team level controller coordinates the behavior of a group of robots by means of asynchronous communication between the robots. The suggested motion system has been successfully used by many humanoid robot teams at the RoboCup international robot soccer competitions, which has awarded us five successful championships in a row.

  3. 4th International Conference on Robot Intelligence Technology and Applications

    CERN Document Server

    Karray, Fakhri; Jo, Jun; Sincak, Peter; Myung, Hyun

    2017-01-01

    This book covers all aspects of robot intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving researchers and practitioners with a timely dissemination of the recent progress on robot intelligence technology and its applications, based on a collection of papers presented at the 4th International Conference on Robot Intelligence Technology and Applications (RiTA), held in Bucheon, Korea, December 14 - 16, 2015. For better readability, this edition has the total of 49 article...

  4. 3rd International Conference on Robot Intelligence Technology and Applications

    CERN Document Server

    Yang, Weimin; Jo, Jun; Sincak, Peter; Myung, Hyun

    2015-01-01

    This book covers all aspects of robot intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving researchers and practitioners with a timely dissemination of the recent progress on robot intelligence technology and its applications, based on a collection of papers presented at the 3rd International Conference on Robot Intelligence Technology and Applications (RiTA), held in Beijing, China, November 6 - 8, 2014. For better readability, this edition has the total 74 papers group...

  5. Mobile Robots for Hospital Logistics

    DEFF Research Database (Denmark)

    Özkil, Ali Gürcan

    services to maintain the quality of healthcare provided. Logistics is the most resource demanding service in a hospital. The scale of the transportation tasks is huge and the material flow in a hospital is comparable to that of a factory. We believe that these transportation tasks, to a great extent, can...... be and will be automated using mobile robots. This talk consequently addresses the key technical issues of implementing service robots in hospitals. In simple terms, a robotic system for automating hospital logistics has to be reliable, adaptable and scalable. Robots have to be semi-autonomous, and should reliably...... navigate in large and dynamic environments in the hospital. The complexity of the problem has to be manageable, and the solutions have to be flexible, so that the system can be applicable in real world settings. This talk summarizes the efforts to address these issues. Upon the analysis...

  6. Recognition of flow in everyday life using sensor agent robot with laser range finder

    Science.gov (United States)

    Goshima, Misa; Mita, Akira

    2011-04-01

    In the present paper, we suggest an algorithm for a sensor agent robot with a laser range finder to recognize the flows of residents in the living spaces in order to achieve flow recognition in the living spaces, recognition of the number of people in spaces, and the classification of the flows. House reform is or will be demanded to prolong the lifetime of the home. Adaption for the individuals is needed for our aging society which is growing at a rapid pace. Home autonomous mobile robots will become popular in the future for aged people to assist them in various situations. Therefore we have to collect various type of information of human and living spaces. However, a penetration in personal privacy must be avoided. It is essential to recognize flows in everyday life in order to assist house reforms and aging societies in terms of adaption for the individuals. With background subtraction, extra noise removal, and the clustering based k-means method, we got an average accuracy of more than 90% from the behavior from 1 to 3 persons, and also confirmed the reliability of our system no matter the position of the sensor. Our system can take advantages from autonomous mobile robots and protect the personal privacy. It hints at a generalization of flow recognition methods in the living spaces.

  7. R and D on robots for nuclear power plants in 'advanced robot technology' project

    International Nuclear Information System (INIS)

    Ando, Hiroaki

    1987-01-01

    The project aims at developing a safe man-robot system of high mobility and workability, highly adaptable to the working environment, and readily and reliably remote-controlled. The plan is to develop 'multi-purpose robots' that can do monitoring, inspection and light work quickly and correctly in areas where access of humans is difficult (e.g. hot spots and the inner space of the primary containment vessel), and 'robots used exclusively for valves, pumps, and other equipment, multi-functional to be used only for specific purposes'. This can be expected to be completed on the basis of results in research and development for the multi-purpose robots. R and D on the total system means manufacturing an optimum system with sufficient functions and performance required for the robot by combining existing technologies most adequately on the basis of the results of research and development on the project. After conceptual drawing and conceptual design, the system will be manufactured and demonstration tests will be completed by fiscal 1987 or 1988. This report describes the total image of the robots concerning the shape, locomotion, manipulation, perception, communication, control management, reliability and environmental durability, and then outlines the research and development activities regarding locomotion, manipulator, tectile sensor, actuator, single-eye three-dimensional measurement, visual data processing, optical spacial transmission, failure repair controller, functional reduction, robot health care and radiation resistance. (Nogami, K.)

  8. Morphology Independent Learning in Modular Robots

    DEFF Research Database (Denmark)

    Christensen, David Johan; Bordignon, Mirko; Schultz, Ulrik Pagh

    2009-01-01

    speed its modules independently and in parallel adjust their behavior based on a single global reward signal. In simulation, we study the learning strategy’s performance on different robot configurations. On the physical platform, we perform learning experiments with ATRON robots learning to move as fast...

  9. Morphology Independent Learning in Modular Robots

    DEFF Research Database (Denmark)

    Christensen, David Johan; Bordignon, Mirko; Schultz, Ulrik Pagh

    2009-01-01

    speed its modules independently and in parallel adjust their behavior based on a single global reward signal. In simulation, we study the learning strategy?s performance on different robot con?gurations. On the physical platform, we perform learning experiments with ATRON robots learning to move as fast...

  10. International Workshop and Summer School on Medical and Service Robotics

    CERN Document Server

    Bouri, Mohamed; Mondada, Francesco; Pisla, Doina; Rodic, Aleksandar; Helmer, Patrick

    2016-01-01

    Medical and Service Robotics integrate the most recent achievements in mechanics, mechatronics, computer science, haptic and teleoperation devices together with adaptive control algorithms. The book  includes topics such as surgery robotics, assist devices, rehabilitation technology, surgical instrumentation and Brain-Machine Interface (BMI) as examples for medical robotics. Autonomous cleaning, tending, logistics, surveying and rescue robots, and elderly and healthcare robots are typical examples of topics from service robotics. This is the Proceedings of the Third International Workshop on Medical and Service Robots, held in Lausanne, Switzerland in 2014. It presents an overview of current research directions and fields of interest. It is divided into three sections, namely 1) assistive and rehabilitation devices; 2) surgical robotics; and 3) educational and service robotics. Most contributions are strongly anchored on collaborations between technical and medical actors, engineers, surgeons and clinicians....

  11. Adaptive Visual Face Tracking for an Autonomous Robot

    NARCIS (Netherlands)

    van Hoof, Herke; van der Zant, Tijn; Wiering, Marco

    2011-01-01

    Perception is an essential ability for autonomous robots in non-standardized conditions. However, the appearance of objects can change between different conditions. A system visually tracking a target based on its appearance could lose its target in those cases. A tracker learning the appearance of

  12. Intelligent manipulation technique for multi-branch robotic systems

    Science.gov (United States)

    Chen, Alexander Y. K.; Chen, Eugene Y. S.

    1990-01-01

    New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

  13. Robotics in Orthopedics: A Brave New World.

    Science.gov (United States)

    Parsley, Brian S

    2018-02-16

    Future health-care projection projects a significant growth in population by 2020. Health care has seen an exponential growth in technology to address the growing population with the decreasing number of physicians and health-care workers. Robotics in health care has been introduced to address this growing need. Early adoption of robotics was limited because of the limited application of the technology, the cumbersome nature of the equipment, and technical complications. A continued improvement in efficacy, adaptability, and cost reduction has stimulated increased interest in robotic-assisted surgery. The evolution in orthopedic surgery has allowed for advanced surgical planning, precision robotic machining of bone, improved implant-bone contact, optimization of implant placement, and optimization of the mechanical alignment. The potential benefits of robotic surgery include improved surgical work flow, improvements in efficacy and reduction in surgical time. Robotic-assisted surgery will continue to evolve in the orthopedic field. Copyright © 2018 Elsevier Inc. All rights reserved.

  14. Continuum robots and underactuated grasping

    Directory of Open Access Journals (Sweden)

    N. Giri

    2011-02-01

    Full Text Available We discuss the capabilities of continuum (continuous backbone robot structures in the performance of under-actuated grasping. Continuum robots offer the potential of robust grasps over a wide variety of object classes, due to their ability to adapt their shape to interact with the environment via non-local continuum contact conditions. Furthermore, this capability can be achieved with simple, low degree of freedom hardware. However, there are practical issues which currently limit the application of continuum robots to grasping. We discuss these issues and illustrate via an experimental continuum grasping case study.

    This paper was presented at the IFToMM/ASME International Workshop on Underactuated Grasping (UG2010, 19 August 2010, Montréal, Canada.

  15. Experientally guided robots. [for planet exploration

    Science.gov (United States)

    Merriam, E. W.; Becker, J. D.

    1974-01-01

    This paper argues that an experientally guided robot is necessary to successfully explore far-away planets. Such a robot is characterized as having sense organs which receive sensory information from its environment and motor systems which allow it to interact with that environment. The sensori-motor information which it receives is organized into an experiential knowledge structure and this knowledge in turn is used to guide the robot's future actions. A summary is presented of a problem solving system which is being used as a test bed for developing such a robot. The robot currently engages in the behaviors of visual tracking, focusing down, and looking around in a simulated Martian landscape. Finally, some unsolved problems are outlined whose solutions are necessary before an experientally guided robot can be produced. These problems center around organizing the motivational and memory structure of the robot and understanding its high-level control mechanisms.

  16. Relationships to Social Robots: Towards a Triadic Analysis of Media-oriented Behavior

    Directory of Open Access Journals (Sweden)

    Joachim R. Höflich

    2013-01-01

    Full Text Available People are living in relationships not only to other people but also to media, including things and robots. As the theory of media equation suggests, people treat media as if they were real persons. This theoretical perspective is also relevant to the case of human-robot interaction. A distinctive feature of such interaction is that the relation to social robots also depends on the human likeness as an anthropomorphic perspective underlines. But people seem to prefer a certain imperfection; otherwise they feel uncanny. This paper explores the idea of robots as media and people’s relations to them. The paper argues that robots are seen not only in the context of a relationship with a medium but also as a medium that ‘mediates.’ This means that robots connect between the environment and other people, but can also divide them. The paper concludes with a proposed perspective that widens a dyadic model of human-robot-interaction towards a triadic analysis.

  17. Task-space sensory feedback control of robot manipulators

    CERN Document Server

    Cheah, Chien Chern

    2015-01-01

    This book presents recent advances in robot control theory on task space sensory feedback control of robot manipulators. By using sensory feedback information, the robot control systems are robust to various uncertainties in modelling and calibration errors of the sensors. Several sensory task space control methods that do not require exact knowledge of either kinematics or dynamics of robots, are presented. Some useful methods such as approximate Jacobian control, adaptive Jacobian control, region control and multiple task space regional feedback are included. These formulations and methods give robots a high degree of flexibility in dealing with unforeseen changes and uncertainties in its kinematics and dynamics, which is similar to human reaching movements and tool manipulation. It also leads to the solution of several long-standing problems and open issues in robot control, such as force control with constraint uncertainty, control of multi-fingered robot hand with uncertain contact points, singularity i...

  18. State Estimation for Tensegrity Robots

    Science.gov (United States)

    Caluwaerts, Ken; Bruce, Jonathan; Friesen, Jeffrey M.; Sunspiral, Vytas

    2016-01-01

    Tensegrity robots are a class of compliant robots that have many desirable traits when designing mass efficient systems that must interact with uncertain environments. Various promising control approaches have been proposed for tensegrity systems in simulation. Unfortunately, state estimation methods for tensegrity robots have not yet been thoroughly studied. In this paper, we present the design and evaluation of a state estimator for tensegrity robots. This state estimator will enable existing and future control algorithms to transfer from simulation to hardware. Our approach is based on the unscented Kalman filter (UKF) and combines inertial measurements, ultra wideband time-of-flight ranging measurements, and actuator state information. We evaluate the effectiveness of our method on the SUPERball, a tensegrity based planetary exploration robotic prototype. In particular, we conduct tests for evaluating both the robot's success in estimating global position in relation to fixed ranging base stations during rolling maneuvers as well as local behavior due to small-amplitude deformations induced by cable actuation.

  19. Learning and adaptation: neural and behavioural mechanisms behind behaviour change

    Science.gov (United States)

    Lowe, Robert; Sandamirskaya, Yulia

    2018-01-01

    This special issue presents perspectives on learning and adaptation as they apply to a number of cognitive phenomena including pupil dilation in humans and attention in robots, natural language acquisition and production in embodied agents (robots), human-robot game play and social interaction, neural-dynamic modelling of active perception and neural-dynamic modelling of infant development in the Piagetian A-not-B task. The aim of the special issue, through its contributions, is to highlight some of the critical neural-dynamic and behavioural aspects of learning as it grounds adaptive responses in robotic- and neural-dynamic systems.

  20. A real time tracking vision system and its application to robotics

    International Nuclear Information System (INIS)

    Inoue, Hirochika

    1994-01-01

    Among various sensing channels the vision is most important for making robot intelligent. If provided with a high speed visual tracking capability, the robot-environment interaction becomes dynamic instead of static, and thus the potential repertoire of robot behavior becomes very rich. For this purpose we developed a real-time tracking vision system. The fundamental operation on which our system based is the calculation of correlation between local images. Use of special chip for correlation and the multi-processor configuration enable the robot to track more than hundreds cues in full video rate. In addition to the fundamental visual performance, applications for robot behavior control are also introduced. (author)

  1. Behavior-Based Approach for the Detection of Land Mines Utilizing off the Shelf Low Cost Autonomous Robot

    Directory of Open Access Journals (Sweden)

    Abdel Ilah Nour Alshbatat

    2013-03-01

    Full Text Available Several countries all of the world are affected by landmines. The presence of mines represents a major threat to lives and causes economic problems. Currently, detecting and clearing mines demand specific expertise with special equipment. In this context, this paper offers the design and development of an intelligent controller which can control and enable the robot to detect mines by means of sensors and of processing the fused information to guide soldiers when passing landmines.  This is accomplished by broken down the overall system into two subsystems: sensor technologies and robotic device. Sensors devices include infrared distance sensor, metal detector, ultrasonic range finder, accelerometer sensor, while the structure of the robot in our case consists mainly  of a commercial  off-the-shelf  parts which  are  available  at  low  costs. The proposed controller is mainly based on creating fuzzy rules that reflect the behaviors of soldier beings in controlling a robot in a well known landmine. Simulation and experimental results are presented her to prove the efficiency of the proposed approach. The results show that the system is able to detect landmines and guide soldiers while crossing mines area.

  2. The difficulties of writing procurement specifications for robots in nuclear applications

    International Nuclear Information System (INIS)

    Moore, F.W.; Bowen, W.W.

    1986-01-01

    The commercial robots available today were developed to primarily support the automotive or electronics industries. The adaptation of these robots and the current robotic technology to handle and manufacture nuclear materials has had its problems. The operational space and maintenance constraints have special consideration. The robotic systems of today tend to not have the payload capability for nuclear applications or, if the payload is sufficient, the system is very large and has several operating and maintenance accessibility requirements. The process of specifying, purchasing, and modifying a robotic system is an expensive and time-consuming process. The procurement specification is critical to obtaining competitive quotations on robots for nuclear applications resulting in the most economical robotic system

  3. Methods in the analysis of mobile robots behavior in unstructured environment

    Science.gov (United States)

    Mondoc, Alina; Dolga, Valer; Gorie, Nina

    2012-11-01

    A mobile robot can be described as a mechatronic system that must execute an application in a working environment. From mechatronic concept, the authors highlight mechatronic system structure based on its secondary function. Mobile robot will move, either in a known environment - structured environment may be described in time by an appropriate mathematical model or in an unfamiliar environment - unstructured - the random aspects prevail. Starting from a point robot must reach a START STOP point in the context of functional constraints imposed on the one hand, the application that, on the other hand, the working environment. The authors focus their presentation on unstructured environment. In this case the evolution of mobile robot is based on obtaining information in the work environment, their processing and integration results in action strategy. Number of sensory elements used is subject to optimization parameter. Starting from a known structure of mobile robot, the authors analyze the possibility of developing a mathematical model variants mathematical contact wheel - ground. It analyzes the various types of soil and the possibility of obtaining a "signature" on it based on sensory information. Theoretical aspects of the problem are compared to experimental results obtained in robot evolution. The mathematical model of the robot system allowed the simulation environment and its evolution in comparison with the experimental results estimated.

  4. Robot Faces that Follow Gaze Facilitate Attentional Engagement and Increase Their Likeability.

    Science.gov (United States)

    Willemse, Cesco; Marchesi, Serena; Wykowska, Agnieszka

    2018-01-01

    Gaze behavior of humanoid robots is an efficient mechanism for cueing our spatial orienting, but less is known about the cognitive-affective consequences of robots responding to human directional cues. Here, we examined how the extent to which a humanoid robot (iCub) avatar directed its gaze to the same objects as our participants affected engagement with the robot, subsequent gaze-cueing, and subjective ratings of the robot's characteristic traits. In a gaze-contingent eyetracking task, participants were asked to indicate a preference for one of two objects with their gaze while an iCub avatar was presented between the object photographs. In one condition, the iCub then shifted its gaze toward the object chosen by a participant in 80% of the trials (joint condition) and in the other condition it looked at the opposite object 80% of the time (disjoint condition). Based on the literature in human-human social cognition, we took the speed with which the participants looked back at the robot as a measure of facilitated reorienting and robot-preference, and found these return saccade onset times to be quicker in the joint condition than in the disjoint condition. As indicated by results from a subsequent gaze-cueing tasks, the gaze-following behavior of the robot had little effect on how our participants responded to gaze cues. Nevertheless, subjective reports suggested that our participants preferred the iCub following participants' gaze to the one with a disjoint attention behavior, rated it as more human-like and as more likeable. Taken together, our findings show a preference for robots who follow our gaze. Importantly, such subtle differences in gaze behavior are sufficient to influence our perception of humanoid agents, which clearly provides hints about the design of behavioral characteristics of humanoid robots in more naturalistic settings.

  5. Overcoming Deception in Evolution of Cognitive Behaviors

    DEFF Research Database (Denmark)

    Lehman, Joel; Miikkulainen, Risto

    2014-01-01

    When scaling neuroevolution to complex behaviors, cognitive capabilities such as learning, communication, and memory become increasingly important. However, successfully evolving such cognitive abilities remains difficult. This paper argues that a main cause for such difficulty is deception, i.......e. evolution converges to a behavior unrelated to the desired solution. More specifically, cognitive behaviors often require accumulating neural structure that provides no immediate fitness benefit, and evolution often thus converges to non-cognitive solutions. To investigate this hypothesis, a common...... evolutionary robotics T-Maze domain is adapted in three separate ways to require agents to communicate, remember, and learn. Indicative of deception, evolution driven by objective-based fitness often converges upon simple non- cognitive behaviors. In contrast, evolution driven to explore novel behaviors, i...

  6. Low-Back Pain Patients Learn to Adapt Motor Behavior with Adverse Secondary Consequences

    NARCIS (Netherlands)

    van Dieën, Jaap H.; Flor, Herta; Hodges, Paul W.

    2017-01-01

    ABSTRACT: We hypothesize that changes in motor behavior in individuals with low-back pain are adaptations aimed at minimizing the real or perceived risk of further pain. Through reinforcement learning, pain and subsequent adaptions result in less dynamic motor behavior, leading to increased loading

  7. Behavior and adaptive functioning in adolescents with Down syndrome: specifying targets for intervention.

    Science.gov (United States)

    Jacola, Lisa M; Hickey, Francis; Howe, Steven R; Esbensen, Anna; Shear, Paula K

    2014-01-01

    Research suggests that adolescents with Down syndrome experience increased behavior problems as compared to age matched peers; however, few studies have examined how these problems relate to adaptive functioning. The primary aim of this study was to characterize behavior in a sample of adolescents with Down syndrome using two widely-used caregiver reports: the Behavioral Assessment System for Children, 2 nd Edition (BASC-2) and Child Behavioral Checklist (CBCL). The clinical utility of the BASC-2 as a measure of behavior and adaptive functioning in adolescents with Down syndrome was also examined. Fifty-two adolescents with Down syndrome between the ages of 12 and 18 (24 males) completed the Peabody Picture Vocabulary Test, 4 th Edition (PPVT-IV) as an estimate of cognitive ability. Caregivers completed the BASC-2 and the CBCL for each participant. A significant proportion of the sample was reported to demonstrate behavior problems, particularly related to attention and social participation. The profile of adaptive function was variable, with caregivers most frequently rating impairment in skills related to activities of daily living and functional communication. Caregiver ratings did not differ by gender and were not related to age or estimated cognitive ability. Caregiver ratings of attention problems on the BASC-2 accounted for a significant proportion of variance in Activities of Daily Living ( Adj R 2 = 0.30) , Leadership ( Adj R 2 = 0.30) Functional Communication ( Adj R 2 = 0.28, Adaptability ( Adj R 2 = 0.29), and Social Skills ( Adj R 2 = 0.17). Higher frequencies of symptoms related to social withdrawal added incremental predictive validity for Functional Communication, Leadership, and Social Skills. Convergent validity between the CBCL and BASC-2 was poor when compared with expectations based on the normative sample. Our results confirm and extend previous findings by describing relationships between specific behavior problems and targeted areas of

  8. Behavior and adaptive functioning in adolescents with Down syndrome: specifying targets for intervention

    Science.gov (United States)

    Jacola, Lisa M.; Hickey, Francis; Howe, Steven R.; Esbensen, Anna; Shear, Paula K.

    2016-01-01

    Background Research suggests that adolescents with Down syndrome experience increased behavior problems as compared to age matched peers; however, few studies have examined how these problems relate to adaptive functioning. The primary aim of this study was to characterize behavior in a sample of adolescents with Down syndrome using two widely-used caregiver reports: the Behavioral Assessment System for Children, 2nd Edition (BASC-2) and Child Behavioral Checklist (CBCL). The clinical utility of the BASC-2 as a measure of behavior and adaptive functioning in adolescents with Down syndrome was also examined. Methods Fifty-two adolescents with Down syndrome between the ages of 12 and 18 (24 males) completed the Peabody Picture Vocabulary Test, 4th Edition (PPVT-IV) as an estimate of cognitive ability. Caregivers completed the BASC-2 and the CBCL for each participant. Results A significant proportion of the sample was reported to demonstrate behavior problems, particularly related to attention and social participation. The profile of adaptive function was variable, with caregivers most frequently rating impairment in skills related to activities of daily living and functional communication. Caregiver ratings did not differ by gender and were not related to age or estimated cognitive ability. Caregiver ratings of attention problems on the BASC-2 accounted for a significant proportion of variance in Activities of Daily Living (Adj R2 = 0.30), Leadership (Adj R2 = 0.30) Functional Communication (Adj R2 = 0.28, Adaptability (Adj R2 = 0.29), and Social Skills (Adj R2 = 0.17). Higher frequencies of symptoms related to social withdrawal added incremental predictive validity for Functional Communication, Leadership, and Social Skills. Convergent validity between the CBCL and BASC-2 was poor when compared with expectations based on the normative sample. Conclusion Our results confirm and extend previous findings by describing relationships between specific behavior problems

  9. Robotics Offer Newfound Surgical Capabilities

    Science.gov (United States)

    2008-01-01

    Barrett Technology Inc., of Cambridge, Massachusetts, completed three Phase II Small Business Innovation Research (SBIR) contracts with Johnson Space Center, during which the company developed and commercialized three core technologies: a robotic arm, a hand that functions atop the arm, and a motor driver to operate the robotics. Among many industry uses, recently, an adaptation of the arm has been cleared by the U.S. Food and Drug Administration (FDA) for use in a minimally invasive knee surgery procedure, where its precision control makes it ideal for inserting a very small implant.

  10. Adaptive Behavior in Young Children with Neurofibromatosis Type 1

    Directory of Open Access Journals (Sweden)

    Bonita P. Klein-Tasman

    2013-01-01

    Full Text Available Neurofibromatosis-1 is the most common single gene disorder affecting 1 in 3000. In children, it is associated not only with physical features but also with attention and learning problems. Research has identified a downward shift in intellectual functioning as well, but to date, there are no published studies about the everyday adaptive behavior of children with NF1. In this study, parental reports of adaptive behavior of 61 children with NF1 ages 3 through 8 were compared to an unaffected contrast group (n=55 that comprised siblings and community members. Significant group differences in adaptive skills were evident and were largely related to group differences in intellectual functioning. In a subsample of children with average-range intellectual functioning, group differences in parent-reported motor skills were apparent even after controlling statistically for group differences in intellectual functioning. The implications of the findings for the care of children with NF1 are discussed.

  11. Application requirements for Robotic Nursing Assistants in hospital environments

    Science.gov (United States)

    Cremer, Sven; Doelling, Kris; Lundberg, Cody L.; McNair, Mike; Shin, Jeongsik; Popa, Dan

    2016-05-01

    In this paper we report on analysis toward identifying design requirements for an Adaptive Robotic Nursing Assistant (ARNA). Specifically, the paper focuses on application requirements for ARNA, envisioned as a mobile assistive robot that can navigate hospital environments to perform chores in roles such as patient sitter and patient walker. The role of a sitter is primarily related to patient observation from a distance, and fetching objects at the patient's request, while a walker provides physical assistance for ambulation and rehabilitation. The robot will be expected to not only understand nurse and patient intent but also close the decision loop by automating several routine tasks. As a result, the robot will be equipped with sensors such as distributed pressure sensitive skins, 3D range sensors, and so on. Modular sensor and actuator hardware configured in the form of several multi-degree-of-freedom manipulators, and a mobile base are expected to be deployed in reconfigurable platforms for physical assistance tasks. Furthermore, adaptive human-machine interfaces are expected to play a key role, as they directly impact the ability of robots to assist nurses in a dynamic and unstructured environment. This paper discusses required tasks for the ARNA robot, as well as sensors and software infrastructure to carry out those tasks in the aspects of technical resource availability, gaps, and needed experimental studies.

  12. CLARAty: Challenges and Steps Toward Reusable Robotic Software

    Directory of Open Access Journals (Sweden)

    Richard Madison

    2008-11-01

    Full Text Available We present in detail some of the challenges in developing reusable robotic software. We base that on our experience in developing the CLARAty robotics software, which is a generic object-oriented framework used for the integration of new algorithms in the areas of motion control, vision, manipulation, locomotion, navigation, localization, planning and execution. CLARAty was adapted to a number of heterogeneous robots with different mechanisms and hardware control architectures. In this paper, we also describe how we addressed some of these challenges in the development of the CLARAty software.

  13. CLARAty: Challenges and Steps toward Reusable Robotic Software

    Directory of Open Access Journals (Sweden)

    Issa A.D. Nesnas

    2006-03-01

    Full Text Available We present in detail some of the challenges in developing reusable robotic software. We base that on our experience in developing the CLARAty robotics software, which is a generic object-oriented framework used for the integration of new algorithms in the areas of motion control, vision, manipulation, locomotion, navigation, localization, planning and execution. CLARAty was adapted to a number of heterogeneous robots with different mechanisms and hardware control architectures. In this paper, we also describe how we addressed some of these challenges in the development of the CLARAty software.

  14. Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas

    Science.gov (United States)

    Sanfeliu, Alberto; Andrade-Cetto, Juan; Barbosa, Marco; Bowden, Richard; Capitán, Jesús; Corominas, Andreu; Gilbert, Andrew; Illingworth, John; Merino, Luis; Mirats, Josep M.; Moreno, Plínio; Ollero, Aníbal; Sequeira, João; Spaan, Matthijs T.J.

    2010-01-01

    In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted. PMID:22294927

  15. The Dominant Robot: Threatening Robots Cause Psychological Reactance, Especially When They Have Incongruent Goals

    Science.gov (United States)

    Roubroeks, M. A. J.; Ham, J. R. C.; Midden, C. J. H.

    Persuasive technology can take the form of a social agent that persuades people to change behavior or attitudes. However, like any persuasive technology, persuasive social agents might trigger psychological reactance, which can lead to restoration behavior. The current study investigated whether interacting with a persuasive robot can cause psychological reactance. Additionally, we investigated whether goal congruency plays a role in psychological reactance. Participants programmed a washing machine while a robot gave threatening advice. Confirming expectations, participants experienced more psychological reactance when receiving high-threatening advice compared to low-threatening advice. Moreover, when the robot gave high-threatening advice and expressed an incongruent goal, participants reported the highest level of psychological reactance (on an anger measure). Finally, high-threatening advice led to more restoration, and this relationship was partially mediated by psychological reactance. Overall, results imply that under certain circumstances persuasive technology can trigger opposite effects, especially when people have incongruent goal intentions.

  16. A Web-Based Integration Procedure for the Development of Reconfigurable Robotic Work-Cells

    Directory of Open Access Journals (Sweden)

    Paulo Ferreira

    2013-07-01

    Full Text Available Concepts related to the development of reconfigurable manufacturing systems (RMS and methodologies to provide the best practices in the processing industry and factory automation, such as system integration and web-based technology, are major issues in designing next-generation manufacturing systems (NGMS. Adaptable and integrable devices are crucial for the success of NGMS. In robotic cells the integration of manufacturing components is essential to accelerate system adaptability. Sensors, control architectures and communication technologies have contributed to achieving further agility in reconfigurable factories. In this work a web-based robotic cell integration procedure is proposed to aid the identification of reconfigurable issues and requirements. This methodology is applied to an industrial robot manipulator to enhance system flexibility towards the development of a reconfigurable robotic platform.

  17. Approaches to probabilistic model learning for mobile manipulation robots

    CERN Document Server

    Sturm, Jürgen

    2013-01-01

    Mobile manipulation robots are envisioned to provide many useful services both in domestic environments as well as in the industrial context. Examples include domestic service robots that implement large parts of the housework, and versatile industrial assistants that provide automation, transportation, inspection, and monitoring services. The challenge in these applications is that the robots have to function under changing, real-world conditions, be able to deal with considerable amounts of noise and uncertainty, and operate without the supervision of an expert. This book presents novel learning techniques that enable mobile manipulation robots, i.e., mobile platforms with one or more robotic manipulators, to autonomously adapt to new or changing situations. The approaches presented in this book cover the following topics: (1) learning the robot's kinematic structure and properties using actuation and visual feedback, (2) learning about articulated objects in the environment in which the robot is operating,...

  18. Adaptive Colour Feature Identification in Image for Object Tracking

    Directory of Open Access Journals (Sweden)

    Feng Su

    2012-01-01

    Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

  19. Intelligent control and cooperation for mobile robots

    Science.gov (United States)

    Stingu, Petru Emanuel

    The topic discussed in this work addresses the current research being conducted at the Automation & Robotics Research Institute in the areas of UAV quadrotor control and heterogenous multi-vehicle cooperation. Autonomy can be successfully achieved by a robot under the following conditions: the robot has to be able to acquire knowledge about the environment and itself, and it also has to be able to reason under uncertainty. The control system must react quickly to immediate challenges, but also has to slowly adapt and improve based on accumulated knowledge. The major contribution of this work is the transfer of the ADP algorithms from the purely theoretical environment to the complex real-world robotic platforms that work in real-time and in uncontrolled environments. Many solutions are adopted from those present in nature because they have been proven to be close to optimal in very different settings. For the control of a single platform, reinforcement learning algorithms are used to design suboptimal controllers for a class of complex systems that can be conceptually split in local loops with simpler dynamics and relatively weak coupling to the rest of the system. Optimality is enforced by having a global critic but the curse of dimensionality is avoided by using local actors and intelligent pre-processing of the information used for learning the optimal controllers. The system model is used for constructing the structure of the control system, but on top of that the adaptive neural networks that form the actors use the knowledge acquired during normal operation to get closer to optimal control. In real-world experiments, efficient learning is a strong requirement for success. This is accomplished by using an approximation of the system model to focus the learning for equivalent configurations of the state space. Due to the availability of only local data for training, neural networks with local activation functions are implemented. For the control of a formation

  20. The Robot Path Planning Based on Improved Artificial Fish Swarm Algorithm

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2016-01-01

    Full Text Available Path planning is critical to the efficiency and fidelity of robot navigation. The solution of robot path planning is to seek a collision-free and the shortest path from the start node to target node. In this paper, we propose a new improved artificial fish swarm algorithm (IAFSA to process the mobile robot path planning problem in a real environment. In IAFSA, an attenuation function is introduced to improve the visual of standard AFSA and get the balance of global search and local search; also, an adaptive operator is introduced to enhance the adaptive ability of step. Besides, a concept of inertia weight factor is proposed in IAFSA inspired by PSO intelligence algorithm to improve the convergence rate and accuracy of IAFSA. Five unconstrained optimization test functions are given to illustrate the strong searching ability and ideal convergence of IAFSA. Finally, the ROS (robot operation system based experiment is carried out on a Pioneer 3-DX mobile robot; the experiment results also show the superiority of IAFSA.

  1. Adaptive Behavior and Development of Infants and Toddlers with Williams Syndrome

    Directory of Open Access Journals (Sweden)

    Rebecca M. Kirchner

    2016-04-01

    Full Text Available Williams syndrome (WS is a neurodevelopmental disorder that causes deficits in adaptive behavior, difficulties eating and sleeping, cognitive delays, and delayed development. Although researchers have conducted characterizations of children and adults with WS, less is known about young children with this disorder. This study characterizes the developmental and adaptive behavior features of 16 infants and toddlers with WS aged 3 months - 5 years. Data for this project was obtained from 2007-2014, and includes parent report data and standardized developmental testing. Thirty-one percent (31.3% of parents reported that their infant/toddler with WS had sleeping problems and 58.3% reported feeding difficulties. Levels of adaptive behavior were in the Mildly Delayed range as measured by the Adaptive Behavior Assessment System, Second Edition. Self care skills such as feeding or dressing oneself were significantly weaker than skills needed to function in the community, such as recognizing his/her home or throwing away trash. The difficulty with self-care skills is hypothesized to be related to the reported difficulties with eating and sleeping. Motor skills were significantly lower than both cognitive and language skills on the Bayley Scales of Infant and Toddler Development, Third Edition. The current study highlights the need for early intervention in these young children across all areas of development, particularly in self-care skills.

  2. Controlling Tensegrity Robots Through Evolution

    Science.gov (United States)

    Iscen, Atil; Agogino, Adrian; SunSpiral, Vytas; Tumer, Kagan

    2013-01-01

    Tensegrity structures (built from interconnected rods and cables) have the potential to offer a revolutionary new robotic design that is light-weight, energy-efficient, robust to failures, capable of unique modes of locomotion, impact tolerant, and compliant (reducing damage between the robot and its environment). Unfortunately robots built from tensegrity structures are difficult to control with traditional methods due to their oscillatory nature, nonlinear coupling between components and overall complexity. Fortunately this formidable control challenge can be overcome through the use of evolutionary algorithms. In this paper we show that evolutionary algorithms can be used to efficiently control a ball-shaped tensegrity robot. Experimental results performed with a variety of evolutionary algorithms in a detailed soft-body physics simulator show that a centralized evolutionary algorithm performs 400 percent better than a hand-coded solution, while the multi-agent evolution performs 800 percent better. In addition, evolution is able to discover diverse control solutions (both crawling and rolling) that are robust against structural failures and can be adapted to a wide range of energy and actuation constraints. These successful controls will form the basis for building high-performance tensegrity robots in the near future.

  3. A Comparison of Adaptive Behaviors among Mentally Retarded and Normal Individuals: A guide to Prevention and Treatment

    Directory of Open Access Journals (Sweden)

    Leyla Sadros

    2010-01-01

    Full Text Available Objectives: Because of the importance of adaptive behaviors in socialand domestic lives, this study aimed at a comparison of various domainsof adaptive behaviors, between mentally retarded and normalindividuals.Methods: A number of 246 normal and 74 mentally retarded individuals(7-18 years of age, mean: 12±3.5 years, participated this study inTehran, Iran. Their adaptive behaviors scores, were obtained using"Adaptive Behavioral Scale, Residential & Community" (ABS-RC: 2,consisting of 18 domains of behavior. The scale was first translatedinto Persian by the professionals and then retranslated into English byanother translator, to ensure content non-distortion.Results: The following domains were significantly lower in mentallyretarded than in normal individuals: independent functioning, economicactivity, language development, number & time, prevocational/vocational activity, self direction, responsibility, socialization,disturbing interpersonal behavior, domestic activity, social engagement,conformity and trustworthiness. No significant difference was documentedin the physical development, stereotype & hyperactive behaviors,sexual behavior as well as self abuse behavior domains, betweenthe two groups.Conclusions: As mentally deficient subjects did worse than normalones in terms of many adaptive behavioral domains, it implies that theadaptive behavioral issues in such people might need a great deal ofattention and intervention. For these retarded people to function betterin their social and residential environment, it would be necessary todevelop their adaptive behaviors. This study may shed light on theimportance of attention to the adaptive behavioral domains of mentallyretarded people and also indicates the necessity of preventive measures,even for normal individuals.

  4. Adaptive control of penetration and joint following for robotic GTA welding

    International Nuclear Information System (INIS)

    Bahram Mir Sadeghi; Hishamuddin Jamaludin; Iskandar Baharin

    1997-01-01

    A statistical-based method for adaptive control of weld pool penetration and joint following in Tungsten Inert Gas Welding as an approach to process and trajectory control of robotic GTA welding has been designed and simulated. Welding process parameters such as: base current and time, pulse current and time, electrode tip to work piece distance, filler travelling speed, torch speed and work piece thickness were used for finding the equations which describe the interrelationship between the aforementioned variables and penetration depth as well as bead width. The calculation of these equations was developed from the statistical regression analysis of 80 welds deposited using various combinations of welding parameters. For monitoring of the work piece thickness variations, an ultrasonic device was used. In order to control the weld trajectory, a CCD camera was also used. The results showed that the misalignment of the progressive heat affected zone which is adjacent to the weld puddle can be detected, and used for control of the weld trajectory. Also, it was found that scanning of a certain region of the captured image in front of the weld puddle decreases the data processing time drastically

  5. Intuitive adaptive orientation control of assistive robots for people living with upper limb disabilities.

    Science.gov (United States)

    Vu, Dinh-Son; Allard, Ulysse Cote; Gosselin, Clement; Routhier, Francois; Gosselin, Benoit; Campeau-Lecours, Alexandre

    2017-07-01

    Robotic assistive devices enhance the autonomy of individuals living with physical disabilities in their day-to-day life. Although the first priority for such devices is safety, they must also be intuitive and efficient from an engineering point of view in order to be adopted by a broad range of users. This is especially true for assistive robotic arms, as they are used for the complex control tasks of daily living. One challenge in the control of such assistive robots is the management of the end-effector orientation which is not always intuitive for the human operator, especially for neophytes. This paper presents a novel orientation control algorithm designed for robotic arms in the context of human-robot interaction. This work aims at making the control of the robot's orientation easier and more intuitive for the user, in particular, individuals living with upper limb disabilities. The performance and intuitiveness of the proposed orientation control algorithm is assessed through two experiments with 25 able-bodied subjects and shown to significantly improve on both aspects.

  6. Variability in Adaptive Behavior in Autism: Evidence for the Importance of Family History

    Science.gov (United States)

    Mazefsky, Carla A.; Williams, Diane L.; Minshew, Nancy J.

    2008-01-01

    Adaptive behavior in autism is highly variable and strongly related to prognosis. This study explored family history as a potential source of variability in adaptive behavior in autism. Participants included 77 individuals (mean age = 18) with average or better intellectual ability and autism. Parents completed the Family History Interview about…

  7. Adaptive-Repetitive Visual-Servo Control of Low-Flying Aerial Robots via Uncalibrated High-Flying Cameras

    Science.gov (United States)

    Guo, Dejun; Bourne, Joseph R.; Wang, Hesheng; Yim, Woosoon; Leang, Kam K.

    2017-08-01

    This paper presents the design and implementation of an adaptive-repetitive visual-servo control system for a moving high-flying vehicle (HFV) with an uncalibrated camera to monitor, track, and precisely control the movements of a low-flying vehicle (LFV) or mobile ground robot. Applications of this control strategy include the use of high-flying unmanned aerial vehicles (UAVs) with computer vision for monitoring, controlling, and coordinating the movements of lower altitude agents in areas, for example, where GPS signals may be unreliable or nonexistent. When deployed, a remote operator of the HFV defines the desired trajectory for the LFV in the HFV's camera frame. Due to the circular motion of the HFV, the resulting motion trajectory of the LFV in the image frame can be periodic in time, thus an adaptive-repetitive control system is exploited for regulation and/or trajectory tracking. The adaptive control law is able to handle uncertainties in the camera's intrinsic and extrinsic parameters. The design and stability analysis of the closed-loop control system is presented, where Lyapunov stability is shown. Simulation and experimental results are presented to demonstrate the effectiveness of the method for controlling the movement of a low-flying quadcopter, demonstrating the capabilities of the visual-servo control system for localization (i.e.,, motion capturing) and trajectory tracking control. In fact, results show that the LFV can be commanded to hover in place as well as track a user-defined flower-shaped closed trajectory, while the HFV and camera system circulates above with constant angular velocity. On average, the proposed adaptive-repetitive visual-servo control system reduces the average RMS tracking error by over 77% in the image plane and over 71% in the world frame compared to using just the adaptive visual-servo control law.

  8. Robot Faces that Follow Gaze Facilitate Attentional Engagement and Increase Their Likeability

    Science.gov (United States)

    Willemse, Cesco; Marchesi, Serena; Wykowska, Agnieszka

    2018-01-01

    Gaze behavior of humanoid robots is an efficient mechanism for cueing our spatial orienting, but less is known about the cognitive–affective consequences of robots responding to human directional cues. Here, we examined how the extent to which a humanoid robot (iCub) avatar directed its gaze to the same objects as our participants affected engagement with the robot, subsequent gaze-cueing, and subjective ratings of the robot’s characteristic traits. In a gaze-contingent eyetracking task, participants were asked to indicate a preference for one of two objects with their gaze while an iCub avatar was presented between the object photographs. In one condition, the iCub then shifted its gaze toward the object chosen by a participant in 80% of the trials (joint condition) and in the other condition it looked at the opposite object 80% of the time (disjoint condition). Based on the literature in human–human social cognition, we took the speed with which the participants looked back at the robot as a measure of facilitated reorienting and robot-preference, and found these return saccade onset times to be quicker in the joint condition than in the disjoint condition. As indicated by results from a subsequent gaze-cueing tasks, the gaze-following behavior of the robot had little effect on how our participants responded to gaze cues. Nevertheless, subjective reports suggested that our participants preferred the iCub following participants’ gaze to the one with a disjoint attention behavior, rated it as more human-like and as more likeable. Taken together, our findings show a preference for robots who follow our gaze. Importantly, such subtle differences in gaze behavior are sufficient to influence our perception of humanoid agents, which clearly provides hints about the design of behavioral characteristics of humanoid robots in more naturalistic settings. PMID:29459842

  9. Robot Faces that Follow Gaze Facilitate Attentional Engagement and Increase Their Likeability

    Directory of Open Access Journals (Sweden)

    Cesco Willemse

    2018-02-01

    Full Text Available Gaze behavior of humanoid robots is an efficient mechanism for cueing our spatial orienting, but less is known about the cognitive–affective consequences of robots responding to human directional cues. Here, we examined how the extent to which a humanoid robot (iCub avatar directed its gaze to the same objects as our participants affected engagement with the robot, subsequent gaze-cueing, and subjective ratings of the robot’s characteristic traits. In a gaze-contingent eyetracking task, participants were asked to indicate a preference for one of two objects with their gaze while an iCub avatar was presented between the object photographs. In one condition, the iCub then shifted its gaze toward the object chosen by a participant in 80% of the trials (joint condition and in the other condition it looked at the opposite object 80% of the time (disjoint condition. Based on the literature in human–human social cognition, we took the speed with which the participants looked back at the robot as a measure of facilitated reorienting and robot-preference, and found these return saccade onset times to be quicker in the joint condition than in the disjoint condition. As indicated by results from a subsequent gaze-cueing tasks, the gaze-following behavior of the robot had little effect on how our participants responded to gaze cues. Nevertheless, subjective reports suggested that our participants preferred the iCub following participants’ gaze to the one with a disjoint attention behavior, rated it as more human-like and as more likeable. Taken together, our findings show a preference for robots who follow our gaze. Importantly, such subtle differences in gaze behavior are sufficient to influence our perception of humanoid agents, which clearly provides hints about the design of behavioral characteristics of humanoid robots in more naturalistic settings.

  10. Iterative design process for robots with personality

    NARCIS (Netherlands)

    Meerbeek, B.W.; Saerbeck, M.; Bartneck, C.; Dautenhahn, K.

    2009-01-01

    Previous research has shown that autonomous robots tend to induce the perception of a personality through their behavior and appearance. It has therefore been suggested that the personality of a robot can be used as a design guideline. A welldefined and clearly communicated personality can serve as

  11. A multitasking behavioral control system for the Robotic All Terrain Lunar Exploration Rover (RATLER)

    Science.gov (United States)

    Klarer, P.

    1994-01-01

    An alternative methodology for designing an autonomous navigation and control system is discussed. This generalized hybrid system is based on a less sequential and less anthropomorphic approach than that used in the more traditional artificial intelligence (AI) technique. The architecture is designed to allow both synchronous and asynchronous operations between various behavior modules. This is accomplished by intertask communications channels which implement each behavior module and each interconnection node as a stand-alone task. The proposed design architecture allows for construction of hybrid systems which employ both subsumption and traditional AI techniques as well as providing for a teleoperator's interface. Implementation of the architecture is planned for the prototype Robotic All Terrain Lunar Explorer Rover (RATLER) which is described briefly.

  12. Static aeroelastic behavior of an adaptive laminated piezoelectric composite wing

    Science.gov (United States)

    Weisshaar, T. A.; Ehlers, S. M.

    1990-01-01

    The effect of using an adaptive material to modify the static aeroelastic behavior of a uniform wing is examined. The wing structure is idealized as a laminated sandwich structure with piezoelectric layers in the upper and lower skins. A feedback system that senses the wing root loads applies a constant electric field to the piezoelectric actuator. Modification of pure torsional deformaton behavior and pure bending deformation are investigated, as is the case of an anisotropic composite swept wing. The use of piezoelectric actuators to create an adaptive structure is found to alter static aeroelastic behavior in that the proper choice of the feedback gain can increase or decrease the aeroelastic divergence speed. This concept also may be used to actively change the lift effectiveness of a wing. The ability to modify static aeroelastic behavior is limited by physical limitations of the piezoelectric material and the manner in which it is integrated into the parent structure.

  13. Robot Deception and Squirrel Behavior: A Case Study in Bio-inspired Robotics

    Science.gov (United States)

    2014-08-01

    soccer , and handball (Brault, Bideau, Craig, & Kkulpa, 2010; Dessing & Craig, 2010; Vignais, Kulpa, Craig, Brault, Multon, & Bideau, 2010...Robots , 1 (1), 27-52. Barnes, J. A. (1994). A pack of lies: Towards a sociology of lying. . Cambridge University press. Baron-Cohen, S. (2007). I

  14. Fish and robot dancing together: bluefin killifish females respond differently to the courtship of a robot with varying color morphs.

    Science.gov (United States)

    Phamduy, P; Polverino, G; Fuller, R C; Porfiri, M

    2014-09-01

    The experimental integration of bioinspired robots in groups of social animals has become a valuable tool to understand the basis of social behavior and uncover the fundamental determinants of animal communication. In this study, we measured the preference of fertile female bluefin killifish (Lucania goodei) for robotic replicas whose aspect ratio, body size, motion pattern, and color morph were inspired by adult male killifish. The motion of the fish replica was controlled via a robotic platform, which simulated the typical courtship behavior observed in killifish males. The positional preferences of females were measured for three different color morphs (red, yellow, and blue). While variation in preference was high among females, females tend to spend more time in the vicinity of the yellow painted robot replicas. This preference may have emerged because the yellow robot replicas were very bright, particularly in the longer wavelengths (550–700 nm) compared to the red and blue replicas. These findings are in agreement with previous observations in mosquitofish and zebrafish on fish preference for artificially enhanced yellow pigmentation.

  15. Fish and robot dancing together: bluefin killifish females respond differently to the courtship of a robot with varying color morphs

    International Nuclear Information System (INIS)

    Phamduy, P; Polverino, G; Porfiri, M; Fuller, R C

    2014-01-01

    The experimental integration of bioinspired robots in groups of social animals has become a valuable tool to understand the basis of social behavior and uncover the fundamental determinants of animal communication. In this study, we measured the preference of fertile female bluefin killifish (Lucania goodei) for robotic replicas whose aspect ratio, body size, motion pattern, and color morph were inspired by adult male killifish. The motion of the fish replica was controlled via a robotic platform, which simulated the typical courtship behavior observed in killifish males. The positional preferences of females were measured for three different color morphs (red, yellow, and blue). While variation in preference was high among females, females tend to spend more time in the vicinity of the yellow painted robot replicas. This preference may have emerged because the yellow robot replicas were very bright, particularly in the longer wavelengths (550–700 nm) compared to the red and blue replicas. These findings are in agreement with previous observations in mosquitofish and zebrafish on fish preference for artificially enhanced yellow pigmentation. (paper)

  16. Decentralized Sensor Fusion for Ubiquitous Networking Robotics in Urban Areas

    Directory of Open Access Journals (Sweden)

    Aníbal Ollero

    2010-03-01

    Full Text Available In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites, a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted.

  17. Unibot, a Universal Agent Architecture for Robots

    Directory of Open Access Journals (Sweden)

    Saša Mladenović

    2017-01-01

    Full Text Available Today there are numerous robots in different applications domains despite the fact that they still have limitations in perception, actuation and decision process. Consequently, robots usually have limited autonomy, they are domain specific or have difficulty to adapt on new environments. Learning is the property that makes an agent intelligent and the crucial property that a robot should have to proliferate into the human society. Embedding the learning ability into the robot may simplify the development of the robot control mechanism. The motivation for this research is to develop the agent architecture of the universal robot – Unibot. In our approach the agent is the robot i.e. Unibot that acts in the physical world and is capable of learning. The Unibot conducts several simultaneous simulations of a problem of interest like path-finding. The novelty in our approach is the Multi-Agent Decision Support System which is developed and integrated into the Unibot agent architecture in order to execute simultaneous simulations. Furthermore, the Unibot calculates and evaluates between multiple solutions, decides which action should be performed and performs the action. The prototype of the Unibot agent architecture is described and evaluated in the experiment supported by the Lego Mindstorms robot and the NetLogo.

  18. Where do people look when tutoring a robot?

    DEFF Research Database (Denmark)

    Lohan, Katrin Solveig; Fischer, Kerstin; Dondrup, Christian

    In this paper, we investigate the relationship between tutors' gaze behavior and particular kinds of linguistic behaviors. In particular, we describe how word classes are distributed over different gazing classes. For this, we collected data from human-robot interactions and used a classification......). The analysis shows that there are, for instance, more object related keywords when people are gazing at an object, and more personal pronouns when people are looking at the robot. Understanding the relationship between human tutors' linguistic and gazing behavior can facilitate bootstrapping the one capability...

  19. Empowerment As Replacement for the Three Laws of Robotics

    Directory of Open Access Journals (Sweden)

    Christoph Salge

    2017-06-01

    Full Text Available The greater ubiquity of robots creates a need for generic guidelines for robot behavior. We focus less on how a robot can technically achieve a predefined goal and more on what a robot should do in the first place. Particularly, we are interested in the question how a heuristic should look like, which motivates the robot’s behavior in interaction with human agents. We make a concrete, operational proposal as to how the information-theoretic concept of empowerment can be used as a generic heuristic to quantify concepts, such as self-preservation, protection of the human partner, and responding to human actions. While elsewhere we studied involved single-agent scenarios in detail, here, we present proof-of-principle scenarios demonstrating how empowerment interpreted in light of these perspectives allows one to specify core concepts with a similar aim as Asimov’s Three Laws of Robotics in an operational way. Importantly, this route does not depend on having to establish an explicit verbalized understanding of human language and conventions in the robots. Also, it incorporates the ability to take into account a rich variety of different situations and types of robotic embodiment.

  20. Piezoresistive pressure sensor array for robotic skin

    Science.gov (United States)

    Mirza, Fahad; Sahasrabuddhe, Ritvij R.; Baptist, Joshua R.; Wijesundara, Muthu B. J.; Lee, Woo H.; Popa, Dan O.

    2016-05-01

    Robots are starting to transition from the confines of the manufacturing floor to homes, schools, hospitals, and highly dynamic environments. As, a result, it is impossible to foresee all the probable operational situations of robots, and preprogram the robot behavior in those situations. Among human-robot interaction technologies, haptic communication is an intuitive physical interaction method that can help define operational behaviors for robots cooperating with humans. Multimodal robotic skin with distributed sensors can help robots increase perception capabilities of their surrounding environments. Electro-Hydro-Dynamic (EHD) printing is a flexible multi-modal sensor fabrication method because of its direct printing capability of a wide range of materials onto substrates with non-uniform topographies. In past work we designed interdigitated comb electrodes as a sensing element and printed piezoresistive strain sensors using customized EHD printable PEDOT:PSS based inks. We formulated a PEDOT:PSS derivative ink, by mixing PEDOT:PSS and DMSO. Bending induced characterization tests of prototyped sensors showed high sensitivity and sufficient stability. In this paper, we describe SkinCells, robot skin sensor arrays integrated with electronic modules. 4x4 EHD-printed arrays of strain sensors was packaged onto Kapton sheets and silicone encapsulant and interconnected to a custom electronic module that consists of a microcontroller, Wheatstone bridge with adjustable digital potentiometer, multiplexer, and serial communication unit. Thus, SkinCell's electronics can be used for signal acquisition, conditioning, and networking between sensor modules. Several SkinCells were loaded with controlled pressure, temperature and humidity testing apparatuses, and testing results are reported in this paper.

  1. A neural network-based exploratory learning and motor planning system for co-robots

    Directory of Open Access Journals (Sweden)

    Byron V Galbraith

    2015-07-01

    Full Text Available Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or learning by doing, an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

  2. A neural network-based exploratory learning and motor planning system for co-robots.

    Science.gov (United States)

    Galbraith, Byron V; Guenther, Frank H; Versace, Massimiliano

    2015-01-01

    Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or "learning by doing," an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

  3. Soft segmented inchworm robot with dielectric elastomer muscles

    Science.gov (United States)

    Conn, Andrew T.; Hinitt, Andrew D.; Wang, Pengchuan

    2014-03-01

    Robotic devices typically utilize rigid components in order to produce precise and robust operation. Rigidity becomes a significant impediment, however, when navigating confined or constricted environments e.g. search-and-rescue, industrial pipe inspection. In such cases adaptively conformable soft structures become optimal. Dielectric elastomers (DEs) are well suited for developing such soft robots since they are inherently compliant and can produce large musclelike actuation strains. In this paper, a soft segmented inchworm robot is presented that utilizes pneumatically-coupled DE membranes to produce inchworm-like locomotion. The robot is constructed from repeated body segments, each with a simple control architecture, so that the total length can be readily adapted by adding or removing segments. Each segment consists of a soft inflatable shell (internal pressure in range of 1.0-15.9 mBar) and a pair of antagonistic DE membranes (VHB 4905). Experimental testing of a single body segment is presented and the relationship between drive voltage, pneumatic pressure and active displacement is characterized. This demonstrates that pneumatic coupling of DE membranes induces complex non-linear electro-mechanical behaviour as drive voltage and pneumatic pressure are altered. Locomotion of a two-segment inchworm robot prototype with a passive length of 80 mm is presented. Artificial setae are included on the body shell to generate anisotropic friction for locomotion. A maximum locomotion speed of 4.1 mm/s was recorded at a drive frequency of 1.5 Hz, which compares favourably to biological counterparts. Future development of the soft inchworm robot are discussed including reflexive low-level control of individual segments.

  4. Planning and decision making for aerial robots

    CERN Document Server

    Bestaoui Sebbane, Yasmina

    2014-01-01

    This book provides an introduction to the emerging field of planning and decision making for aerial robots. An aerial robot is the ultimate form of Unmanned Aerial Vehicle, an aircraft endowed with built-in intelligence, requiring no direct human control and able to perform a specific task. It must be able to fly within a partially structured environment, to react and adapt to changing environmental conditions and to accommodate for the uncertainty that exists in the physical world. An aerial robot can be termed as a physical agent that exists and flies in the real 3D world, can sense its environment and act on it to achieve specific goals. So throughout this book, an aerial robot will also be termed as an agent.   Fundamental problems in aerial robotics include the tasks of spatial motion, spatial sensing and spatial reasoning. Reasoning in complex environments represents a difficult problem. The issues specific to spatial reasoning are planning and decision making. Planning deals with the trajectory algori...

  5. Help-Giving Robot Behaviors in Child-Robot Games : Exploring Semantic Free Utterances

    NARCIS (Netherlands)

    Zaga, Cristina; De Vries, Roelof A.J.; Spenkelink, Sem J.; Truong, Khiet P.; Evers, Vanessa

    We present initial findings from an experiment where we used Semantic Free Utterances vocalizations and sounds without semantic content as an alternative to Natural Language in a child-robot collaborative game. We tested (i) if two types of Semantic Free Utterances could be accurately recognized by

  6. Image-guided robotic surgery.

    Science.gov (United States)

    Marescaux, Jacques; Solerc, Luc

    2004-06-01

    Medical image processing leads to an improvement in patient care by guiding the surgical gesture. Three-dimensional models of patients that are generated from computed tomographic scans or magnetic resonance imaging allow improved surgical planning and surgical simulation that offers the opportunity for a surgeon to train the surgical gesture before performing it for real. These two preoperative steps can be used intra-operatively because of the development of augmented reality, which consists of superimposing the preoperative three-dimensional model of the patient onto the real intraoperative view. Augmented reality provides the surgeon with a view of the patient in transparency and can also guide the surgeon, thanks to the real-time tracking of surgical tools during the procedure. When adapted to robotic surgery, this tool tracking enables visual serving with the ability to automatically position and control surgical robotic arms in three dimensions. It is also now possible to filter physiologic movements such as breathing or the heart beat. In the future, by combining augmented reality and robotics, these image-guided robotic systems will enable automation of the surgical procedure, which will be the next revolution in surgery.

  7. Ideas from Developmental Robotics and Embodied AI on the Questions of Ethics in Robots

    OpenAIRE

    Pitti , Alexandre

    2017-01-01

    Advances in Artificial Intelligence and robotics are currently questioning theethical framework of their applications to deal with potential drifts, as well as the way inwhich these algorithms learn because they will have a strong impact on the behavior ofrobots and the type of robots. interactions with people. We would like to highlight someprinciples and ideas from cognitive neuroscience and development sciences based on theimportance of the body for intelligence, contrary to the theory of ...

  8. Ideas from Developmental Robotics and Embodied AI on the Questions of Ethics in Robots

    OpenAIRE

    Pitti, Alexandre

    2018-01-01

    Advances in Artificial Intelligence and robotics are currently questioning theethical framework of their applications to deal with potential drifts, as well as the way inwhich these algorithms learn because they will have a strong impact on the behavior ofrobots and the type of robots. interactions with people. We would like to highlight someprinciples and ideas from cognitive neuroscience and development sciences based on theimportance of the body for intelligence, contrary to the theory of ...

  9. Reservoir-based Online Adaptive Forward Models with Neural Control for Complex Locomotion in a Hexapod Robot

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Dasgupta, Sakyasingha; Goldschmidt, Dennis

    2014-01-01

    Walking animals show fascinating locomotor abilities and complex behaviors. Biological study has revealed that such complex behaviors is a result of a combination of biomechanics and neural mechanisms. While biomechanics allows for flexibility and a variety of movements, neural mechanisms generate...... locomotion, make predictions, and provide adaptation. Inspired by this finding, we present here an artificial bio-inspired walking system which combines biomechanics (in terms of its body and leg structures) and neural mechanisms. The neural mechanisms consist of 1) central pattern generator-based control...... for generating basic rhythmic patterns and coordinated movements, 2) reservoir-based adaptive forward models with efference copies for sensory prediction as well as state estimation, and 3) searching and elevation control for adapting the movement of an individual leg to deal with different environmental...

  10. SLAM algorithm applied to robotics assistance for navigation in unknown environments

    Directory of Open Access Journals (Sweden)

    Lobo Pereira Fernando

    2010-02-01

    Full Text Available Abstract Background The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous. The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI. Methods In this paper, a sequential Extended Kalman Filter (EKF feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. Results The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how

  11. Applying commercial robotic technology to radioactive material processing

    International Nuclear Information System (INIS)

    Grasz, E.L.; Sievers, R.H. Jr.

    1991-01-01

    The development of robotic systems to automate nuclear material processing in glove boxes is motivated by the need to reduce operator radiation exposure, minimize the generation of process waste, and to improve security of nuclear materials. Commercial robotic systems can furnish the needed manipulation capabilities by are not readily compatible with the glove box environment and physical restrictions. Alpha radiation, concentrated dust, a dry atmosphere and restricted work space require unique adaptations of commercial robotics. Tradeoffs between meeting desired functional capabilities and extensive customization are necessary. The reported design and development efforts include evaluating the feasibility of using a commercial gantry robot for glove box pyrochemical and smelting operations. This paper presents the initial results and observations for this development effort

  12. A Service-Oriented Framework for the Development of Home Robots

    Directory of Open Access Journals (Sweden)

    Tsung-Hsien Yang

    2013-02-01

    Full Text Available In recent years, researchers have been building home robots able to interact and work with people. Yet, because of the complicated and independent robot development environments, it is not always easy to share and reuse robot code created by different providers. In this work, we present an ontology-based framework that integrates service-oriented computing environments with the standard web interface to develop reusable robotic services. In addition to the service discovery, selection, and composition processes often performed by traditional web services, our work also includes an adaptive mechanism through which the user can iteratively modify composite robotic services to suit his or her needs. The proposed methodology has been implemented and evaluated, and the results show that our framework can be used to build robotic services successfully.

  13. 2nd International Conference on Robot Intelligence Technology and Applications

    CERN Document Server

    Matson, Eric; Myung, Hyun; Xu, Peter; Karray, Fakhri

    2014-01-01

    We are facing a new technological challenge on how to store and retrieve knowledge and manipulate intelligence for autonomous services by intelligent systems which should be capable of carrying out real world tasks autonomously. To address this issue, robot researchers have been developing intelligence technology (InT) for “robots that think” which is in the focus of this book. The book covers all aspects of intelligence from perception at sensor level and reasoning at cognitive level to behavior planning at execution level for each low level segment of the machine. It also presents the technologies for cognitive reasoning, social interaction with humans, behavior generation, ability to cooperate with other robots, ambience awareness, and an artificial genome that can be passed on to other robots. These technologies are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The book aims at serving resear...

  14. A Domain-Specific Language for Programming Self-Reconfigurable Robots

    DEFF Research Database (Denmark)

    Schultz, Ulrik Pagh; Christensen, David Johan; Støy, Kasper

    2007-01-01

    . Programming a modular, self-reconfigurable robot is however a complicated task: the robot is essentially a real-time, distributed embedded system, where control and communication paths often are tightly coupled to the current physical configuration of the robot. To facilitate the task of programming modular......, self-reconfigurable robots, we have developed a declarative, role-based language that allows the programmer to define roles and behavior independently of the concrete physical structure of the robot. Roles are compiled to mobile code fragments that distribute themselves over the physical structure...

  15. Morphology Independent Learning in Modular Robots

    DEFF Research Database (Denmark)

    Christensen, David Johan; Bordignon, Mirko; Schultz, Ulrik Pagh

    2009-01-01

    Hand-coding locomotion controllers for modular robots is difficult due to their polymorphic nature. Instead, we propose to use a simple and distributed reinforcement learning strategy. ATRON modules with identical controllers can be assembled in any configuration. To optimize the robot’s locomotion...... speed its modules independently and in parallel adjust their behavior based on a single global reward signal. In simulation, we study the learning strategy’s performance on different robot configurations. On the physical platform, we perform learning experiments with ATRON robots learning to move as fast...

  16. See You See Me: the Role of Eye Contact in Multimodal Human-Robot Interaction

    Science.gov (United States)

    XU, TIAN (LINGER); ZHANG, HUI; YU, CHEN

    2016-01-01

    We focus on a fundamental looking behavior in human-robot interactions – gazing at each other’s face. Eye contact and mutual gaze between two social partners are critical in smooth human-human interactions. Therefore, investigating at what moments and in what ways a robot should look at a human user’s face as a response to the human’s gaze behavior is an important topic. Toward this goal, we developed a gaze-contingent human-robot interaction system, which relied on momentary gaze behaviors from a human user to control an interacting robot in real time. Using this system, we conducted an experiment in which human participants interacted with the robot in a joint attention task. In the experiment, we systematically manipulated the robot’s gaze toward the human partner’s face in real time and then analyzed the human’s gaze behavior as a response to the robot’s gaze behavior. We found that more face looks from the robot led to more look-backs (to the robot’s face) from human participants and consequently created more mutual gaze and eye contact between the two. Moreover, participants demonstrated more coordinated and synchronized multimodal behaviors between speech and gaze when more eye contact was successfully established and maintained. PMID:28966875

  17. Brain-behavioral adaptability predicts response to cognitive behavioral therapy for emotional disorders: A person-centered event-related potential study.

    Science.gov (United States)

    Stange, Jonathan P; MacNamara, Annmarie; Kennedy, Amy E; Hajcak, Greg; Phan, K Luan; Klumpp, Heide

    2017-06-23

    Single-trial-level analyses afford the ability to link neural indices of elaborative attention (such as the late positive potential [LPP], an event-related potential) with downstream markers of attentional processing (such as reaction time [RT]). This approach can provide useful information about individual differences in information processing, such as the ability to adapt behavior based on attentional demands ("brain-behavioral adaptability"). Anxiety and depression are associated with maladaptive information processing implicating aberrant cognition-emotion interactions, but whether brain-behavioral adaptability predicts response to psychotherapy is not known. We used a novel person-centered, trial-level analysis approach to link neural indices of stimulus processing to behavioral responses and to predict treatment outcome. Thirty-nine patients with anxiety and/or depression received 12 weeks of cognitive behavioral therapy (CBT). Prior to treatment, patients performed a speeded reaction-time task involving briefly-presented pairs of aversive and neutral pictures while electroencephalography was recorded. Multilevel modeling demonstrated that larger LPPs predicted slower responses on subsequent trials, suggesting that increased attention to the task-irrelevant nature of pictures interfered with reaction time on subsequent trials. Whereas using LPP and RT averages did not distinguish CBT responders from nonresponders, in trial-level analyses individuals who demonstrated greater ability to benefit behaviorally (i.e., faster RT) from smaller LPPs on the previous trial (greater brain-behavioral adaptability) were more likely to respond to treatment and showed greater improvements in depressive symptoms. These results highlight the utility of trial-level analyses to elucidate variability in within-subjects, brain-behavioral attentional coupling in the context of emotion processing, in predicting response to CBT for emotional disorders. Copyright © 2017 Elsevier Ltd

  18. Flocking and rendezvous in distributed robotics

    CERN Document Server

    Francis, Bruce A

    2016-01-01

    This brief describes the coordinated control of groups of robots using only sensory input – and no direct external commands. Furthermore, each robot employs the same local strategy, i.e., there are no leaders, and the text also deals with decentralized control, allowing for cases in which no single robot can sense all the others. One can get intuition for the problem from the natural world, for example, flocking birds. How do they achieve and maintain their flying formation? Recognizing their importance as the most basic coordination tasks for mobile robot networks, the brief details flocking and rendezvous. They are shown to be physical illustrations of emergent behaviors with global consensus arising from local interactions. The authors extend the consideration of these fundamental ideas to describe their operation in flying robots and prompt readers to pursue further research in the field.  Flocking and Rendezvous in Distributed Robotics will provide graduate students a firm grounding in the subject, w...

  19. Autonomous mobile robot for radiologic surveys

    International Nuclear Information System (INIS)

    Dudar, A.M.; Wagner, D.G.; Teese, G.D.

    1994-01-01

    An apparatus is described for conducting radiologic surveys. The apparatus comprises in the main a robot capable of following a preprogrammed path through an area, a radiation monitor adapted to receive input from a radiation detector assembly, ultrasonic transducers for navigation and collision avoidance, and an on-board computer system including an integrator for interfacing the radiation monitor and the robot. Front and rear bumpers are attached to the robot by bumper mounts. The robot may be equipped with memory boards for the collection and storage of radiation survey information. The on-board computer system is connected to a remote host computer via a UHF radio link. The apparatus is powered by a rechargeable 24-volt DC battery, and is stored at a docking station when not in use and/or for recharging. A remote host computer contains a stored database defining paths between points in the area where the robot is to operate, including but not limited to the locations of walls, doors, stationary furniture and equipment, and sonic markers if used. When a program consisting of a series of paths is downloaded to the on-board computer system, the robot conducts a floor survey autonomously at any preselected rate. When the radiation monitor detects contamination, the robot resurveys the area at reduced speed and resumes its preprogrammed path if the contamination is not confirmed. If the contamination is confirmed, the robot stops and sounds an alarm. 5 figures

  20. Formal-Language-Theoretic Control & Coordination of Mobile Robots

    National Research Council Canada - National Science Library

    Ray, Asok

    2007-01-01

    .... The research has formulated and experimentally validated robust adaptive algorithms and software codes for decision and control of mobile robotic platforms, as applied to real-time computation...