A multimodal interface for real-time soldier-robot teaming

Science.gov (United States)

Barber, Daniel J.; Howard, Thomas M.; Walter, Matthew R.

2016-05-01

Recent research and advances in robotics have led to the development of novel platforms leveraging new sensing capabilities for semantic navigation. As these systems becoming increasingly more robust, they support highly complex commands beyond direct teleoperation and waypoint finding facilitating a transition away from robots as tools to robots as teammates. Supporting future Soldier-Robot teaming requires communication capabilities on par with human-human teams for successful integration of robots. Therefore, as robots increase in functionality, it is equally important that the interface between the Soldier and robot advances as well. Multimodal communication (MMC) enables human-robot teaming through redundancy and levels of communications more robust than single mode interaction. Commercial-off-the-shelf (COTS) technologies released in recent years for smart-phones and gaming provide tools for the creation of portable interfaces incorporating MMC through the use of speech, gestures, and visual displays. However, for multimodal interfaces to be successfully used in the military domain, they must be able to classify speech, gestures, and process natural language in real-time with high accuracy. For the present study, a prototype multimodal interface supporting real-time interactions with an autonomous robot was developed. This device integrated COTS Automated Speech Recognition (ASR), a custom gesture recognition glove, and natural language understanding on a tablet. This paper presents performance results (e.g. response times, accuracy) of the integrated device when commanding an autonomous robot to perform reconnaissance and surveillance activities in an unknown outdoor environment.

Human-Robot Teaming for Hydrologic Data Gathering at Multiple Scales

Science.gov (United States)

Peschel, J.; Young, S. N.

2017-12-01

The use of personal robot-assistive technology by researchers and practitioners for hydrologic data gathering has grown in recent years as barriers to platform capability, cost, and human-robot interaction have been overcome. One consequence to this growth is a broad availability of unmanned platforms that might or might not be suitable for a specific hydrologic investigation. Through multiple field studies, a set of recommendations has been developed to help guide novice through experienced users in choosing the appropriate unmanned platforms for a given application. This talk will present a series of hydrologic data sets gathered using a human-robot teaming approach that has leveraged unmanned aerial, ground, and surface vehicles over multiple scales. The field case studies discussed will be connected to the best practices, also provided in the presentation. This talk will be of interest to geoscience researchers and practitioners, in general, as well as those working in fields related to emerging technologies.

Collaborative Tools for Mixed Teams of Humans and Robots

National Research Council Canada - National Science Library

Bruemmer, David J; Walton, Miles C

2003-01-01

.... Our approach has been to consider the air vehicles, ground robots and humans as team members with different levels of authority, different communication, processing, power and mobility capabilities...

Human-Robot Interaction: Status and Challenges.

Science.gov (United States)

Sheridan, Thomas B

2016-06-01

The current status of human-robot interaction (HRI) is reviewed, and key current research challenges for the human factors community are described. Robots have evolved from continuous human-controlled master-slave servomechanisms for handling nuclear waste to a broad range of robots incorporating artificial intelligence for many applications and under human supervisory control. This mini-review describes HRI developments in four application areas and what are the challenges for human factors research. In addition to a plethora of research papers, evidence of success is manifest in live demonstrations of robot capability under various forms of human control. HRI is a rapidly evolving field. Specialized robots under human teleoperation have proven successful in hazardous environments and medical application, as have specialized telerobots under human supervisory control for space and repetitive industrial tasks. Research in areas of self-driving cars, intimate collaboration with humans in manipulation tasks, human control of humanoid robots for hazardous environments, and social interaction with robots is at initial stages. The efficacy of humanoid general-purpose robots has yet to be proven. HRI is now applied in almost all robot tasks, including manufacturing, space, aviation, undersea, surgery, rehabilitation, agriculture, education, package fetch and delivery, policing, and military operations. © 2016, Human Factors and Ergonomics Society.

User localization during human-robot interaction.

Science.gov (United States)

Alonso-Martín, F; Gorostiza, Javi F; Malfaz, María; Salichs, Miguel A

2012-01-01

This paper presents a user localization system based on the fusion of visual information and sound source localization, implemented on a social robot called Maggie. One of the main requisites to obtain a natural interaction between human-human and human-robot is an adequate spatial situation between the interlocutors, that is, to be orientated and situated at the right distance during the conversation in order to have a satisfactory communicative process. Our social robot uses a complete multimodal dialog system which manages the user-robot interaction during the communicative process. One of its main components is the presented user localization system. To determine the most suitable allocation of the robot in relation to the user, a proxemic study of the human-robot interaction is required, which is described in this paper. The study has been made with two groups of users: children, aged between 8 and 17, and adults. Finally, at the end of the paper, experimental results with the proposed multimodal dialog system are presented.

Compliance control based on PSO algorithm to improve the feeling during physical human-robot interaction.

Science.gov (United States)

Jiang, Zhongliang; Sun, Yu; Gao, Peng; Hu, Ying; Zhang, Jianwei

2016-01-01

Robots play more important roles in daily life and bring us a lot of convenience. But when people work with robots, there remain some significant differences in human-human interactions and human-robot interaction. It is our goal to make robots look even more human-like. We design a controller which can sense the force acting on any point of a robot and ensure the robot can move according to the force. First, a spring-mass-dashpot system was used to describe the physical model, and the second-order system is the kernel of the controller. Then, we can establish the state space equations of the system. In addition, the particle swarm optimization algorithm had been used to obtain the system parameters. In order to test the stability of system, the root-locus diagram had been shown in the paper. Ultimately, some experiments had been carried out on the robotic spinal surgery system, which is developed by our team, and the result shows that the new controller performs better during human-robot interaction.

Interaction debugging : an integral approach to analyze human-robot interaction

NARCIS (Netherlands)

Kooijmans, T.; Kanda, T.; Bartneck, C.; Ishiguro, H.; Hagita, N.

2006-01-01

Along with the development of interactive robots, controlled experiments and field trials are regularly conducted to stage human-robot interaction. Experience in this field has shown that analyzing human-robot interaction for evaluation purposes fosters the development of improved systems and the

Robotic situational awareness of actions in human teaming

Science.gov (United States)

Tahmoush, Dave

2015-06-01

When robots can sense and interpret the activities of the people they are working with, they become more of a team member and less of just a piece of equipment. This has motivated work on recognizing human actions using existing robotic sensors like short-range ladar imagers. These produce three-dimensional point cloud movies which can be analyzed for structure and motion information. We skeletonize the human point cloud and apply a physics-based velocity correlation scheme to the resulting joint motions. The twenty actions are then recognized using a nearest-neighbors classifier that achieves good accuracy.

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...

Ontological Reasoning for Human-Robot Teaming in Search and Rescue Missions

NARCIS (Netherlands)

Bagosi, T.; Hindriks, k.V.; Neerincx, M.A.

2016-01-01

In search and rescue missions robots are used to help rescue workers in exploring the disaster site. Our research focuses on how multiple robots and rescuers act as a team, and build up situation awareness. We propose a multi-agent system where each agent supports one member, either human or robot.

Human Robot Interaction for Hybrid Collision Avoidance System for Indoor Mobile Robots

Directory of Open Access Journals (Sweden)

Mazen Ghandour

2017-06-01

Full Text Available In this paper, a novel approach for collision avoidance for indoor mobile robots based on human-robot interaction is realized. The main contribution of this work is a new technique for collision avoidance by engaging the human and the robot in generating new collision-free paths. In mobile robotics, collision avoidance is critical for the success of the robots in implementing their tasks, especially when the robots navigate in crowded and dynamic environments, which include humans. Traditional collision avoidance methods deal with the human as a dynamic obstacle, without taking into consideration that the human will also try to avoid the robot, and this causes the people and the robot to get confused, especially in crowded social places such as restaurants, hospitals, and laboratories. To avoid such scenarios, a reactive-supervised collision avoidance system for mobile robots based on human-robot interaction is implemented. In this method, both the robot and the human will collaborate in generating the collision avoidance via interaction. The person will notify the robot about the avoidance direction via interaction, and the robot will search for the optimal collision-free path on the selected direction. In case that no people interacted with the robot, it will select the navigation path autonomously and select the path that is closest to the goal location. The humans will interact with the robot using gesture recognition and Kinect sensor. To build the gesture recognition system, two models were used to classify these gestures, the first model is Back-Propagation Neural Network (BPNN, and the second model is Support Vector Machine (SVM. Furthermore, a novel collision avoidance system for avoiding the obstacles is implemented and integrated with the HRI system. The system is tested on H20 robot from DrRobot Company (Canada and a set of experiments were implemented to report the performance of the system in interacting with the human and avoiding

Human-Robot Interaction in High Vulnerability Domains

Science.gov (United States)

Gore, Brian F.

2016-01-01

Future NASA missions will require successful integration of the human with highly complex systems. Highly complex systems are likely to involve humans, automation, and some level of robotic assistance. The complex environments will require successful integration of the human with automation, with robots, and with human-automation-robot teams to accomplish mission critical goals. Many challenges exist for the human performing in these types of operational environments with these kinds of systems. Systems must be designed to optimally integrate various levels of inputs and outputs based on the roles and responsibilities of the human, the automation, and the robots; from direct manual control, shared human-robotic control, or no active human control (i.e. human supervisory control). It is assumed that the human will remain involved at some level. Technologies that vary based on contextual demands and on operator characteristics (workload, situation awareness) will be needed when the human integrates into these systems. Predictive models that estimate the impact of the technologies on the system performance and the on the human operator are also needed to meet the challenges associated with such future complex human-automation-robot systems in extreme environments.

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.

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.

Human-Robot Teams Informed by Human Performance Moderator Functions

Science.gov (United States)

2012-08-29

performance factors that affect the ability of a human to drive at night, which includes the eyesight of the driver, the fatigue level of the driver...where human factors are factors that affect the performance of an individual. 7 for human interaction. For instance, they explain the various human... affecting trust in human-robot interaction. Human Factors 53(5), 517-527 (2001) 35. Hart, S. G. and Staveland, L. E. Development of NASA-TLX (Task

Accelerating Robot Development through Integral Analysis of Human-Robot Interaction

NARCIS (Netherlands)

Kooijmans, T.; Kanda, T.; Bartneck, C.; Ishiguro, H.; Hagita, N.

2007-01-01

The development of interactive robots is a complicated process, involving a plethora of psychological, technical, and contextual influences. To design a robot capable of operating "intelligently" in everyday situations, one needs a profound understanding of human-robot interaction (HRI). We propose

Human-Robot Interaction Directed Research Project

Science.gov (United States)

Rochlis, Jennifer; Ezer, Neta; Sandor, Aniko

2011-01-01

Human-robot interaction (HRI) is about understanding and shaping the interactions between humans and robots (Goodrich & Schultz, 2007). It is important to evaluate how the design of interfaces and command modalities affect the human s ability to perform tasks accurately, efficiently, and effectively (Crandall, Goodrich, Olsen Jr., & Nielsen, 2005) It is also critical to evaluate the effects of human-robot interfaces and command modalities on operator mental workload (Sheridan, 1992) and situation awareness (Endsley, Bolt , & Jones, 2003). By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed that support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for design. Because the factors associated with interfaces and command modalities in HRI are too numerous to address in 3 years of research, the proposed research concentrates on three manageable areas applicable to National Aeronautics and Space Administration (NASA) robot systems. These topic areas emerged from the Fiscal Year (FY) 2011 work that included extensive literature reviews and observations of NASA systems. The three topic areas are: 1) video overlays, 2) camera views, and 3) command modalities. Each area is described in detail below, along with relevance to existing NASA human-robot systems. In addition to studies in these three topic areas, a workshop is proposed for FY12. The workshop will bring together experts in human-robot interaction and robotics to discuss the state of the practice as applicable to research in space robotics. Studies proposed in the area of video overlays consider two factors in the implementation of augmented reality (AR) for operator displays during teleoperation. The first of these factors is the type of navigational guidance provided by AR symbology. In the proposed

Pantomimic gestures for human-robot interaction

CSIR Research Space (South Africa)

Burke, Michael G

2015-10-01

Full Text Available -1 IEEE TRANSACTIONS ON ROBOTICS 1 Pantomimic Gestures for Human-Robot Interaction Michael Burke, Student Member, IEEE, and Joan Lasenby Abstract This work introduces a pantomimic gesture interface, which classifies human hand gestures using...

Safe physical human robot interaction- past, present and future

International Nuclear Information System (INIS)

Pervez, Aslam; Ryu, Jeha

2008-01-01

When a robot physically interacts with a human user, the requirements should be drastically changed. The most important requirement is the safety of the human user in the sense that robot should not harm the human in any situation. During the last few years, research has been focused on various aspects of safe physical human robot interaction. This paper provides a review of the work on safe physical interaction of robotic systems sharing their workspace with human users (especially elderly people). Three distinct areas of research are identified: interaction safety assessment, interaction safety through design, and interaction safety through planning and control. The paper then highlights the current challenges and available technologies and points out future research directions for realization of a safe and dependable robotic system for human users

Effect of cognitive biases on human-robot interaction: a case study of robot's misattribution

OpenAIRE

Biswas, Mriganka; Murray, John

2014-01-01

This paper presents a model for developing long-term human-robot interactions and social relationships based on the principle of 'human' cognitive biases applied to a robot. The aim of this work is to study how a robot influenced with human ‘misattribution’ helps to build better human-robot interactions than unbiased robots. The results presented in this paper suggest that it is important to know the effect of cognitive biases in human characteristics and interactions in order to better u...

Designing, developing, and deploying systems to support human-robot teams in disaster response

NARCIS (Netherlands)

Kruijff, G.J.M.; Kruijff-Korbayová, I.; Keshavdas, S.; Larochelle, B.; Janíček, M.; Colas, F.; Liu, M.; Pomerleau, F.; Siegwart, R.; Neerincx, M.A.; Looije, R.; Smets, N.J.J.M.; Mioch, T.; Diggelen, J. van; Pirri, F.; Gianni, M.; Ferri, F.; Menna, M.; Worst, R.; Linder, T.; Tretyakov, V.; Surmann, H.; Svoboda, T.; Reinštein, M.; Zimmermann, K.; Petříček, T.; Hlaváč, V.

2014-01-01

This paper describes our experience in designing, developing and deploying systems for supporting human-robot teams during disaster response. It is based on R&D performed in the EU-funded project NIFTi. NIFTi aimed at building intelligent, collaborative robots that could work together with humans in

A Human-Robot Interaction Perspective on Assistive and Rehabilitation Robotics.

Science.gov (United States)

Beckerle, Philipp; Salvietti, Gionata; Unal, Ramazan; Prattichizzo, Domenico; Rossi, Simone; Castellini, Claudio; Hirche, Sandra; Endo, Satoshi; Amor, Heni Ben; Ciocarlie, Matei; Mastrogiovanni, Fulvio; Argall, Brenna D; Bianchi, Matteo

2017-01-01

Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing, and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human-robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed. Options to provide sensory user feedback that are currently missing from robotic devices are outlined. Parallels between device acceptance and affective computing are made. Furthermore, requirements for functional assessment protocols that relate to real-world tasks are discussed. In all topic areas, the design of human-oriented frameworks and methods is dominated by challenges related to the close interaction between the human and robotic device. This paper discusses the aforementioned aspects in order to open up new perspectives for future robotic solutions.

Towards quantifying dynamic human-human physical interactions for robot assisted stroke therapy.

Science.gov (United States)

Mohan, Mayumi; Mendonca, Rochelle; Johnson, Michelle J

2017-07-01

Human-Robot Interaction is a prominent field of robotics today. Knowledge of human-human physical interaction can prove vital in creating dynamic physical interactions between human and robots. Most of the current work in studying this interaction has been from a haptic perspective. Through this paper, we present metrics that can be used to identify if a physical interaction occurred between two people using kinematics. We present a simple Activity of Daily Living (ADL) task which involves a simple interaction. We show that we can use these metrics to successfully identify interactions.

Toward a framework for levels of robot autonomy in human-robot interaction.

Science.gov (United States)

Beer, Jenay M; Fisk, Arthur D; Rogers, Wendy A

2014-07-01

A critical construct related to human-robot interaction (HRI) is autonomy, which varies widely across robot platforms. Levels of robot autonomy (LORA), ranging from teleoperation to fully autonomous systems, influence the way in which humans and robots may interact with one another. Thus, there is a need to understand HRI by identifying variables that influence - and are influenced by - robot autonomy. Our overarching goal is to develop a framework for levels of robot autonomy in HRI. To reach this goal, the framework draws links between HRI and human-automation interaction, a field with a long history of studying and understanding human-related variables. The construct of autonomy is reviewed and redefined within the context of HRI. Additionally, the framework proposes a process for determining a robot's autonomy level, by categorizing autonomy along a 10-point taxonomy. The framework is intended to be treated as guidelines to determine autonomy, categorize the LORA along a qualitative taxonomy, and consider which HRI variables (e.g., acceptance, situation awareness, reliability) may be influenced by the LORA.

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.

Interaction Challenges in Human-Robot Space Exploration

Science.gov (United States)

Fong, Terrence; Nourbakhsh, Illah

2005-01-01

In January 2004, NASA established a new, long-term exploration program to fulfill the President's Vision for U.S. Space Exploration. The primary goal of this program is to establish a sustained human presence in space, beginning with robotic missions to the Moon in 2008, followed by extended human expeditions to the Moon as early as 2015. In addition, the program places significant emphasis on the development of joint human-robot systems. A key difference from previous exploration efforts is that future space exploration activities must be sustainable over the long-term. Experience with the space station has shown that cost pressures will keep astronaut teams small. Consequently, care must be taken to extend the effectiveness of these astronauts well beyond their individual human capacity. Thus, in order to reduce human workload, costs, and fatigue-driven error and risk, intelligent robots will have to be an integral part of mission design.

An Integrated Human System Interaction (HSI) Framework for Human-Agent Team Collaboration, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — As space missions become more complex and as mission demands increase, robots, human-robot mixed initiative teams and software autonomy applications are needed to...

Context-Augmented Robotic Interaction Layer (CARIL), Phase II

Data.gov (United States)

National Aeronautics and Space Administration — CHI Systems and the Institute for Human Machine Cognition have teamed to create a human-robot interaction system that leverages cognitive representations of shared...

Human-Robot Interaction Directed Research Project

Science.gov (United States)

Sandor, Aniko; Cross, Ernest V., II; Chang, Mai Lee

2014-01-01

Human-robot interaction (HRI) is a discipline investigating the factors affecting the interactions between humans and robots. It is important to evaluate how the design of interfaces and command modalities affect the human's ability to perform tasks accurately, efficiently, and effectively when working with a robot. By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed to appropriately support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for the design of robotic systems. This DRP concentrates on three areas associated with interfaces and command modalities in HRI which are applicable to NASA robot systems: 1) Video Overlays, 2) Camera Views, and 3) Command Modalities. The first study focused on video overlays that investigated how Augmented Reality (AR) symbology can be added to the human-robot interface to improve teleoperation performance. Three types of AR symbology were explored in this study, command guidance (CG), situation guidance (SG), and both (SCG). CG symbology gives operators explicit instructions on what commands to input, whereas SG symbology gives operators implicit cues so that operators can infer the input commands. The combination of CG and SG provided operators with explicit and implicit cues allowing the operator to choose which symbology to utilize. The objective of the study was to understand how AR symbology affects the human operator's ability to align a robot arm to a target using a flight stick and the ability to allocate attention between the symbology and external views of the world. The study evaluated the effects type of symbology (CG and SG) has on operator tasks performance and attention allocation during teleoperation of a robot arm. The second study expanded on the first study by evaluating the effects of the type of

Extending NGOMSL Model for Human-Humanoid Robot Interaction in the Soccer Robotics Domain

Directory of Open Access Journals (Sweden)

Rajesh Elara Mohan

2008-01-01

Full Text Available In the field of human-computer interaction, the Natural Goals, Operators, Methods, and Selection rules Language (NGOMSL model is one of the most popular methods for modelling knowledge and cognitive processes for rapid usability evaluation. The NGOMSL model is a description of the knowledge that a user must possess to operate the system represented as elementary actions for effective usability evaluations. In the last few years, mobile robots have been exhibiting a stronger presence in commercial markets and very little work has been done with NGOMSL modelling for usability evaluations in the human-robot interaction discipline. This paper focuses on extending the NGOMSL model for usability evaluation of human-humanoid robot interaction in the soccer robotics domain. The NGOMSL modelled human-humanoid interaction design of Robo-Erectus Junior was evaluated and the results of the experiments showed that the interaction design was able to find faults in an average time of 23.84 s. Also, the interaction design was able to detect the fault within the 60 s in 100% of the cases. The Evaluated Interaction design was adopted by our Robo-Erectus Junior version of humanoid robots in the RoboCup 2007 humanoid soccer league.

Mapping planetary caves with an autonomous, heterogeneous robot team

Science.gov (United States)

Husain, Ammar; Jones, Heather; Kannan, Balajee; Wong, Uland; Pimentel, Tiago; Tang, Sarah; Daftry, Shreyansh; Huber, Steven; Whittaker, William L.

Caves on other planetary bodies offer sheltered habitat for future human explorers and numerous clues to a planet's past for scientists. While recent orbital imagery provides exciting new details about cave entrances on the Moon and Mars, the interiors of these caves are still unknown and not observable from orbit. Multi-robot teams offer unique solutions for exploration and modeling subsurface voids during precursor missions. Robot teams that are diverse in terms of size, mobility, sensing, and capability can provide great advantages, but this diversity, coupled with inherently distinct low-level behavior architectures, makes coordination a challenge. This paper presents a framework that consists of an autonomous frontier and capability-based task generator, a distributed market-based strategy for coordinating and allocating tasks to the different team members, and a communication paradigm for seamless interaction between the different robots in the system. Robots have different sensors, (in the representative robot team used for testing: 2D mapping sensors, 3D modeling sensors, or no exteroceptive sensors), and varying levels of mobility. Tasks are generated to explore, model, and take science samples. Based on an individual robot's capability and associated cost for executing a generated task, a robot is autonomously selected for task execution. The robots create coarse online maps and store collected data for high resolution offline modeling. The coordination approach has been field tested at a mock cave site with highly-unstructured natural terrain, as well as an outdoor patio area. Initial results are promising for applicability of the proposed multi-robot framework to exploration and modeling of planetary caves.

Are You Talking to Me? Dialogue Systems Supporting Mixed Teams of Humans and Robots

Science.gov (United States)

Dowding, John; Clancey, William J.; Graham, Jeffrey

2006-01-01

This position paper describes an approach to building spoken dialogue systems for environments containing multiple human speakers and hearers, and multiple robotic speakers and hearers. We address the issue, for robotic hearers, of whether the speech they hear is intended for them, or more likely to be intended for some other hearer. We will describe data collected during a series of experiments involving teams of multiple human and robots (and other software participants), and some preliminary results for distinguishing robot-directed speech from human-directed speech. The domain of these experiments is Mars-analogue planetary exploration. These Mars-analogue field studies involve two subjects in simulated planetary space suits doing geological exploration with the help of 1-2 robots, supporting software agents, a habitat communicator and links to a remote science team. The two subjects are performing a task (geological exploration) which requires them to speak with each other while also speaking with their assistants. The technique used here is to use a probabilistic context-free grammar language model in the speech recognizer that is trained on prior robot-directed speech. Intuitively, the recognizer will give higher confidence to an utterance if it is similar to utterances that have been directed to the robot in the past.

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.

Human-robot interaction strategies for walker-assisted locomotion

CERN Document Server

Cifuentes, Carlos A

2016-01-01

This book presents the development of a new multimodal human-robot interface for testing and validating control strategies applied to robotic walkers for assisting human mobility and gait rehabilitation. The aim is to achieve a closer interaction between the robotic device and the individual, empowering the rehabilitation potential of such devices in clinical applications. A new multimodal human-robot interface for testing and validating control strategies applied to robotic walkers for assisting human mobility and gait rehabilitation is presented. Trends and opportunities for future advances in the field of assistive locomotion via the development of hybrid solutions based on the combination of smart walkers and biomechatronic exoskeletons are also discussed. .

Dynamic perceptions of human-likeness while interacting with a social robot

NARCIS (Netherlands)

Ruijten, P.A.M.; Cuijpers, R.H.

2017-01-01

In human-robot interaction research, much attention is given to the development of socially assistive robots that can have natural interactions with their users. One crucial aspect of such natural interactions is that the robot is perceived as human-like. Much research already exists that

Human-robot interaction assessment using dynamic engagement profiles

DEFF Research Database (Denmark)

Drimus, Alin; Poltorak, Nicole

2017-01-01

-1] interval, where 0 represents disengaged and 1 fully engaged. The network shows a good accuracy at recognizing the engagement state of humans given positive emotions. A time based analysis of interaction experiments between small humanoid robots and humans provides time series of engagement estimates, which...... and is applicable to humanoid robotics as well as other related contexts.......This paper addresses the use of convolutional neural networks for image analysis resulting in an engagement metric that can be used to assess the quality of human robot interactions. We propose a method based on a pretrained convolutional network able to map emotions onto a continuous [0...

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

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.

A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

OpenAIRE

Mavridis, Nikolaos

2014-01-01

In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-lookin...

Robot initiative in a team learning task increases the rhythm of interaction but not the perceived engagement

Science.gov (United States)

Ivaldi, Serena; Anzalone, Salvatore M.; Rousseau, Woody; Sigaud, Olivier; Chetouani, Mohamed

2014-01-01

We hypothesize that the initiative of a robot during a collaborative task with a human can influence the pace of interaction, the human response to attention cues, and the perceived engagement. We propose an object learning experiment where the human interacts in a natural way with the humanoid iCub. Through a two-phases scenario, the human teaches the robot about the properties of some objects. We compare the effect of the initiator of the task in the teaching phase (human or robot) on the rhythm of the interaction in the verification phase. We measure the reaction time of the human gaze when responding to attention utterances of the robot. Our experiments show that when the robot is the initiator of the learning task, the pace of interaction is higher and the reaction to attention cues faster. Subjective evaluations suggest that the initiating role of the robot, however, does not affect the perceived engagement. Moreover, subjective and third-person evaluations of the interaction task suggest that the attentive mechanism we implemented in the humanoid robot iCub is able to arouse engagement and make the robot's behavior readable. PMID:24596554

Development of Methodologies, Metrics, and Tools for Investigating Human-Robot Interaction in Space Robotics

Science.gov (United States)

Ezer, Neta; Zumbado, Jennifer Rochlis; Sandor, Aniko; Boyer, Jennifer

2011-01-01

Human-robot systems are expected to have a central role in future space exploration missions that extend beyond low-earth orbit [1]. As part of a directed research project funded by NASA s Human Research Program (HRP), researchers at the Johnson Space Center have started to use a variety of techniques, including literature reviews, case studies, knowledge capture, field studies, and experiments to understand critical human-robot interaction (HRI) variables for current and future systems. Activities accomplished to date include observations of the International Space Station s Special Purpose Dexterous Manipulator (SPDM), Robonaut, and Space Exploration Vehicle (SEV), as well as interviews with robotics trainers, robot operators, and developers of gesture interfaces. A survey of methods and metrics used in HRI was completed to identify those most applicable to space robotics. These methods and metrics included techniques and tools associated with task performance, the quantification of human-robot interactions and communication, usability, human workload, and situation awareness. The need for more research in areas such as natural interfaces, compensations for loss of signal and poor video quality, psycho-physiological feedback, and common HRI testbeds were identified. The initial findings from these activities and planned future research are discussed. Human-robot systems are expected to have a central role in future space exploration missions that extend beyond low-earth orbit [1]. As part of a directed research project funded by NASA s Human Research Program (HRP), researchers at the Johnson Space Center have started to use a variety of techniques, including literature reviews, case studies, knowledge capture, field studies, and experiments to understand critical human-robot interaction (HRI) variables for current and future systems. Activities accomplished to date include observations of the International Space Station s Special Purpose Dexterous Manipulator

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.

Peer-to-Peer Human-Robot Interaction for Space Exploration

Science.gov (United States)

Fong, Terrence; Nourbakhsh, Illah

2004-01-01

NASA has embarked on a long-term program to develop human-robot systems for sustained, affordable space exploration. To support this mission, we are working to improve human-robot interaction and performance on planetary surfaces. Rather than building robots that function as glorified tools, our focus is to enable humans and robots to work as partners and peers. In this paper. we describe our approach, which includes contextual dialogue, cognitive modeling, and metrics-based field testing.

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.

Control of a Robot Dancer for Enhancing Haptic Human-Robot Interaction in Waltz.

Science.gov (United States)

Hongbo Wang; Kosuge, K

2012-01-01

Haptic interaction between a human leader and a robot follower in waltz is studied in this paper. An inverted pendulum model is used to approximate the human's body dynamics. With the feedbacks from the force sensor and laser range finders, the robot is able to estimate the human leader's state by using an extended Kalman filter (EKF). To reduce interaction force, two robot controllers, namely, admittance with virtual force controller, and inverted pendulum controller, are proposed and evaluated in experiments. The former controller failed the experiment; reasons for the failure are explained. At the same time, the use of the latter controller is validated by experiment results.

Cooperative Robot Teams Applied to the Site Preparation Task

International Nuclear Information System (INIS)

Parker, LE

2001-01-01

Prior to human missions to Mars, infrastructures on Mars that support human survival must be prepared. robotic teams can assist in these advance preparations in a number of ways. This paper addresses one of these advance robotic team tasks--the site preparation task--by proposing a control structure that allows robot teams to cooperatively solve this aspect of infrastructure preparation. A key question in this context is determining how robots should make decisions on which aspect of the site preparation t6ask to address throughout the mission, especially while operating in rough terrains. This paper describes a control approach to solving this problem that is based upon the ALLIANCE architecture, combined with performance-based rough terrain navigation that addresses path planning and control of mobile robots in rough terrain environments. They present the site preparation task and the proposed cooperative control approach, followed by some of the results of the initial testing of various aspects of the system

Robot Tracking of Human Subjects in Field Environments

Science.gov (United States)

Graham, Jeffrey; Shillcutt, Kimberly

2003-01-01

Future planetary exploration will involve both humans and robots. Understanding and improving their interaction is a main focus of research in the Intelligent Systems Branch at NASA's Johnson Space Center. By teaming intelligent robots with astronauts on surface extra-vehicular activities (EVAs), safety and productivity can be improved. The EVA Robotic Assistant (ERA) project was established to study the issues of human-robot teams, to develop a testbed robot to assist space-suited humans in exploration tasks, and to experimentally determine the effectiveness of an EVA assistant robot. A companion paper discusses the ERA project in general, its history starting with ASRO (Astronaut-Rover project), and the results of recent field tests in Arizona. This paper focuses on one aspect of the research, robot tracking, in greater detail: the software architecture and algorithms. The ERA robot is capable of moving towards and/or continuously following mobile or stationary targets or sequences of targets. The contributions made by this research include how the low-level pose data is assembled, normalized and communicated, how the tracking algorithm was generalized and implemented, and qualitative performance reports from recent field tests.

Model-based acquisition and analysis of multimodal interactions for improving human-robot interaction

OpenAIRE

Renner, Patrick; Pfeiffer, Thies

2014-01-01

For solving complex tasks cooperatively in close interaction with robots, they need to understand natural human communication. To achieve this, robots could benefit from a deeper understanding of the processes that humans use for successful communication. Such skills can be studied by investigating human face-to-face interactions in complex tasks. In our work the focus lies on shared-space interactions in a path planning task and thus 3D gaze directions and hand movements are of particular in...

Motor contagion during human-human and human-robot interaction.

Directory of Open Access Journals (Sweden)

Ambra Bisio

Full Text Available Motor resonance mechanisms are known to affect humans' ability to interact with others, yielding the kind of "mutual understanding" that is the basis of social interaction. However, it remains unclear how the partner's action features combine or compete to promote or prevent motor resonance during interaction. To clarify this point, the present study tested whether and how the nature of the visual stimulus and the properties of the observed actions influence observer's motor response, being motor contagion one of the behavioral manifestations of motor resonance. Participants observed a humanoid robot and a human agent move their hands into a pre-specified final position or put an object into a container at various velocities. Their movements, both in the object- and non-object- directed conditions, were characterized by either a smooth/curvilinear or a jerky/segmented trajectory. These trajectories were covered with biological or non-biological kinematics (the latter only by the humanoid robot. After action observation, participants were requested to either reach the indicated final position or to transport a similar object into another container. Results showed that motor contagion appeared for both the interactive partner except when the humanoid robot violated the biological laws of motion. These findings suggest that the observer may transiently match his/her own motor repertoire to that of the observed agent. This matching might mediate the activation of motor resonance, and modulate the spontaneity and the pleasantness of the interaction, whatever the nature of the communication partner.

Motor contagion during human-human and human-robot interaction.

Science.gov (United States)

Bisio, Ambra; Sciutti, Alessandra; Nori, Francesco; Metta, Giorgio; Fadiga, Luciano; Sandini, Giulio; Pozzo, Thierry

2014-01-01

Motor resonance mechanisms are known to affect humans' ability to interact with others, yielding the kind of "mutual understanding" that is the basis of social interaction. However, it remains unclear how the partner's action features combine or compete to promote or prevent motor resonance during interaction. To clarify this point, the present study tested whether and how the nature of the visual stimulus and the properties of the observed actions influence observer's motor response, being motor contagion one of the behavioral manifestations of motor resonance. Participants observed a humanoid robot and a human agent move their hands into a pre-specified final position or put an object into a container at various velocities. Their movements, both in the object- and non-object- directed conditions, were characterized by either a smooth/curvilinear or a jerky/segmented trajectory. These trajectories were covered with biological or non-biological kinematics (the latter only by the humanoid robot). After action observation, participants were requested to either reach the indicated final position or to transport a similar object into another container. Results showed that motor contagion appeared for both the interactive partner except when the humanoid robot violated the biological laws of motion. These findings suggest that the observer may transiently match his/her own motor repertoire to that of the observed agent. This matching might mediate the activation of motor resonance, and modulate the spontaneity and the pleasantness of the interaction, whatever the nature of the communication partner.

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...

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.

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.

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...

Human-Robot Interaction

Science.gov (United States)

Rochlis-Zumbado, Jennifer; Sandor, Aniko; Ezer, Neta

2012-01-01

Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is a new Human Research Program (HRP) risk. HRI is a research area that seeks to understand the complex relationship among variables that affect the way humans and robots work together to accomplish goals. The DRP addresses three major HRI study areas that will provide appropriate information for navigation guidance to a teleoperator of a robot system, and contribute to the closure of currently identified HRP gaps: (1) Overlays -- Use of overlays for teleoperation to augment the information available on the video feed (2) Camera views -- Type and arrangement of camera views for better task performance and awareness of surroundings (3) Command modalities -- Development of gesture and voice command vocabularies

Exploring cultural factors in human-robot interaction : A matter of personality?

NARCIS (Netherlands)

Weiss, Astrid; Evers, Vanessa

2011-01-01

This paper proposes an experimental study to investigate task-dependence and cultural-background dependence of the personality trait attribution on humanoid robots. In Human-Robot Interaction, as well as in Human-Agent Interaction research, the attribution of personality traits towards intelligent

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.

Intrinsically motivated reinforcement learning for human-robot interaction in the real-world.

Science.gov (United States)

Qureshi, Ahmed Hussain; Nakamura, Yutaka; Yoshikawa, Yuichiro; Ishiguro, Hiroshi

2018-03-26

For a natural social human-robot interaction, it is essential for a robot to learn the human-like social skills. However, learning such skills is notoriously hard due to the limited availability of direct instructions from people to teach a robot. In this paper, we propose an intrinsically motivated reinforcement learning framework in which an agent gets the intrinsic motivation-based rewards through the action-conditional predictive model. By using the proposed method, the robot learned the social skills from the human-robot interaction experiences gathered in the real uncontrolled environments. The results indicate that the robot not only acquired human-like social skills but also took more human-like decisions, on a test dataset, than a robot which received direct rewards for the task achievement. Copyright © 2018 Elsevier Ltd. All rights reserved.

Simplified Human-Robot Interaction: Modeling and Evaluation

Directory of Open Access Journals (Sweden)

Balazs Daniel

2013-10-01

Full Text Available In this paper a novel concept of human-robot interaction (HRI modeling is proposed. Including factors like trust in automation, situational awareness, expertise and expectations a new user experience framework is formed for industrial robots. Service Oriented Robot Operation, proposed in a previous paper, creates an abstract level in HRI and it is also included in the framework. This concept is evaluated with exhaustive tests. Results prove that significant improvement in task execution may be achieved and the new system is more usable for operators with less experience with robotics; personnel specific for small and medium enterprises (SMEs.

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.

Muecas: A Multi-Sensor Robotic Head for Affective Human Robot Interaction and Imitation

Directory of Open Access Journals (Sweden)

Felipe Cid

2014-04-01

Full Text Available This paper presents a multi-sensor humanoid robotic head for human robot interaction. The design of the robotic head, Muecas, is based on ongoing research on the mechanisms of perception and imitation of human expressions and emotions. These mechanisms allow direct interaction between the robot and its human companion through the different natural language modalities: speech, body language and facial expressions. The robotic head has 12 degrees of freedom, in a human-like configuration, including eyes, eyebrows, mouth and neck, and has been designed and built entirely by IADeX (Engineering, Automation and Design of Extremadura and RoboLab. A detailed description of its kinematics is provided along with the design of the most complex controllers. Muecas can be directly controlled by FACS (Facial Action Coding System, the de facto standard for facial expression recognition and synthesis. This feature facilitates its use by third party platforms and encourages the development of imitation and of goal-based systems. Imitation systems learn from the user, while goal-based ones use planning techniques to drive the user towards a final desired state. To show the flexibility and reliability of the robotic head, the paper presents a software architecture that is able to detect, recognize, classify and generate facial expressions in real time using FACS. This system has been implemented using the robotics framework, RoboComp, which provides hardware-independent access to the sensors in the head. Finally, the paper presents experimental results showing the real-time functioning of the whole system, including recognition and imitation of human facial expressions.

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.

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.

Exploiting Child-Robot Aesthetic Interaction for a Social Robot

OpenAIRE

Lee, Jae-Joon; Kim, Dae-Won; Kang, Bo-Yeong

2012-01-01

A social robot interacts and communicates with humans by using the embodied knowledge gained from interactions with its social environment. In recent years, emotion has emerged as a popular concept for designing social robots. Several studies on social robots reported an increase in robot sociability through emotional imitative interactions between the robot and humans. In this paper conventional emotional interactions are extended by exploiting the aesthetic theories that the sociability of ...

Ghost-in-the-Machine reveals human social signals for human-robot interaction.

Science.gov (United States)

Loth, Sebastian; Jettka, Katharina; Giuliani, Manuel; de Ruiter, Jan P

2015-01-01

We used a new method called "Ghost-in-the-Machine" (GiM) to investigate social interactions with a robotic bartender taking orders for drinks and serving them. Using the GiM paradigm allowed us to identify how human participants recognize the intentions of customers on the basis of the output of the robotic recognizers. Specifically, we measured which recognizer modalities (e.g., speech, the distance to the bar) were relevant at different stages of the interaction. This provided insights into human social behavior necessary for the development of socially competent robots. When initiating the drink-order interaction, the most important recognizers were those based on computer vision. When drink orders were being placed, however, the most important information source was the speech recognition. Interestingly, the participants used only a subset of the available information, focussing only on a few relevant recognizers while ignoring others. This reduced the risk of acting on erroneous sensor data and enabled them to complete service interactions more swiftly than a robot using all available sensor data. We also investigated socially appropriate response strategies. In their responses, the participants preferred to use the same modality as the customer's requests, e.g., they tended to respond verbally to verbal requests. Also, they added redundancy to their responses, for instance by using echo questions. We argue that incorporating the social strategies discovered with the GiM paradigm in multimodal grammars of human-robot interactions improves the robustness and the ease-of-use of these interactions, and therefore provides a smoother user experience.

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.

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...

Interaction with Soft Robotic Tentacles

DEFF Research Database (Denmark)

Jørgensen, Jonas

2018-01-01

Soft robotics technology has been proposed for a number of applications that involve human-robot interaction. In this tabletop demonstration it is possible to interact with two soft robotic platforms that have been used in human-robot interaction experiments (also accepted to HRI'18 as a Late...

Abstract robots with an attitude : applying interpersonal relation models to human-robot interaction

NARCIS (Netherlands)

Hiah, J.L.; Beursgens, L.; Haex, R.; Perez Romero, L.M.; Teh, Y.; Bhomer, ten M.; Berkel, van R.E.A.; Barakova, E.I.

2013-01-01

This paper explores new possibilities for social interaction between a human user and a robot with an abstract shape. The social interaction takes place by simulating behaviors such as submissiveness and dominance and analyzing the corresponding human reactions. We used an object that has no

A Novel Bioinspired Vision System: A Step toward Real-Time Human-Robot Interactions

Directory of Open Access Journals (Sweden)

Abdul Rahman Hafiz

2011-01-01

Full Text Available Building a human-like robot that could be involved in our daily lives is a dream of many scientists. Achieving a sophisticated robot's vision system, which can enhance the robot's real-time interaction ability with the human, is one of the main keys toward realizing such an autonomous robot. In this work, we are suggesting a bioinspired vision system that helps to develop an advanced human-robot interaction in an autonomous humanoid robot. First, we enhance the robot's vision accuracy online by applying a novel dynamic edge detection algorithm abstracted from the rules that the horizontal cells play in the mammalian retina. Second, in order to support the first algorithm, we improve the robot's tracking ability by designing a variant photoreceptors distribution corresponding to what exists in the human vision system. The experimental results verified the validity of the model. The robot could have a clear vision in real time and build a mental map that assisted it to be aware of the frontal users and to develop a positive interaction with them.

A Social Cognitive Neuroscience Stance on Human-Robot Interactions

Directory of Open Access Journals (Sweden)

Chaminade Thierry

2011-12-01

Full Text Available Robotic devices, thanks to the controlled variations in their appearance and behaviors, provide useful tools to test hypotheses pertaining to social interactions. These agents were used to investigate one theoretical framework, resonance, which is defined, at the behavioral and neural levels, as an overlap between first- and third- person representations of mental states such as motor intentions or emotions. Behaviorally, we found a reduced, but significant, resonance towards a humanoid robot displaying biological motion, compared to a human. Using neuroimaging, we've reported that while perceptual processes in the human occipital and temporal lobe are more strongly engaged when perceiving a humanoid robot than a human action, activity in areas involved in motor resonance depends on attentional modulation for artificial agent more strongly than for human agents. Altogether, these studies using artificial agents offer valuable insights into the interaction of bottom-up and top-down processes in the perception of artificial agents.

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.

Warning Signals for Poor Performance Improve Human-Robot Interaction

NARCIS (Netherlands)

van den Brule, Rik; Bijlstra, Gijsbert; Dotsch, Ron; Haselager, Pim; Wigboldus, Daniel HJ

2016-01-01

The present research was aimed at investigating whether human-robot interaction (HRI) can be improved by a robot’s nonverbal warning signals. Ideally, when a robot signals that it cannot guarantee good performance, people could take preventive actions to ensure the successful completion of the

Mobile app for human-interaction with sitter robots

Science.gov (United States)

Das, Sumit Kumar; Sahu, Ankita; Popa, Dan O.

2017-05-01

Human environments are often unstructured and unpredictable, thus making the autonomous operation of robots in such environments is very difficult. Despite many remaining challenges in perception, learning, and manipulation, more and more studies involving assistive robots have been carried out in recent years. In hospital environments, and in particular in patient rooms, there are well-established practices with respect to the type of furniture, patient services, and schedule of interventions. As a result, adding a robot into semi-structured hospital environments is an easier problem to tackle, with results that could have positive benefits to the quality of patient care and the help that robots can offer to nursing staff. When working in a healthcare facility, robots need to interact with patients and nurses through Human-Machine Interfaces (HMIs) that are intuitive to use, they should maintain awareness of surroundings, and offer safety guarantees for humans. While fully autonomous operation for robots is not yet technically feasible, direct teleoperation control of the robot would also be extremely cumbersome, as it requires expert user skills, and levels of concentration not available to many patients. Therefore, in our current study we present a traded control scheme, in which the robot and human both perform expert tasks. The human-robot communication and control scheme is realized through a mobile tablet app that can be customized for robot sitters in hospital environments. The role of the mobile app is to augment the verbal commands given to a robot through natural speech, camera and other native interfaces, while providing failure mode recovery options for users. Our app can access video feed and sensor data from robots, assist the user with decision making during pick and place operations, monitor the user health over time, and provides conversational dialogue during sitting sessions. In this paper, we present the software and hardware framework that

Gaze-and-brain-controlled interfaces for human-computer and human-robot interaction

Directory of Open Access Journals (Sweden)

Shishkin S. L.

2017-09-01

Full Text Available Background. Human-machine interaction technology has greatly evolved during the last decades, but manual and speech modalities remain single output channels with their typical constraints imposed by the motor system’s information transfer limits. Will brain-computer interfaces (BCIs and gaze-based control be able to convey human commands or even intentions to machines in the near future? We provide an overview of basic approaches in this new area of applied cognitive research. Objective. We test the hypothesis that the use of communication paradigms and a combination of eye tracking with unobtrusive forms of registering brain activity can improve human-machine interaction. Methods and Results. Three groups of ongoing experiments at the Kurchatov Institute are reported. First, we discuss the communicative nature of human-robot interaction, and approaches to building a more e cient technology. Specifically, “communicative” patterns of interaction can be based on joint attention paradigms from developmental psychology, including a mutual “eye-to-eye” exchange of looks between human and robot. Further, we provide an example of “eye mouse” superiority over the computer mouse, here in emulating the task of selecting a moving robot from a swarm. Finally, we demonstrate a passive, noninvasive BCI that uses EEG correlates of expectation. This may become an important lter to separate intentional gaze dwells from non-intentional ones. Conclusion. The current noninvasive BCIs are not well suited for human-robot interaction, and their performance, when they are employed by healthy users, is critically dependent on the impact of the gaze on selection of spatial locations. The new approaches discussed show a high potential for creating alternative output pathways for the human brain. When support from passive BCIs becomes mature, the hybrid technology of the eye-brain-computer (EBCI interface will have a chance to enable natural, fluent, and the

Human-Robot Site Survey and Sampling for Space Exploration

Science.gov (United States)

Fong, Terrence; Bualat, Maria; Edwards, Laurence; Flueckiger, Lorenzo; Kunz, Clayton; Lee, Susan Y.; Park, Eric; To, Vinh; Utz, Hans; Ackner, Nir

2006-01-01

NASA is planning to send humans and robots back to the Moon before 2020. In order for extended missions to be productive, high quality maps of lunar terrain and resources are required. Although orbital images can provide much information, many features (local topography, resources, etc) will have to be characterized directly on the surface. To address this need, we are developing a system to perform site survey and sampling. The system includes multiple robots and humans operating in a variety of team configurations, coordinated via peer-to-peer human-robot interaction. In this paper, we present our system design and describe planned field tests.

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

Intelligent Interaction for Human-Friendly Service Robot in Smart House Environment

Directory of Open Access Journals (Sweden)

Z. Zenn Bien

2008-01-01

Full Text Available The smart house under consideration is a service-integrated complex system to assist older persons and/or people with disabilities. The primary goal of the system is to achieve independent living by various robotic devices and systems. Such a system is treated as a human-in-the loop system in which human- robot interaction takes place intensely and frequently. Based on our experiences of having designed and implemented a smart house environment, called Intelligent Sweet Home (ISH, we present a framework of realizing human-friendly HRI (human-robot interaction module with various effective techniques of computational intelligence. More specifically, we partition the robotic tasks of HRI module into three groups in consideration of the level of specificity, fuzziness or uncertainty of the context of the system, and present effective interaction method for each case. We first show a task planning algorithm and its architecture to deal with well-structured tasks autonomously by a simplified set of commands of the user instead of inconvenient manual operations. To provide with capability of interacting in a human-friendly way in a fuzzy context, it is proposed that the robot should make use of human bio-signals as input of the HRI module as shown in a hand gesture recognition system, called a soft remote control system. Finally we discuss a probabilistic fuzzy rule-based life-long learning system, equipped with intention reading capability by learning human behavioral patterns, which is introduced as a solution in uncertain and time-varying situations.

An Experimental Study of Embodied Interaction and Human Perception of Social Presence for Interactive Robots in Public Settings

DEFF Research Database (Denmark)

Jochum, Elizabeth Ann; Heath, Damith; Vlachos, Evgenios

2018-01-01

The human perception of cognitive robots as social depends on many factors, including those that do not necessarily pertain to a robot’s cognitive functioning. Experience Design offers a useful framework for evaluating when participants interact with robots as products or tools and when they regard...... them as social actors. This study describes a between-participants experiment conducted at a science museum, where visitors were invited to play a game of noughts and crosses with a Baxter robot. The goal is to foster meaningful interactions that promote engagement between the human and robot...... in a museum context. Using an Experience Design framework, we tested the robot in three different conditions to better understand which factors contribute to the perception of robots as social. The experiment also outlines best practices for conducting human-robot interaction research in museum exhibitions...

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

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

Understanding and Resolving Failures in Human-Robot Interaction: Literature Review and Model Development

Directory of Open Access Journals (Sweden)

Shanee Honig

2018-06-01

Full Text Available While substantial effort has been invested in making robots more reliable, experience demonstrates that robots operating in unstructured environments are often challenged by frequent failures. Despite this, robots have not yet reached a level of design that allows effective management of faulty or unexpected behavior by untrained users. To understand why this may be the case, an in-depth literature review was done to explore when people perceive and resolve robot failures, how robots communicate failure, how failures influence people's perceptions and feelings toward robots, and how these effects can be mitigated. Fifty-two studies were identified relating to communicating failures and their causes, the influence of failures on human-robot interaction (HRI, and mitigating failures. Since little research has been done on these topics within the HRI community, insights from the fields of human computer interaction (HCI, human factors engineering, cognitive engineering and experimental psychology are presented and discussed. Based on the literature, we developed a model of information processing for robotic failures (Robot Failure Human Information Processing, RF-HIP, that guides the discussion of our findings. The model describes the way people perceive, process, and act on failures in human robot interaction. The model includes three main parts: (1 communicating failures, (2 perception and comprehension of failures, and (3 solving failures. Each part contains several stages, all influenced by contextual considerations and mitigation strategies. Several gaps in the literature have become evident as a result of this evaluation. More focus has been given to technical failures than interaction failures. Few studies focused on human errors, on communicating failures, or the cognitive, psychological, and social determinants that impact the design of mitigation strategies. By providing the stages of human information processing, RF-HIP can be used as a

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.

Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction.

Science.gov (United States)

de Greeff, Joachim; Belpaeme, Tony

2015-01-01

Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance.

Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction.

Directory of Open Access Journals (Sweden)

Joachim de Greeff

Full Text Available Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference; the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance.

Advancing the Strategic Messages Affecting Robot Trust Effect: The Dynamic of User- and Robot-Generated Content on Human-Robot Trust and Interaction Outcomes.

Science.gov (United States)

Liang, Yuhua Jake; Lee, Seungcheol Austin

2016-09-01

Human-robot interaction (HRI) will soon transform and shift the communication landscape such that people exchange messages with robots. However, successful HRI requires people to trust robots, and, in turn, the trust affects the interaction. Although prior research has examined the determinants of human-robot trust (HRT) during HRI, no research has examined the messages that people received before interacting with robots and their effect on HRT. We conceptualize these messages as SMART (Strategic Messages Affecting Robot Trust). Moreover, we posit that SMART can ultimately affect actual HRI outcomes (i.e., robot evaluations, robot credibility, participant mood) by affording the persuasive influences from user-generated content (UGC) on participatory Web sites. In Study 1, participants were assigned to one of two conditions (UGC/control) in an original experiment of HRT. Compared with the control (descriptive information only), results showed that UGC moderated the correlation between HRT and interaction outcomes in a positive direction (average Δr = +0.39) for robots as media and robots as tools. In Study 2, we explored the effect of robot-generated content but did not find similar moderation effects. These findings point to an important empirical potential to employ SMART in future robot deployment.

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....

Physical human-robot interaction of an active pelvis orthosis: toward ergonomic assessment of wearable robots.

Science.gov (United States)

d'Elia, Nicolò; Vanetti, Federica; Cempini, Marco; Pasquini, Guido; Parri, Andrea; Rabuffetti, Marco; Ferrarin, Maurizio; Molino Lova, Raffaele; Vitiello, Nicola

2017-04-14

In human-centered robotics, exoskeletons are becoming relevant for addressing needs in the healthcare and industrial domains. Owing to their close interaction with the user, the safety and ergonomics of these systems are critical design features that require systematic evaluation methodologies. Proper transfer of mechanical power requires optimal tuning of the kinematic coupling between the robotic and anatomical joint rotation axes. We present the methods and results of an experimental evaluation of the physical interaction with an active pelvis orthosis (APO). This device was designed to effectively assist in hip flexion-extension during locomotion with a minimum impact on the physiological human kinematics, owing to a set of passive degrees of freedom for self-alignment of the human and robotic hip flexion-extension axes. Five healthy volunteers walked on a treadmill at different speeds without and with the APO under different levels of assistance. The user-APO physical interaction was evaluated in terms of: (i) the deviation of human lower-limb joint kinematics when wearing the APO with respect to the physiological behavior (i.e., without the APO); (ii) relative displacements between the APO orthotic shells and the corresponding body segments; and (iii) the discrepancy between the kinematics of the APO and the wearer's hip joints. The results show: (i) negligible interference of the APO in human kinematics under all the experimented conditions; (ii) small (i.e., ergonomics assessment of wearable robots.

Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction

Science.gov (United States)

de Greeff, Joachim; Belpaeme, Tony

2015-01-01

Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children’s social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a “mental model” of the robot, tailoring the tutoring to the robot’s performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot’s bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance. PMID:26422143

Mission Reliability Estimation for Repairable Robot Teams

Science.gov (United States)

Trebi-Ollennu, Ashitey; Dolan, John; Stancliff, Stephen

2010-01-01

A mission reliability estimation method has been designed to translate mission requirements into choices of robot modules in order to configure a multi-robot team to have high reliability at minimal cost. In order to build cost-effective robot teams for long-term missions, one must be able to compare alternative design paradigms in a principled way by comparing the reliability of different robot models and robot team configurations. Core modules have been created including: a probabilistic module with reliability-cost characteristics, a method for combining the characteristics of multiple modules to determine an overall reliability-cost characteristic, and a method for the generation of legitimate module combinations based on mission specifications and the selection of the best of the resulting combinations from a cost-reliability standpoint. The developed methodology can be used to predict the probability of a mission being completed, given information about the components used to build the robots, as well as information about the mission tasks. In the research for this innovation, sample robot missions were examined and compared to the performance of robot teams with different numbers of robots and different numbers of spare components. Data that a mission designer would need was factored in, such as whether it would be better to have a spare robot versus an equivalent number of spare parts, or if mission cost can be reduced while maintaining reliability using spares. This analytical model was applied to an example robot mission, examining the cost-reliability tradeoffs among different team configurations. Particularly scrutinized were teams using either redundancy (spare robots) or repairability (spare components). Using conservative estimates of the cost-reliability relationship, results show that it is possible to significantly reduce the cost of a robotic mission by using cheaper, lower-reliability components and providing spares. This suggests that the

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.

Human-inspired feedback synergies for environmental interaction with a dexterous robotic hand.

Science.gov (United States)

Kent, Benjamin A; Engeberg, Erik D

2014-11-07

Effortless control of the human hand is mediated by the physical and neural couplings inherent in the structure of the hand. This concept was explored for environmental interaction tasks with the human hand, and a novel human-inspired feedback synergy (HFS) controller was developed for a robotic hand which synchronized position and force feedback signals to mimic observed human hand motions. This was achieved by first recording the finger joint motion profiles of human test subjects, where it was observed that the subjects would extend their fingers to maintain a natural hand posture when interacting with different surfaces. The resulting human joint angle data were used as inspiration to develop the HFS controller for the anthropomorphic robotic hand, which incorporated finger abduction and force feedback in the control laws for finger extension. Experimental results showed that by projecting a broader view of the tasks at hand to each specific joint, the HFS controller produced hand motion profiles that closely mimic the observed human responses and allowed the robotic manipulator to interact with the surfaces while maintaining a natural hand posture. Additionally, the HFS controller enabled the robotic hand to autonomously traverse vertical step discontinuities without prior knowledge of the environment, visual feedback, or traditional trajectory planning techniques.

Human-inspired feedback synergies for environmental interaction with a dexterous robotic hand

International Nuclear Information System (INIS)

Kent, Benjamin A; Engeberg, Erik D

2014-01-01

Effortless control of the human hand is mediated by the physical and neural couplings inherent in the structure of the hand. This concept was explored for environmental interaction tasks with the human hand, and a novel human-inspired feedback synergy (HFS) controller was developed for a robotic hand which synchronized position and force feedback signals to mimic observed human hand motions. This was achieved by first recording the finger joint motion profiles of human test subjects, where it was observed that the subjects would extend their fingers to maintain a natural hand posture when interacting with different surfaces. The resulting human joint angle data were used as inspiration to develop the HFS controller for the anthropomorphic robotic hand, which incorporated finger abduction and force feedback in the control laws for finger extension. Experimental results showed that by projecting a broader view of the tasks at hand to each specific joint, the HFS controller produced hand motion profiles that closely mimic the observed human responses and allowed the robotic manipulator to interact with the surfaces while maintaining a natural hand posture. Additionally, the HFS controller enabled the robotic hand to autonomously traverse vertical step discontinuities without prior knowledge of the environment, visual feedback, or traditional trajectory planning techniques. (paper)

Common Metrics for Human-Robot Interaction

Science.gov (United States)

Steinfeld, Aaron; Lewis, Michael; Fong, Terrence; Scholtz, Jean; Schultz, Alan; Kaber, David; Goodrich, Michael

2006-01-01

This paper describes an effort to identify common metrics for task-oriented human-robot interaction (HRI). We begin by discussing the need for a toolkit of HRI metrics. We then describe the framework of our work and identify important biasing factors that must be taken into consideration. Finally, we present suggested common metrics for standardization and a case study. Preparation of a larger, more detailed toolkit is in progress.

Negative Affect in Human Robot Interaction

DEFF Research Database (Denmark)

Rehm, Matthias; Krogsager, Anders

2013-01-01

The vision of social robotics sees robots moving more and more into unrestricted social environments, where robots interact closely with users in their everyday activities, maybe even establishing relationships with the user over time. In this paper we present a field trial with a robot in a semi...

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.

Human-Robot Collaboration: A Literature Review and Augmented Reality Approach in Design

Directory of Open Access Journals (Sweden)

Scott A. Green

2008-03-01

Full Text Available NASA's vision for space exploration stresses the cultivation of human-robotic systems. Similar systems are also envisaged for a variety of hazardous earthbound applications such as urban search and rescue. Recent research has pointed out that to reduce human workload, costs, fatigue driven error and risk, intelligent robotic systems will need to be a significant part of mission design. However, little attention has been paid to joint human-robot teams. Making human-robot collaboration natural and efficient is crucial. In particular, grounding, situational awareness, a common frame of reference and spatial referencing are vital in effective communication and collaboration. Augmented Reality (AR, the overlaying of computer graphics onto the real worldview, can provide the necessary means for a human-robotic system to fulfill these requirements for effective collaboration. This article reviews the field of human-robot interaction and augmented reality, investigates the potential avenues for creating natural human-robot collaboration through spatial dialogue utilizing AR and proposes a holistic architectural design for human-robot collaboration.

Human-Robot Collaboration: A Literature Review and Augmented Reality Approach in Design

Directory of Open Access Journals (Sweden)

Scott A. Green

2008-11-01

Full Text Available NASA?s vision for space exploration stresses the cultivation of human-robotic systems. Similar systems are also envisaged for a variety of hazardous earthbound applications such as urban search and rescue. Recent research has pointed out that to reduce human workload, costs, fatigue driven error and risk, intelligent robotic systems will need to be a significant part of mission design. However, little attention has been paid to joint human-robot teams. Making human-robot collaboration natural and efficient is crucial. In particular, grounding, situational awareness, a common frame of reference and spatial referencing are vital in effective communication and collaboration. Augmented Reality (AR, the overlaying of computer graphics onto the real worldview, can provide the necessary means for a human-robotic system to fulfill these requirements for effective collaboration. This article reviews the field of human-robot interaction and augmented reality, investigates the potential avenues for creating natural human-robot collaboration through spatial dialogue utilizing AR and proposes a holistic architectural design for human-robot collaboration.

Sediment Sampling in Estuarine Mudflats with an Aerial-Ground Robotic Team

Directory of Open Access Journals (Sweden)

Pedro Deusdado

2016-09-01

Full Text Available This paper presents a robotic team suited for bottom sediment sampling and retrieval in mudflats, targeting environmental monitoring tasks. The robotic team encompasses a four-wheel-steering ground vehicle, equipped with a drilling tool designed to be able to retain wet soil, and a multi-rotor aerial vehicle for dynamic aerial imagery acquisition. On-demand aerial imagery, properly fused on an aerial mosaic, is used by remote human operators for specifying the robotic mission and supervising its execution. This is crucial for the success of an environmental monitoring study, as often it depends on human expertise to ensure the statistical significance and accuracy of the sampling procedures. Although the literature is rich on environmental monitoring sampling procedures, in mudflats, there is a gap as regards including robotic elements. This paper closes this gap by also proposing a preliminary experimental protocol tailored to exploit the capabilities offered by the robotic system. Field trials in the south bank of the river Tagus’ estuary show the ability of the robotic system to successfully extract and transport bottom sediment samples for offline analysis. The results also show the efficiency of the extraction and the benefits when compared to (conventional human-based sampling.

Sediment Sampling in Estuarine Mudflats with an Aerial-Ground Robotic Team

Science.gov (United States)

Deusdado, Pedro; Guedes, Magno; Silva, André; Marques, Francisco; Pinto, Eduardo; Rodrigues, Paulo; Lourenço, André; Mendonça, Ricardo; Santana, Pedro; Corisco, José; Almeida, Susana Marta; Portugal, Luís; Caldeira, Raquel; Barata, José; Flores, Luis

2016-01-01

This paper presents a robotic team suited for bottom sediment sampling and retrieval in mudflats, targeting environmental monitoring tasks. The robotic team encompasses a four-wheel-steering ground vehicle, equipped with a drilling tool designed to be able to retain wet soil, and a multi-rotor aerial vehicle for dynamic aerial imagery acquisition. On-demand aerial imagery, properly fused on an aerial mosaic, is used by remote human operators for specifying the robotic mission and supervising its execution. This is crucial for the success of an environmental monitoring study, as often it depends on human expertise to ensure the statistical significance and accuracy of the sampling procedures. Although the literature is rich on environmental monitoring sampling procedures, in mudflats, there is a gap as regards including robotic elements. This paper closes this gap by also proposing a preliminary experimental protocol tailored to exploit the capabilities offered by the robotic system. Field trials in the south bank of the river Tagus’ estuary show the ability of the robotic system to successfully extract and transport bottom sediment samples for offline analysis. The results also show the efficiency of the extraction and the benefits when compared to (conventional) human-based sampling. PMID:27618060

Multi-Axis Force Sensor for Human-Robot Interaction Sensing in a Rehabilitation Robotic Device.

Science.gov (United States)

Grosu, Victor; Grosu, Svetlana; Vanderborght, Bram; Lefeber, Dirk; Rodriguez-Guerrero, Carlos

2017-06-05

Human-robot interaction sensing is a compulsory feature in modern robotic systems where direct contact or close collaboration is desired. Rehabilitation and assistive robotics are fields where interaction forces are required for both safety and increased control performance of the device with a more comfortable experience for the user. In order to provide an efficient interaction feedback between the user and rehabilitation device, high performance sensing units are demanded. This work introduces a novel design of a multi-axis force sensor dedicated for measuring pelvis interaction forces in a rehabilitation exoskeleton device. The sensor is conceived such that it has different sensitivity characteristics for the three axes of interest having also movable parts in order to allow free rotations and limit crosstalk errors. Integrated sensor electronics make it easy to acquire and process data for a real-time distributed system architecture. Two of the developed sensors are integrated and tested in a complex gait rehabilitation device for safe and compliant control.

Systematic Analysis of Video Data from Different Human-Robot Interaction Studies: A Categorisation of Social Signals During Error Situations

OpenAIRE

Manuel eGiuliani; Nicole eMirnig; Gerald eStollnberger; Susanne eStadler; Roland eBuchner; Manfred eTscheligi

2015-01-01

Human?robot interactions are often affected by error situations that are caused by either the robot or the human. Therefore, robots would profit from the ability to recognize when error situations occur. We investigated the verbal and non-verbal social signals that humans show when error situations occur in human?robot interaction experiments. For that, we analyzed 201 videos of five human?robot interaction user studies with varying tasks from four independent projects. The analysis shows tha...

The ethics of human-robot relationships

NARCIS (Netherlands)

de Graaf, M.M.A.

2015-01-01

Currently, human-robot interactions are constructed according to the rules of human-human interactions inviting users to interact socially with robots. Is there something morally wrong with deceiving humans into thinking they can foster meaningful interactions with a technological object? Or is this

Estimation of Physical Human-Robot Interaction Using Cost-Effective Pneumatic Padding

Directory of Open Access Journals (Sweden)

André Wilkening

2016-08-01

Full Text Available The idea to use a cost-effective pneumatic padding for sensing of physical interaction between a user and wearable rehabilitation robots is not new, but until now there has not been any practical relevant realization. In this paper, we present a novel method to estimate physical human-robot interaction using a pneumatic padding based on artificial neural networks (ANNs. This estimation can serve as rough indicator of applied forces/torques by the user and can be applied for visual feedback about the user’s participation or as additional information for interaction controllers. Unlike common mostly very expensive 6-axis force/torque sensors (FTS, the proposed sensor system can be easily integrated in the design of physical human-robot interfaces of rehabilitation robots and adapts itself to the shape of the individual patient’s extremity by pressure changing in pneumatic chambers, in order to provide a safe physical interaction with high user’s comfort. This paper describes a concept of using ANNs for estimation of interaction forces/torques based on pressure variations of eight customized air-pad chambers. The ANNs were trained one-time offline using signals of a high precision FTS which is also used as reference sensor for experimental validation. Experiments with three different subjects confirm the functionality of the concept and the estimation algorithm.

In our own image? Emotional and neural processing differences when observing human-human vs human-robot interactions.

Science.gov (United States)

Wang, Yin; Quadflieg, Susanne

2015-11-01

Notwithstanding the significant role that human-robot interactions (HRI) will play in the near future, limited research has explored the neural correlates of feeling eerie in response to social robots. To address this empirical lacuna, the current investigation examined brain activity using functional magnetic resonance imaging while a group of participants (n = 26) viewed a series of human-human interactions (HHI) and HRI. Although brain sites constituting the mentalizing network were found to respond to both types of interactions, systematic neural variation across sites signaled diverging social-cognitive strategies during HHI and HRI processing. Specifically, HHI elicited increased activity in the left temporal-parietal junction indicative of situation-specific mental state attributions, whereas HRI recruited the precuneus and the ventromedial prefrontal cortex (VMPFC) suggestive of script-based social reasoning. Activity in the VMPFC also tracked feelings of eeriness towards HRI in a parametric manner, revealing a potential neural correlate for a phenomenon known as the uncanny valley. By demonstrating how understanding social interactions depends on the kind of agents involved, this study highlights pivotal sub-routes of impression formation and identifies prominent challenges in the use of humanoid robots. © The Author (2015). Published by Oxford University Press.

A meta-analysis of factors affecting trust in human-robot interaction.

Science.gov (United States)

Hancock, Peter A; Billings, Deborah R; Schaefer, Kristin E; Chen, Jessie Y C; de Visser, Ewart J; Parasuraman, Raja

2011-10-01

We evaluate and quantify the effects of human, robot, and environmental factors on perceived trust in human-robot interaction (HRI). To date, reviews of trust in HRI have been qualitative or descriptive. Our quantitative review provides a fundamental empirical foundation to advance both theory and practice. Meta-analytic methods were applied to the available literature on trust and HRI. A total of 29 empirical studies were collected, of which 10 met the selection criteria for correlational analysis and 11 for experimental analysis. These studies provided 69 correlational and 47 experimental effect sizes. The overall correlational effect size for trust was r = +0.26,with an experimental effect size of d = +0.71. The effects of human, robot, and environmental characteristics were examined with an especial evaluation of the robot dimensions of performance and attribute-based factors. The robot performance and attributes were the largest contributors to the development of trust in HRI. Environmental factors played only a moderate role. Factors related to the robot itself, specifically, its performance, had the greatest current association with trust, and environmental factors were moderately associated. There was little evidence for effects of human-related factors. The findings provide quantitative estimates of human, robot, and environmental factors influencing HRI trust. Specifically, the current summary provides effect size estimates that are useful in establishing design and training guidelines with reference to robot-related factors of HRI trust. Furthermore, results indicate that improper trust calibration may be mitigated by the manipulation of robot design. However, many future research needs are identified.

Perceptions of a Soft Robotic Tentacle in Interaction

DEFF Research Database (Denmark)

Jørgensen, Jonas

2018-01-01

Soft robotics technology has been proposed for a number of applications that involve human-robot interaction. This video documents a platform created to explore human perceptions of soft robots in interaction. The video presents select footage from an interaction experiment conducted...

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.

Affect in Human-Robot Interaction

Science.gov (United States)

2014-01-01

Werry, I., Rae, J., Dickerson, P., Stribling, P., & Ogden, B. (2002). Robotic Playmates: Analysing Interactive Competencies of Children with Autism ...WE-4RII. IEEE International Conference on Intelligent Robots and Systems, Edmonton, Canada. 35. Moravec, H. (1988). Mind Children : The Future of...and if so when and where? • What approaches, theories , representations, and experimental methods inform affective HRI research? Report Documentation

Turn-Taking Based on Information Flow for Fluent Human-Robot Interaction

OpenAIRE

Thomaz, Andrea L.; Chao, Crystal

2011-01-01

Turn-taking is a fundamental part of human communication. Our goal is to devise a turn-taking framework for human-robot interaction that, like the human skill, represents something fundamental about interaction, generic to context or domain. We propose a model of turn-taking, and conduct an experiment with human subjects to inform this model. Our findings from this study suggest that information flow is an integral part of human floor-passing behavior. Following this, we implement autonomous ...

Visual exploration and analysis of human-robot interaction rules

Science.gov (United States)

Zhang, Hui; Boyles, Michael J.

2013-01-01

We present a novel interaction paradigm for the visual exploration, manipulation and analysis of human-robot interaction (HRI) rules; our development is implemented using a visual programming interface and exploits key techniques drawn from both information visualization and visual data mining to facilitate the interaction design and knowledge discovery process. HRI is often concerned with manipulations of multi-modal signals, events, and commands that form various kinds of interaction rules. Depicting, manipulating and sharing such design-level information is a compelling challenge. Furthermore, the closed loop between HRI programming and knowledge discovery from empirical data is a relatively long cycle. This, in turn, makes design-level verification nearly impossible to perform in an earlier phase. In our work, we exploit a drag-and-drop user interface and visual languages to support depicting responsive behaviors from social participants when they interact with their partners. For our principal test case of gaze-contingent HRI interfaces, this permits us to program and debug the robots' responsive behaviors through a graphical data-flow chart editor. We exploit additional program manipulation interfaces to provide still further improvement to our programming experience: by simulating the interaction dynamics between a human and a robot behavior model, we allow the researchers to generate, trace and study the perception-action dynamics with a social interaction simulation to verify and refine their designs. Finally, we extend our visual manipulation environment with a visual data-mining tool that allows the user to investigate interesting phenomena such as joint attention and sequential behavioral patterns from multiple multi-modal data streams. We have created instances of HRI interfaces to evaluate and refine our development paradigm. As far as we are aware, this paper reports the first program manipulation paradigm that integrates visual programming

Ghost-in-the-Machine reveals human social signals for human–robot interaction

Science.gov (United States)

Loth, Sebastian; Jettka, Katharina; Giuliani, Manuel; de Ruiter, Jan P.

2015-01-01

We used a new method called “Ghost-in-the-Machine” (GiM) to investigate social interactions with a robotic bartender taking orders for drinks and serving them. Using the GiM paradigm allowed us to identify how human participants recognize the intentions of customers on the basis of the output of the robotic recognizers. Specifically, we measured which recognizer modalities (e.g., speech, the distance to the bar) were relevant at different stages of the interaction. This provided insights into human social behavior necessary for the development of socially competent robots. When initiating the drink-order interaction, the most important recognizers were those based on computer vision. When drink orders were being placed, however, the most important information source was the speech recognition. Interestingly, the participants used only a subset of the available information, focussing only on a few relevant recognizers while ignoring others. This reduced the risk of acting on erroneous sensor data and enabled them to complete service interactions more swiftly than a robot using all available sensor data. We also investigated socially appropriate response strategies. In their responses, the participants preferred to use the same modality as the customer’s requests, e.g., they tended to respond verbally to verbal requests. Also, they added redundancy to their responses, for instance by using echo questions. We argue that incorporating the social strategies discovered with the GiM paradigm in multimodal grammars of human–robot interactions improves the robustness and the ease-of-use of these interactions, and therefore provides a smoother user experience. PMID:26582998

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.

Systematic analysis of video data from different human-robot interaction studies: a categorization of social signals during error situations.

Science.gov (United States)

Giuliani, Manuel; Mirnig, Nicole; Stollnberger, Gerald; Stadler, Susanne; Buchner, Roland; Tscheligi, Manfred

2015-01-01

Human-robot interactions are often affected by error situations that are caused by either the robot or the human. Therefore, robots would profit from the ability to recognize when error situations occur. We investigated the verbal and non-verbal social signals that humans show when error situations occur in human-robot interaction experiments. For that, we analyzed 201 videos of five human-robot interaction user studies with varying tasks from four independent projects. The analysis shows that there are two types of error situations: social norm violations and technical failures. Social norm violations are situations in which the robot does not adhere to the underlying social script of the interaction. Technical failures are caused by technical shortcomings of the robot. The results of the video analysis show that the study participants use many head movements and very few gestures, but they often smile, when in an error situation with the robot. Another result is that the participants sometimes stop moving at the beginning of error situations. We also found that the participants talked more in the case of social norm violations and less during technical failures. Finally, the participants use fewer non-verbal social signals (for example smiling, nodding, and head shaking), when they are interacting with the robot alone and no experimenter or other human is present. The results suggest that participants do not see the robot as a social interaction partner with comparable communication skills. Our findings have implications for builders and evaluators of human-robot interaction systems. The builders need to consider including modules for recognition and classification of head movements to the robot input channels. The evaluators need to make sure that the presence of an experimenter does not skew the results of their user studies.

Pragmatic Frames for Teaching and Learning in Human-Robot Interaction: Review and Challenges.

Science.gov (United States)

Vollmer, Anna-Lisa; Wrede, Britta; Rohlfing, Katharina J; Oudeyer, Pierre-Yves

2016-01-01

One of the big challenges in robotics today is to learn from human users that are inexperienced in interacting with robots but yet are often used to teach skills flexibly to other humans and to children in particular. A potential route toward natural and efficient learning and teaching in Human-Robot Interaction (HRI) is to leverage the social competences of humans and the underlying interactional mechanisms. In this perspective, this article discusses the importance of pragmatic frames as flexible interaction protocols that provide important contextual cues to enable learners to infer new action or language skills and teachers to convey these cues. After defining and discussing the concept of pragmatic frames, grounded in decades of research in developmental psychology, we study a selection of HRI work in the literature which has focused on learning-teaching interaction and analyze the interactional and learning mechanisms that were used in the light of pragmatic frames. This allows us to show that many of the works have already used in practice, but not always explicitly, basic elements of the pragmatic frames machinery. However, we also show that pragmatic frames have so far been used in a very restricted way as compared to how they are used in human-human interaction and argue that this has been an obstacle preventing robust natural multi-task learning and teaching in HRI. In particular, we explain that two central features of human pragmatic frames, mostly absent of existing HRI studies, are that (1) social peers use rich repertoires of frames, potentially combined together, to convey and infer multiple kinds of cues; (2) new frames can be learnt continually, building on existing ones, and guiding the interaction toward higher levels of complexity and expressivity. To conclude, we give an outlook on the future research direction describing the relevant key challenges that need to be solved for leveraging pragmatic frames for robot learning and teaching.

Human-Automation Allocations for Current Robotic Space Operations

Science.gov (United States)

Marquez, Jessica J.; Chang, Mai L.; Beard, Bettina L.; Kim, Yun Kyung; Karasinski, John A.

2018-01-01

Within the Human Research Program, one risk delineates the uncertainty surrounding crew working with automation and robotics in spaceflight. The Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is concerned with the detrimental effects on crew performance due to ineffective user interfaces, system designs and/or functional task allocation, potentially compromising mission success and safety. Risk arises because we have limited experience with complex automation and robotics. One key gap within HARI, is the gap related to functional allocation. The gap states: We need to evaluate, develop, and validate methods and guidelines for identifying human-automation/robot task information needs, function allocation, and team composition for future long duration, long distance space missions. Allocations determine the human-system performance as it identifies the functions and performance levels required by the automation/robotic system, and in turn, what work the crew is expected to perform and the necessary human performance requirements. Allocations must take into account each of the human, automation, and robotic systems capabilities and limitations. Some functions may be intuitively assigned to the human versus the robot, but to optimize efficiency and effectiveness, purposeful role assignments will be required. The role of automation and robotics will significantly change in future exploration missions, particularly as crew becomes more autonomous from ground controllers. Thus, we must understand the suitability of existing function allocation methods within NASA as well as the existing allocations established by the few robotic systems that are operational in spaceflight. In order to evaluate future methods of robotic allocations, we must first benchmark the allocations and allocation methods that have been used. We will present 1) documentation of human-automation-robotic allocations in existing, operational spaceflight systems; and 2) To

Generating Self-Reliant Teams of Autonomous Cooperating Robots: Desired design Characteristics

Energy Technology Data Exchange (ETDEWEB)

Parker, L.E.

1999-05-01

The difficulties in designing a cooperative team are significant. Several of the key questions that must be resolved when designing a cooperative control architecture include: How do we formulate, describe, decompose, and allocate problems among a group of intelligent agents? How do we enable agents to communicate and interact? How do we ensure that agents act coherently in their actions? How do we allow agents to recognize and reconcile conflicts? However, in addition to these key issues, the software architecture must be designed to enable multi-robot teams to be robust, reliable, and flexible. Without these capabilities, the resulting robot team will not be able to successfully deal with the dynamic and uncertain nature of the real world. In this extended abstract, we first describe these desired capabilities. We then briefly describe the ALLIANCE software architecture that we have previously developed for multi-robot cooperation. We then briefly analyze the ALLIANCE architecture in terms of the desired design qualities identified.

Social robots from a human perspective

CERN Document Server

Taipale, Sakari; Sapio, Bartolomeo; Lugano, Giuseppe; Fortunati, Leopoldina

2015-01-01

Addressing several issues that explore the human side of social robots, this book asks from a social and human scientific perspective what a social robot is and how we might come to think about social robots in the different areas of everyday life. Organized around three sections that deal with Perceptions and Attitudes to Social Robots, Human Interaction with Social Robots, and Social Robots in Everyday Life, the book explores the idea that even if technical problems related to robot technologies can be continuously solved from a machine perspective, what kind of machine do we want to have and use in our daily lives? Experiences from previously widely adopted technologies, such smartphones, hint that robot technologies could potentially be absorbed into the everyday lives of humans in such a way that it is the human that determines the human-machine interaction. In a similar way to how today’s information and communication technologies were first designed for professional/industrial use, but which soon wer...

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

Classifying a Person's Degree of Accessibility From Natural Body Language During Social Human-Robot Interactions.

Science.gov (United States)

McColl, Derek; Jiang, Chuan; Nejat, Goldie

2017-02-01

For social robots to be successfully integrated and accepted within society, they need to be able to interpret human social cues that are displayed through natural modes of communication. In particular, a key challenge in the design of social robots is developing the robot's ability to recognize a person's affective states (emotions, moods, and attitudes) in order to respond appropriately during social human-robot interactions (HRIs). In this paper, we present and discuss social HRI experiments we have conducted to investigate the development of an accessibility-aware social robot able to autonomously determine a person's degree of accessibility (rapport, openness) toward the robot based on the person's natural static body language. In particular, we present two one-on-one HRI experiments to: 1) determine the performance of our automated system in being able to recognize and classify a person's accessibility levels and 2) investigate how people interact with an accessibility-aware robot which determines its own behaviors based on a person's speech and accessibility levels.

Applications of artificial intelligence in safe human-robot interactions.

Science.gov (United States)

Najmaei, Nima; Kermani, Mehrdad R

2011-04-01

The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of artificial neural networks, namely, self-organizing maps (SOMs), is employed for obtaining a superquadric-based model of the human. The SOM network receives information of the human's footprints from the sensory system and infers necessary data for rendering the human model. The model is then used in order to assess the danger of the robot operations based on the measured as well as predicted human motions. This is followed by the introduction of a new reactive control scheme that results in the least interferences between the human and robot operations. The approach enables the robot to foresee an upcoming danger and take preventive actions before the danger becomes imminent. Simulation and experimental results are presented in order to validate the effectiveness of the proposed method.

Toward a unified method for analysing and teaching Human Robot Interaction

DEFF Research Database (Denmark)

Dinesen, Jens Vilhelm

, drawing on key theories and methods from both communications- and interaction-theory. The aim is to provide a single unified method for analysing interaction, through means of video analysis and then applying theories, with proven mutual compatibility, to reach a desired granularity of study.......This abstract aims to present key aspect of a future paper, which outlines the ongoing development ofa unified method for analysing and teaching Human-Robot-Interaction. The paper will propose a novel method for analysing both HRI, interaction with other forms of technologies and fellow humans...

Cognitive Emotional Regulation Model in Human-Robot Interaction

OpenAIRE

Liu, Xin; Xie, Lun; Liu, Anqi; Li, Dan

2015-01-01

This paper integrated Gross cognitive process into the HMM (hidden Markov model) emotional regulation method and implemented human-robot emotional interaction with facial expressions and behaviors. Here, energy was the psychological driving force of emotional transition in the cognitive emotional model. The input facial expression was translated into external energy by expression-emotion mapping. Robot’s next emotional state was determined by the cognitive energy (the stimulus after cognition...

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.

Exploring the acquisition and production of grammatical constructions through human-robot interaction with echo state networks.

Science.gov (United States)

Hinaut, Xavier; Petit, Maxime; Pointeau, Gregoire; Dominey, Peter Ford

2014-01-01

One of the principal functions of human language is to allow people to coordinate joint action. This includes the description of events, requests for action, and their organization in time. A crucial component of language acquisition is learning the grammatical structures that allow the expression of such complex meaning related to physical events. The current research investigates the learning of grammatical constructions and their temporal organization in the context of human-robot physical interaction with the embodied sensorimotor humanoid platform, the iCub. We demonstrate three noteworthy phenomena. First, a recurrent network model is used in conjunction with this robotic platform to learn the mappings between grammatical forms and predicate-argument representations of meanings related to events, and the robot's execution of these events in time. Second, this learning mechanism functions in the inverse sense, i.e., in a language production mode, where rather than executing commanded actions, the robot will describe the results of human generated actions. Finally, we collect data from naïve subjects who interact with the robot via spoken language, and demonstrate significant learning and generalization results. This allows us to conclude that such a neural language learning system not only helps to characterize and understand some aspects of human language acquisition, but also that it can be useful in adaptive human-robot interaction.

Anthropomorphism in Human-Robot Co-evolution.

Science.gov (United States)

Damiano, Luisa; Dumouchel, Paul

2018-01-01

Social robotics entertains a particular relationship with anthropomorphism, which it neither sees as a cognitive error, nor as a sign of immaturity. Rather it considers that this common human tendency, which is hypothesized to have evolved because it favored cooperation among early humans, can be used today to facilitate social interactions between humans and a new type of cooperative and interactive agents - social robots. This approach leads social robotics to focus research on the engineering of robots that activate anthropomorphic projections in users. The objective is to give robots "social presence" and "social behaviors" that are sufficiently credible for human users to engage in comfortable and potentially long-lasting relations with these machines. This choice of 'applied anthropomorphism' as a research methodology exposes the artifacts produced by social robotics to ethical condemnation: social robots are judged to be a "cheating" technology, as they generate in users the illusion of reciprocal social and affective relations. This article takes position in this debate, not only developing a series of arguments relevant to philosophy of mind, cognitive sciences, and robotic AI, but also asking what social robotics can teach us about anthropomorphism. On this basis, we propose a theoretical perspective that characterizes anthropomorphism as a basic mechanism of interaction, and rebuts the ethical reflections that a priori condemns "anthropomorphism-based" social robots. To address the relevant ethical issues, we promote a critical experimentally based ethical approach to social robotics, "synthetic ethics," which aims at allowing humans to use social robots for two main goals: self-knowledge and moral growth.

Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research

Directory of Open Access Journals (Sweden)

Maya Dimitrova

2015-12-01

Full Text Available The paper presents a novel analysis focused on showing that education is possible through robotic enhancement of the Gestalt processing in children with autism, which is not comparable to alternative educational methods such as demonstration and instruction provided solely by human tutors. The paper underlines the conceptualization of cognitive processing of holistic representations traditionally named in psychology as Gestalt structures, emerging in the process of human-robot interaction in educational settings. Two cognitive processes are proposed in the present study - bounding and unfolding - and their role in Gestalt emergence is outlined. The proposed theoretical approach explains novel findings of autistic perception and gives guidelines for design of robot-assistants to the rehabilitation process.

I Show You How I Like You: Emotional Human-Robot Interaction through Facial Expression and Tactile Stimulation

DEFF Research Database (Denmark)

Canamero, Dolores; Fredslund, Jacob

2001-01-01

We report work on a LEGO robot that displays different emotional expressions in response to physical stimulation, for the purpose of social interaction with humans. This is a first step toward our longer-term goal of exploring believable emotional exchanges to achieve plausible interaction...... with a simple robot. Drawing inspiration from theories of human basic emotions, we implemented several prototypical expressions in the robot's caricatured face and conducted experiments to assess the recognizability of these expressions...

A Human–Robot Interaction Perspective on Assistive and Rehabilitation Robotics

Directory of Open Access Journals (Sweden)

Philipp Beckerle

2017-05-01

Full Text Available Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing, and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human–robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed. Options to provide sensory user feedback that are currently missing from robotic devices are outlined. Parallels between device acceptance and affective computing are made. Furthermore, requirements for functional assessment protocols that relate to real-world tasks are discussed. In all topic areas, the design of human-oriented frameworks and methods is dominated by challenges related to the close interaction between the human and robotic device. This paper discusses the aforementioned aspects in order to open up new perspectives for future robotic solutions.

A Human–Robot Interaction Perspective on Assistive and Rehabilitation Robotics

Science.gov (United States)

Beckerle, Philipp; Salvietti, Gionata; Unal, Ramazan; Prattichizzo, Domenico; Rossi, Simone; Castellini, Claudio; Hirche, Sandra; Endo, Satoshi; Amor, Heni Ben; Ciocarlie, Matei; Mastrogiovanni, Fulvio; Argall, Brenna D.; Bianchi, Matteo

2017-01-01

Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing, and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human–robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed. Options to provide sensory user feedback that are currently missing from robotic devices are outlined. Parallels between device acceptance and affective computing are made. Furthermore, requirements for functional assessment protocols that relate to real-world tasks are discussed. In all topic areas, the design of human-oriented frameworks and methods is dominated by challenges related to the close interaction between the human and robotic device. This paper discusses the aforementioned aspects in order to open up new perspectives for future robotic solutions. PMID:28588473

Hands Off: Mentoring a Student-Led Robotics Team

Science.gov (United States)

Dolenc, Nathan R.; Mitchell, Claire E.; Tai, Robert H.

2016-01-01

Mentors play important roles in determining the working environment of out-of-school-time clubs. On robotics teams, they provide guidance in hopes that their protégés progress through an engineering process. This study examined how mentors on one robotics team who defined their mentoring style as "let the students do the work" navigated…

The relation between people's attitudes and anxiety towards robots in human-robot interaction

NARCIS (Netherlands)

de Graaf, M.M.A.; Ben Allouch, Soumaya

2013-01-01

This paper examines the relation between an interaction with a robot and peoples’ attitudes and emotion towards robots. In our study, participants have had an acquaintance talk with a social robot and both their general attitude and anxiety towards social robots were measured before and after the

Teaching Human Poses Interactively to a Social Robot

Science.gov (United States)

Gonzalez-Pacheco, Victor; Malfaz, Maria; Fernandez, Fernando; Salichs, Miguel A.

2013-01-01

The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher's explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth) -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR) system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics. PMID:24048336

Teaching Human Poses Interactively to a Social Robot

Directory of Open Access Journals (Sweden)

Miguel A. Salichs

2013-09-01

Full Text Available The main activity of social robots is to interact with people. In order to do that, the robot must be able to understand what the user is saying or doing. Typically, this capability consists of pre-programmed behaviors or is acquired through controlled learning processes, which are executed before the social interaction begins. This paper presents a software architecture that enables a robot to learn poses in a similar way as people do. That is, hearing its teacher’s explanations and acquiring new knowledge in real time. The architecture leans on two main components: an RGB-D (Red-, Green-, Blue- Depth -based visual system, which gathers the user examples, and an Automatic Speech Recognition (ASR system, which processes the speech describing those examples. The robot is able to naturally learn the poses the teacher is showing to it by maintaining a natural interaction with the teacher. We evaluate our system with 24 users who teach the robot a predetermined set of poses. The experimental results show that, with a few training examples, the system reaches high accuracy and robustness. This method shows how to combine data from the visual and auditory systems for the acquisition of new knowledge in a natural manner. Such a natural way of training enables robots to learn from users, even if they are not experts in robotics.

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

Intelligence for Human-Assistant Planetary Surface Robots

Science.gov (United States)

Hirsh, Robert; Graham, Jeffrey; Tyree, Kimberly; Sierhuis, Maarten; Clancey, William J.

2006-01-01

The central premise in developing effective human-assistant planetary surface robots is that robotic intelligence is needed. The exact type, method, forms and/or quantity of intelligence is an open issue being explored on the ERA project, as well as others. In addition to field testing, theoretical research into this area can help provide answers on how to design future planetary robots. Many fundamental intelligence issues are discussed by Murphy [2], including (a) learning, (b) planning, (c) reasoning, (d) problem solving, (e) knowledge representation, and (f) computer vision (stereo tracking, gestures). The new "social interaction/emotional" form of intelligence that some consider critical to Human Robot Interaction (HRI) can also be addressed by human assistant planetary surface robots, as human operators feel more comfortable working with a robot when the robot is verbally (or even physically) interacting with them. Arkin [3] and Murphy are both proponents of the hybrid deliberative-reasoning/reactive-execution architecture as the best general architecture for fully realizing robot potential, and the robots discussed herein implement a design continuously progressing toward this hybrid philosophy. The remainder of this chapter will describe the challenges associated with robotic assistance to astronauts, our general research approach, the intelligence incorporated into our robots, and the results and lessons learned from over six years of testing human-assistant mobile robots in field settings relevant to planetary exploration. The chapter concludes with some key considerations for future work in this area.

Effects of eye contact and iconic gestures on message retention in human-robot interaction

NARCIS (Netherlands)

Dijk, van E.T.; Torta, E.; Cuijpers, R.H.

2013-01-01

The effects of iconic gestures and eye contact on message retention in human-robot interaction were investigated in a series of experiments. A humanoid robot gave short verbal messages to participants, accompanied either by iconic gestures or no gestures while making eye contact with the participant

Natural Tasking of Robots Based on Human Interaction Cues (CD-ROM)

National Research Council Canada - National Science Library

Brooks, Rodney A

2005-01-01

...: 1 CD-ROM; 4 3/4 in.; 207 MB. ABSTRACT: We proposed developing the perceptual and intellectual abilities of robots so that in the field, war-fighters can interact with them in the same natural ways as they do with their human cohorts...

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.

Physical Human Robot Interaction for a Wall Mounting Robot - External Force Estimation

DEFF Research Database (Denmark)

Alonso García, Alejandro; Villarmarzo Arruñada, Noelia; Pedersen, Rasmus

2018-01-01

The use of collaborative robots enhances human capabilities, leading to better working conditions and increased productivity. In building construction, such robots are needed, among other tasks, to install large glass panels, where the robot takes care of the heavy lifting part of the job while...

Interactions between Humans and Robots

DEFF Research Database (Denmark)

Vlachos, Evgenios; Schärfe, Henrik

2013-01-01

), and explains the relationships and dependencies that exist between them. The four main factors that define the properties of a robot, and therefore the interaction, are distributed in two dimensions: (1) Intelligence (Control - Autonomy), and (2) Perspective (Tool - Medium). Based on these factors, we...

Anthropomorphic Robot Design and User Interaction Associated with Motion

Science.gov (United States)

Ellis, Stephen R.

2016-01-01

Though in its original concept a robot was conceived to have some human-like shape, most robots now in use have specific industrial purposes and do not closely resemble humans. Nevertheless, robots that resemble human form in some way have continued to be introduced. They are called anthropomorphic robots. The fact that the user interface to all robots is now highly mediated means that the form of the user interface is not necessarily connected to the robots form, human or otherwise. Consequently, the unique way the design of anthropomorphic robots affects their user interaction is through their general appearance and the way they move. These robots human-like appearance acts as a kind of generalized predictor that gives its operators, and those with whom they may directly work, the expectation that they will behave to some extent like a human. This expectation is especially prominent for interactions with social robots, which are built to enhance it. Often interaction with them may be mainly cognitive because they are not necessarily kinematically intricate enough for complex physical interaction. Their body movement, for example, may be limited to simple wheeled locomotion. An anthropomorphic robot with human form, however, can be kinematically complex and designed, for example, to reproduce the details of human limb, torso, and head movement. Because of the mediated nature of robot control, there remains in general no necessary connection between the specific form of user interface and the anthropomorphic form of the robot. But their anthropomorphic kinematics and dynamics imply that the impact of their design shows up in the way the robot moves. The central finding of this report is that the control of this motion is a basic design element through which the anthropomorphic form can affect user interaction. In particular, designers of anthropomorphic robots can take advantage of the inherent human-like movement to 1) improve the users direct manual control over

Human-like robots for space and hazardous environments

Science.gov (United States)

1994-01-01

The three year goal for the Kansas State USRA/NASA Senior Design team is to design and build a walking autonomous robotic rover. The rover should be capable of crossing rough terrain, traversing human made obstacles (such as stairs and doors), and moving through human and robot occupied spaces without collision. The rover is also to evidence considerable decision making ability, navigation, and path planning skills.

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.

The Age of Human-Robot Collaboration: Deep Sea Exploration

KAUST Repository

Khatib, Oussama

2018-01-18

The promise of oceanic discovery has intrigued scientists and explorers for centuries, whether to study underwater ecology and climate change, or to uncover natural resources and historic secrets buried deep at archaeological sites. Reaching these depth is imperative since factors such as pollution and deep-sea trawling increasingly threaten ecology and archaeological sites. These needs demand a system deploying human-level expertise at the depths, and yet remotely operated vehicles (ROVs) are inadequate for the task. To meet the challenge of dexterous operation at oceanic depths, in collaboration with KAUSTﾒs Red Sea Research Center and MEKA Robotics, Oussama Khatib and the team developed Ocean One, a bimanual humanoid robot that brings immediate and intuitive haptic interaction to oceanic environments. Introducing Ocean One, the haptic robotic avatar During this lecture, Oussama Khatib will talk about how teaming with the French Ministry of Cultureﾒs Underwater Archaeology Research Department, they deployed Ocean One in an expedition in the Mediterranean to Louis XIVﾒs flagship Lune, lying off the coast of Toulon at ninety-one meters. In the spring of 2016, Ocean One became the first robotic avatar to embody a humanﾒs presence at the seabed. Ocean Oneﾒs journey in the Mediterranean marks a new level of marine exploration: Much as past technological innovations have impacted society, Ocean Oneﾒs ability to distance humans physically from dangerous and unreachable work spaces while connecting their skills, intuition, and experience to the task promises to fundamentally alter remote work. Robotic avatars will search for and acquire materials, support equipment, build infrastructure, and perform disaster prevention and recovery operations - be it deep in oceans and mines, at mountain tops, or in space.

Ambulatory movements, team dynamics and interactions during robot-assisted surgery.

Science.gov (United States)

Ahmad, Nabeeha; Hussein, Ahmed A; Cavuoto, Lora; Sharif, Mohamed; Allers, Jenna C; Hinata, Nobuyuki; Ahmad, Basel; Kozlowski, Justen D; Hashmi, Zishan; Bisantz, Ann; Guru, Khurshid A

2016-07-01

To analyse ambulatory movements and team dynamics during robot-assisted surgery (RAS), and to investigate whether congestion of the physical space associated with robotic technology led to workflow challenges or predisposed to errors and adverse events. With institutional review board approval, we retrospectively reviewed 10 recorded robot-assisted radical prostatectomies in a single operating room (OR). The OR was divided into eight zones, and all movements were tracked and described in terms of start and end zones, duration, personnel and purpose. Movements were further classified into avoidable (can be eliminated/improved) and unavoidable (necessary for completion of the procedure). The mean operating time was 166 min, of which ambulation constituted 27 min (16%). A total of 2 896 ambulatory movements were identified (mean: 290 ambulatory movements/procedure). Most of the movements were procedure-related (31%), and were performed by the circulating nurse. We identified 11 main pathways in the OR; the heaviest traffic was between the circulating nurse zone, transit zone and supply-1 zone. A total of 50% of ambulatory movements were found to be avoidable. More than half of the movements during RAS can be eliminated with an improved OR setting. More studies are needed to design an evidence-based OR layout that enhances access, workflow and patient safety. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

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

Learning compliant manipulation through kinesthetic and tactile human-robot interaction.

Science.gov (United States)

Kronander, Klas; Billard, Aude

2014-01-01

Robot Learning from Demonstration (RLfD) has been identified as a key element for making robots useful in daily lives. A wide range of techniques has been proposed for deriving a task model from a set of demonstrations of the task. Most previous works use learning to model the kinematics of the task, and for autonomous execution the robot then relies on a stiff position controller. While many tasks can and have been learned this way, there are tasks in which controlling the position alone is insufficient to achieve the goals of the task. These are typically tasks that involve contact or require a specific response to physical perturbations. The question of how to adjust the compliance to suit the need of the task has not yet been fully treated in Robot Learning from Demonstration. In this paper, we address this issue and present interfaces that allow a human teacher to indicate compliance variations by physically interacting with the robot during task execution. We validate our approach in two different experiments on the 7 DoF Barrett WAM and KUKA LWR robot manipulators. Furthermore, we conduct a user study to evaluate the usability of our approach from a non-roboticists perspective.

You Can Leave Your Head On: Attention Management and Turn-Taking in Multi-party Interaction with a Virtual Human/Robot Duo

NARCIS (Netherlands)

Linssen, Jeroen; Berkhoff, Meike; Bode, Max; Rens, Eduard; Theune, Mariet; Wiltenburg, Daan; Beskow, Jonas; Peters, Christopher; Castellano, Ginevra; O'Sullivan, Carol; Leite, Iolanda; Kopp, Stefan

In two small studies, we investigated how a virtual human/ robot duo can complement each other in joint interaction with one or more users. The robot takes care of turn management while the virtual human draws attention to the robot. Our results show that having the virtual human address the robot,

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.

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.

Socially Impaired Robots: Human Social Disorders and Robots' Socio-Emotional Intelligence

OpenAIRE

Vitale, Jonathan; Williams, Mary-Anne; Johnston, Benjamin

2016-01-01

Social robots need intelligence in order to safely coexist and interact with humans. Robots without functional abilities in understanding others and unable to empathise might be a societal risk and they may lead to a society of socially impaired robots. In this work we provide a survey of three relevant human social disorders, namely autism, psychopathy and schizophrenia, as a means to gain a better understanding of social robots' future capability requirements. We provide evidence supporting...

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.

Human-Agent Teaming for Multi-Robot Control: A Literature Review

Science.gov (United States)

2013-02-01

advent of the Goggle driverless car , autonomous farm equipment, and unmanned commercial aircraft (Mosher, 2012). The inexorable trend towards...because a robot cannot be automated to navigate in difficult terrain. However, this high ratio will not be sustainable if large numbers of autonomous ...Parasuraman et al., 2007). 3.5 RoboLeader Past research indicates that autonomous cooperation between robots can improve the performance of the human

The importance of shared mental models and shared situation awareness for transforming robots from tools to teammates

Science.gov (United States)

Ososky, Scott; Schuster, David; Jentsch, Florian; Fiore, Stephen; Shumaker, Randall; Lebiere, Christian; Kurup, Unmesh; Oh, Jean; Stentz, Anthony

2012-06-01

Current ground robots are largely employed via tele-operation and provide their operators with useful tools to extend reach, improve sensing, and avoid dangers. To move from robots that are useful as tools to truly synergistic human-robot teaming, however, will require not only greater technical capabilities among robots, but also a better understanding of the ways in which the principles of teamwork can be applied from exclusively human teams to mixed teams of humans and robots. In this respect, a core characteristic that enables successful human teams to coordinate shared tasks is their ability to create, maintain, and act on a shared understanding of the world and the roles of the team and its members in it. The team performance literature clearly points towards two important cornerstones for shared understanding of team members: mental models and situation awareness. These constructs have been investigated as products of teams as well; amongst teams, they are shared mental models and shared situation awareness. Consequently, we are studying how these two constructs can be measured and instantiated in human-robot teams. In this paper, we report results from three related efforts that are investigating process and performance outcomes for human robot teams. Our investigations include: (a) how human mental models of tasks and teams change whether a teammate is human, a service animal, or an advanced automated system; (b) how computer modeling can lead to mental models being instantiated and used in robots; (c) how we can simulate the interactions between human and future robotic teammates on the basis of changes in shared mental models and situation assessment.

Robot - a member of (re)habilitation team

OpenAIRE

Komazec Zoran; Lemajić-Komazec Slobodanka; Golubović Špela; Mikov Aleksandra; Krasnik Rastislava

2012-01-01

Introduction. The rehabilitation process involves a whole team of experts who participate in it over a long period of time. Development of Robotics and its Application in Medicine. The Intensive development of science and technology has made it possible to design a number of robots which are used for therapeutic purposes and participate in the rehabilitation process. Robotics in Medical Rehabilitation. During the long history of technological development of mankind, a number of conceptu...

Scalable Task Assignment for Heterogeneous Multi-Robot Teams

Directory of Open Access Journals (Sweden)

Paula García

2013-02-01

Full Text Available This work deals with the development of a dynamic task assignment strategy for heterogeneous multi-robot teams in typical real world scenarios. The strategy must be efficiently scalable to support problems of increasing complexity with minimum designer intervention. To this end, we have selected a very simple auction-based strategy, which has been implemented and analysed in a multi-robot cleaning problem that requires strong coordination and dynamic complex subtask organization. We will show that the selection of a simple auction strategy provides a linear computational cost increase with the number of robots that make up the team and allows the solving of highly complex assignment problems in dynamic conditions by means of a hierarchical sub-auction policy. To coordinate and control the team, a layered behaviour-based architecture has been applied that allows the reusing of the auction-based strategy to achieve different coordination levels.

Speech-Based Human and Service Robot Interaction: An Application for Mexican Dysarthric People

Directory of Open Access Journals (Sweden)

Santiago Omar Caballero Morales

2013-01-01

Full Text Available Dysarthria is a motor speech disorder due to weakness or poor coordination of the speech muscles. This condition can be caused by a stroke, traumatic brain injury, or by a degenerative neurological disease. Commonly, people with this disorder also have muscular dystrophy, which restricts their use of switches or keyboards for communication or control of assistive devices (i.e., an electric wheelchair or a service robot. In this case, speech recognition is an attractive alternative for interaction and control of service robots, despite the difficulty of achieving robust recognition performance. In this paper we present a speech recognition system for human and service robot interaction for Mexican Spanish dysarthric speakers. The core of the system consisted of a Speaker Adaptive (SA recognition system trained with normal-speech. Features such as on-line control of the language model perplexity and the adding of vocabulary, contribute to high recognition performance. Others, such as assessment and text-to-speech (TTS synthesis, contribute to a more complete interaction with a service robot. Live tests were performed with two mild dysarthric speakers, achieving recognition accuracies of 90–95% for spontaneous speech and 95–100% of accomplished simulated service robot tasks.

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

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.

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.

Robotics Team Lights Up New Year's Eve

Science.gov (United States)

LeBlanc, Cheryl

2011-01-01

A robotics team from Muncie, Indiana--the PhyXTGears--is made up of high school students from throughout Delaware County. The group formed as part of the FIRST Robotics program (For Inspiration and Recognition of Science and Technology), an international program founded by inventor Dean Kamen in which students work with professional engineers and…

The Relationship between Robot's Nonverbal Behaviour and Human's Likability Based on Human's Personality.

Science.gov (United States)

Thepsoonthorn, Chidchanok; Ogawa, Ken-Ichiro; Miyake, Yoshihiro

2018-05-30

At current state, although robotics technology has been immensely developed, the uncertainty to completely engage in human-robot interaction is still growing among people. Many current studies then started to concern about human factors that might influence human's likability like human's personality, and found that compatibility between human's and robot's personality (expressions of personality characteristics) can enhance human's likability. However, it is still unclear whether specific means and strategy of robot's nonverbal behaviours enhances likability from human with different personality traits and whether there is a relationship between robot's nonverbal behaviours and human's likability based on human's personality. In this study, we investigated and focused on the interaction via gaze and head nodding behaviours (mutual gaze convergence and head nodding synchrony) between introvert/extravert participants and robot in two communication strategies (Backchanneling and Turn-taking). Our findings reveal that the introvert participants are positively affected by backchanneling in robot's head nodding behaviour, which results in substantial head nodding synchrony whereas the extravert participants are positively influenced by turn-taking in gaze behaviour, which leads to significant mutual gaze convergence. This study demonstrates that there is a relationship between robot's nonverbal behaviour and human's likability based on human's personality.

Sustaining Emotional Communication when Interacting with an Android Robot

DEFF Research Database (Denmark)

Vlachos, Evgenios

The more human-like a robot appears and acts, the more users will have the belief of communicating with a human partner rather than with an artificial entity. However, current robotic technology displays limitations on the design of the facial interface and on the design of believable Human...... of an android related to its actions, perception and intelligence, or failure to identify which robot type is qualified to perform a specific task, might lead to disruption of HRI. This study is concerned with the problem of sustaining emotional communication when interacting with an android social robot......-ended evaluation method pertaining to the interpretation of Android facial expressions (g) a study on how users’ perception and attitude can change after direct interaction with a robot, (h) a study on how androids can maintain the focus of attention during short-term dyadic interactions, and (i) a state...

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....

College of Engineering team to build battlefield robots for 2010 competition

OpenAIRE

Mackay, Steven D.

2010-01-01

The roving, walking robotic soldiers of the "Terminator" films are becoming less sci-fi, and more certain future every day. Now, a team of robotics researchers from the Virginia Tech College of Engineering will build a team of fully autonomous cooperative battle-ready robots as part of a 2010 international war games challenge that could spur real-life battle bots.

COMPARISON OF CLASSICAL AND INTERACTIVE MULTI-ROBOT EXPLORATION STRATEGIES IN POPULATED ENVIRONMENTS

Directory of Open Access Journals (Sweden)

Nassim Kalde

2015-06-01

Full Text Available Multi-robot exploration consists in coordinating robots for mapping an unknown environment. It raises several issues concerning task allocation, robot control, path planning and communication. We study exploration in populated environments, in which pedestrian flows can severely impact performances. However, humans have adaptive skills for taking advantage of these flows while moving. Therefore, in order to exploit these human abilities, we propose a novel exploration strategy that explicitly allows for human-robot interactions. Our model for exploration in populated environments combines the classical frontier-based strategy with our interactive approach. We implement interactions where robots can locally choose a human guide to follow and define a parametric heuristic to balance interaction and frontier assignments. Finally, we evaluate to which extent human presence impacts our exploration model in terms of coverage ratio, travelled distance and elapsed time to completion.

Views from Within a Narrative: Evaluating Long-Term Human-Robot Interaction in a Naturalistic Environment Using Open-Ended Scenarios.

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Syrdal, Dag Sverre; Dautenhahn, Kerstin; Koay, Kheng Lee; Ho, Wan Ching

2014-01-01

This article describes the prototyping of human-robot interactions in the University of Hertfordshire (UH) Robot House. Twelve participants took part in a long-term study in which they interacted with robots in the UH Robot House once a week for a period of 10 weeks. A prototyping method using the narrative framing technique allowed participants to engage with the robots in episodic interactions that were framed using narrative to convey the impression of a continuous long-term interaction. The goal was to examine how participants responded to the scenarios and the robots as well as specific robot behaviours, such as agent migration and expressive behaviours. Evaluation of the robots and the scenarios were elicited using several measures, including the standardised System Usability Scale, an ad hoc Scenario Acceptance Scale, as well as single-item Likert scales, open-ended questionnaire items and a debriefing interview. Results suggest that participants felt that the use of this prototyping technique allowed them insight into the use of the robot, and that they accepted the use of the robot within the scenario.

Human-robot interaction: kinematics and muscle activity inside a powered compliant knee exoskeleton.

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Knaepen, Kristel; Beyl, Pieter; Duerinck, Saartje; Hagman, Friso; Lefeber, Dirk; Meeusen, Romain

2014-11-01

Until today it is not entirely clear how humans interact with automated gait rehabilitation devices and how we can, based on that interaction, maximize the effectiveness of these exoskeletons. The goal of this study was to gain knowledge on the human-robot interaction, in terms of kinematics and muscle activity, between a healthy human motor system and a powered knee exoskeleton (i.e., KNEXO). Therefore, temporal and spatial gait parameters, human joint kinematics, exoskeleton kinetics and muscle activity during four different walking trials in 10 healthy male subjects were studied. Healthy subjects can walk with KNEXO in patient-in-charge mode with some slight constraints in kinematics and muscle activity primarily due to inertia of the device. Yet, during robot-in-charge walking the muscular constraints are reversed by adding positive power to the leg swing, compensating in part this inertia. Next to that, KNEXO accurately records and replays the right knee kinematics meaning that subject-specific trajectories can be implemented as a target trajectory during assisted walking. No significant differences in the human response to the interaction with KNEXO in low and high compliant assistance could be pointed out. This is in contradiction with our hypothesis that muscle activity would decrease with increasing assistance. It seems that the differences between the parameter settings of low and high compliant control might not be sufficient to observe clear effects in healthy subjects. Moreover, we should take into account that KNEXO is a unilateral, 1 degree-of-freedom device.

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

Spatiotemporal Aspects of Engagement during Dialogic Storytelling Child–Robot Interaction

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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

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

Mobile Robots in Human Environments

DEFF Research Database (Denmark)

Svenstrup, Mikael

intelligent mobile robotic devices capable of being a more natural and sociable actor in a human environment. More specific the emphasis is on safe and natural motion and navigation issues. First part of the work focus on developing a robotic system, which estimates human interest in interacting......, lawn mowers, toy pets, or as assisting technologies for care giving. If we want robots to be an even larger and more integrated part of our every- day environments, they need to become more intelligent, and behave safe and natural to the humans in the environment. This thesis deals with making...... as being able to navigate safely around one person, the robots must also be able to navigate in environments with more people. This can be environments such as pedestrian streets, hospital corridors, train stations or airports. The developed human-aware navigation strategy is enhanced to formulate...

Mobile Robotic Teams Applied to Precision Agriculture

Energy Technology Data Exchange (ETDEWEB)

Anderson, Matthew Oley; Kinoshita, Robert Arthur; Mckay, Mark D; Willis, Walter David; Gunderson, R.W.; Flann, N.S.

1999-04-01

The Idaho National Engineering and Environmental Laboratory (INEEL) and Utah State University’s Center for Self-Organizing and Intelligent Systems (CSOIS) have developed a team of autonomous robotic vehicles applicable to precision agriculture. A unique technique has been developed to plan, coordinate, and optimize missions in large structured environments for these autonomous vehicles in realtime. Two generic tasks are supported: 1) Driving to a precise location, and 2) Sweeping an area while activating on-board equipment. Sensor data and task achievement data is shared among the vehicles enabling them to cooperatively adapt to changing environmental, vehicle, and task conditions. This paper discusses the development of the autonomous robotic team, details of the mission-planning algorithm, and successful field demonstrations at the INEEL.

Mobile Robotic Teams Applied to Precision Agriculture

Energy Technology Data Exchange (ETDEWEB)

M.D. McKay; M.O. Anderson; N.S. Flann (Utah State University); R.A. Kinoshita; R.W. Gunderson; W.D. Willis (INEEL)

1999-04-01

The Idaho National Engineering and Environmental Laboratory (INEEL) and Utah State University�s Center for Self-Organizing and Intelligent Systems (CSOIS) have developed a team of autonomous robotic vehicles applicable to precision agriculture. A unique technique has been developed to plan, coordinate, and optimize missions in large structured environments for these autonomous vehicles in real-time. Two generic tasks are supported: 1) Driving to a precise location, and 2) Sweeping an area while activating on-board equipment. Sensor data and task achievement data is shared among the vehicles enabling them to cooperatively adapt to changing environmental, vehicle, and task conditions. This paper discusses the development of the autonomous robotic team, details of the mission-planning algorithm, and successful field demonstrations at the INEEL.

Vocal Interactivity in-and-between Humans, Animals and Robots

Directory of Open Access Journals (Sweden)

Roger K Moore

2016-10-01

Full Text Available Almost all animals exploit vocal signals for a range of ecologically-motivated purposes: detecting predators prey and marking territory, expressing emotions, establishing social relations and sharing information. Whether it is a bird raising an alarm, a whale calling to potential partners,a dog responding to human commands, a parent reading a story with a child, or a business-person accessing stock prices using emph{Siri}, vocalisation provides a valuable communication channel through which behaviour may be coordinated and controlled, and information may be distributed and acquired.Indeed, the ubiquity of vocal interaction has led to research across an extremely diverse array of fields, from assessing animal welfare, to understanding the precursors of human language, to developing voice-based human-machine interaction. Opportunities for cross-fertilisation between these fields abound; for example, using artificial cognitive agents to investigate contemporary theories of language grounding, using machine learning to analyse different habitats or adding vocal expressivity to the next generation of language-enabled autonomous social agents. However, much of the research is conducted within well-defined disciplinary boundaries, and many fundamental issues remain. This paper attempts to redress the balance by presenting a comparative review of vocal interaction within-and-between humans, animals and artificial agents (such as robots, and it identifies a rich set of open research questions that may benefit from an inter-disciplinary analysis.

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.

Hand Gesture Modeling and Recognition for Human and Robot Interactive Assembly Using Hidden Markov Models

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Fei Chen

2015-04-01

Full Text Available Gesture recognition is essential for human and robot collaboration. Within an industrial hybrid assembly cell, the performance of such a system significantly affects the safety of human workers. This work presents an approach to recognizing hand gestures accurately during an assembly task while in collaboration with a robot co-worker. We have designed and developed a sensor system for measuring natural human-robot interactions. The position and rotation information of a human worker's hands and fingertips are tracked in 3D space while completing a task. A modified chain-code method is proposed to describe the motion trajectory of the measured hands and fingertips. The Hidden Markov Model (HMM method is adopted to recognize patterns via data streams and identify workers' gesture patterns and assembly intentions. The effectiveness of the proposed system is verified by experimental results. The outcome demonstrates that the proposed system is able to automatically segment the data streams and recognize the gesture patterns thus represented with a reasonable accuracy ratio.

Human - Robot Proximity

DEFF Research Database (Denmark)

Nickelsen, Niels Christian Mossfeldt

The media and political/managerial levels focus on the opportunities to re-perform Denmark through digitization. Feeding assistive robotics is a welfare technology, relevant to citizens with low or no function in their arms. Despite national dissemination strategies, it proves difficult to recruit...... the study that took place as multi-sited ethnography at different locations in Denmark and Sweden. Based on desk research, observation of meals and interviews I examine socio-technological imaginaries and their practical implications. Human - robotics interaction demands engagement and understanding...

Modelling Engagement in Multi-Party Conversations : Data-Driven Approaches to Understanding Human-Human Communication Patterns for Use in Human-Robot Interactions

OpenAIRE

Oertel, Catharine

2016-01-01

The aim of this thesis is to study human-human interaction in order to provide virtual agents and robots with the capability to engage into multi-party-conversations in a human-like-manner. The focus lies with the modelling of conversational dynamics and the appropriate realization of multi-modal feedback behaviour. For such an undertaking, it is important to understand how human-human communication unfolds in varying contexts and constellations over time. To this end, multi-modal human-human...

Sharing skills: using augmented reality for human-robot collaboration

Science.gov (United States)

Giesler, Bjorn; Steinhaus, Peter; Walther, Marcus; Dillmann, Ruediger

2004-05-01

Both stationary 'industrial' and autonomous mobile robots nowadays pervade many workplaces, but human-friendly interaction with them is still very much an experimental subject. One of the reasons for this is that computer and robotic systems are very bad at performing certain tasks well and robust. A prime example is classification of sensor readings: Which part of a 3D depth image is the cup, which the saucer, which the table? These are tasks that humans excel at. To alleviate this problem, we propose a team approah, wherein the robot records sensor data and uses an Augmented-Reality (AR) system to present the data to the user directly in the 3D environment. The user can then perform classification decisions directly on the data by pointing, gestures and speech commands. After the classification has been performed by the user, the robot takes the classified data and matches it to its environment model. As a demonstration of this approach, we present an initial system for creating objects on-the-fly in the environment model. A rotating laser scanner is used to capture a 3D snapshot of the environment. This snapshot is presented to the user as an overlay over his view of the scene. The user classifies unknown objects by pointing at them. The system segments the snapshot according to the user's indications and presents the results of segmentation back to the user, who can then inspect, correct and enhance them interactively. After a satisfying result has been reached, the laser-scanner can take more snapshots from other angles and use the previous segmentation hints to construct a 3D model of the object.

Cognitive Coordination for Cooperative Multi-Robot Teamwork

NARCIS (Netherlands)

Wei, C.

2015-01-01

Multi-robot teams have potential advantages over a single robot. Robots in a team can serve different functionalities, so a team of robots can be more efficient, robust and reliable than a single robot. In this dissertation, we are in particular interested in human level intelligent multi-robot

Human guidance of mobile robots in complex 3D environments using smart glasses

Science.gov (United States)

Kopinsky, Ryan; Sharma, Aneesh; Gupta, Nikhil; Ordonez, Camilo; Collins, Emmanuel; Barber, Daniel

2016-05-01

In order for humans to safely work alongside robots in the field, the human-robot (HR) interface, which enables bi-directional communication between human and robot, should be able to quickly and concisely express the robot's intentions and needs. While the robot operates mostly in autonomous mode, the human should be able to intervene to effectively guide the robot in complex, risky and/or highly uncertain scenarios. Using smart glasses such as Google Glass∗, we seek to develop an HR interface that aids in reducing interaction time and distractions during interaction with the robot.

Robotics and nuclear power. Report by the Technology Transfer Robotics Task Team

International Nuclear Information System (INIS)

1985-06-01

A task team was formed at the request of the Department of Energy to evaluate and assess technology development needed for advanced robotics in the nuclear industry. The mission of these technologies is to provide the nuclear industry with the support for the application of advanced robotics to reduce nuclear power generating costs and enhance the safety of the personnel in the industry. The investigation included robotic and teleoperated systems. A robotic system is defined as a reprogrammable, multifunctional manipulator designed to move materials, parts, tools, or specialized devices through variable programmed motions for the performance of a variety of tasks. A teleoperated system includes an operator who remotely controls the system by direct viewing or through a vision system

Social Moments: A Perspective on Interaction for Social Robotics

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Gautier Durantin

2017-06-01

Full Text Available During a social interaction, events that happen at different timescales can indicate social meanings. In order to socially engage with humans, robots will need to be able to comprehend and manipulate the social meanings that are associated with these events. We define social moments as events that occur within a social interaction and which can signify a pragmatic or semantic meaning. A challenge for social robots is recognizing social moments that occur on short timescales, which can be on the order of 102 ms. In this perspective, we propose that understanding the range and roles of social moments in a social interaction and implementing social micro-abilities—the abilities required to engage in a timely manner through social moments—is a key challenge for the field of human robot interaction (HRI to enable effective social interactions and social robots. In particular, it is an open question how social moments can acquire their associated meanings. Practically, the implementation of these social micro-abilities presents engineering challenges for the fields of HRI and social robotics, including performing processing of sensors and using actuators to meet fast timescales. We present a key challenge of social moments as integration of social stimuli across multiple timescales and modalities. We present the neural basis for human comprehension of social moments and review current literature related to social moments and social micro-abilities. We discuss the requirements for social micro-abilities, how these abilities can enable more natural social robots, and how to address the engineering challenges associated with social moments.

Textile Pressure Mapping Sensor for Emotional Touch Detection in Human-Robot Interaction

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Bo Zhou

2017-11-01

Full Text Available In this paper, we developed a fully textile sensing fabric for tactile touch sensing as the robot skin to detect human-robot interactions. The sensor covers a 20-by-20 cm 2 area with 400 sensitive points and samples at 50 Hz per point. We defined seven gestures which are inspired by the social and emotional interactions of typical people to people or pet scenarios. We conducted two groups of mutually blinded experiments, involving 29 participants in total. The data processing algorithm first reduces the spatial complexity to frame descriptors, and temporal features are calculated through basic statistical representations and wavelet analysis. Various classifiers are evaluated and the feature calculation algorithms are analyzed in details to determine each stage and segments’ contribution. The best performing feature-classifier combination can recognize the gestures with a 93 . 3 % accuracy from a known group of participants, and 89 . 1 % from strangers.

Textile Pressure Mapping Sensor for Emotional Touch Detection in Human-Robot Interaction.

Science.gov (United States)

Zhou, Bo; Altamirano, Carlos Andres Velez; Zurian, Heber Cruz; Atefi, Seyed Reza; Billing, Erik; Martinez, Fernando Seoane; Lukowicz, Paul

2017-11-09

In this paper, we developed a fully textile sensing fabric for tactile touch sensing as the robot skin to detect human-robot interactions. The sensor covers a 20-by-20 cm 2 area with 400 sensitive points and samples at 50 Hz per point. We defined seven gestures which are inspired by the social and emotional interactions of typical people to people or pet scenarios. We conducted two groups of mutually blinded experiments, involving 29 participants in total. The data processing algorithm first reduces the spatial complexity to frame descriptors, and temporal features are calculated through basic statistical representations and wavelet analysis. Various classifiers are evaluated and the feature calculation algorithms are analyzed in details to determine each stage and segments' contribution. The best performing feature-classifier combination can recognize the gestures with a 93 . 3 % accuracy from a known group of participants, and 89 . 1 % from strangers.

Eyeblink Synchrony in Multimodal Human-Android Interaction.

Science.gov (United States)

Tatsukawa, Kyohei; Nakano, Tamami; Ishiguro, Hiroshi; Yoshikawa, Yuichiro

2016-12-23

As the result of recent progress in technology of communication robot, robots are becoming an important social partner for humans. Behavioral synchrony is understood as an important factor in establishing good human-robot relationships. In this study, we hypothesized that biasing a human's attitude toward a robot changes the degree of synchrony between human and robot. We first examined whether eyeblinks were synchronized between a human and an android in face-to-face interaction and found that human listeners' eyeblinks were entrained to android speakers' eyeblinks. This eyeblink synchrony disappeared when the android speaker spoke while looking away from the human listeners but was enhanced when the human participants listened to the speaking android while touching the android's hand. These results suggest that eyeblink synchrony reflects a qualitative state in human-robot interactions.

Digital twins of human robot collaboration in a production setting

DEFF Research Database (Denmark)

Malik, Ali Ahmad; Bilberg, Arne

2018-01-01

This paper aims to present a digital twin framework to support the design, build and control of human-machine cooperation. In this study, computer simulations are used to develop a digital counterpart of a human-robot collaborative work environment for assembly work. The digital counterpart remains...... updated during the life cycle of the production system by continuously mirroring the physical system for quick and safe embed for continuous improvements. The case of a manufacturing company with human-robot work teams is presented for developing and validating the digital twin framework....

Ethorobotics: A New Approach to Human-Robot Relationship

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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.

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

I Show You How I Like You: Emotional Human-Robot Interaction through Facial Expression and Tactile Stimulation

DEFF Research Database (Denmark)

Fredslund, Jakob; Cañamero, Lola D.

2001-01-01

We report work on a LEGO robot capable of displaying several emo- tional expressions in response to physical contact. Our motivation has been to explore believable emotional exchanges to achieve plausible interaction with a simple robot. We have worked toward this goal in two ways. First......, acknowledging the importance of physical manipulation in children's inter- actions, interaction with the robot is through tactile stimulation; the various kinds of stimulation that can elicit the robot's emotions are grounded in a model of emotion activation based on different stimulation patterns. Sec- ond......, emotional states need to be clearly conveyed. We have drawn inspira- tion from theories of human basic emotions with associated universal facial expressions, which we have implemented in a caricaturized face. We have conducted experiments on both children and adults to assess the recogniz- ability...

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.

Student teams maneuver robots in qualifying match at regional robotic competition at KSC

Science.gov (United States)

1999-01-01

All four robots, maneuvered by student teams behind protective walls, converge on a corner of the playing field during qualifying matches of the 1999 Southeastern Regional robotic competition at Kennedy Space Center Visitor Complex . Thirty schools from around the country have converged at KSC for the event that pits gladiator robots against each other in an athletic-style competition. The robots have to retrieve pillow- like disks from the floor, as well as climb onto the platform (with flags) and raise the cache of pillows to a height of eight feet. KSC is hosting the event being sponsored by the nonprofit organization For Inspiration and Recognition of Science and Technology, known as FIRST. The FIRST robotics competition is designed to provide students with a hands-on, inside look at engineering and other professional careers.

Accompany: Acceptable robotiCs COMPanions for AgeiNG Years - Multidimensional aspects of human-system interactions

OpenAIRE

Amirabdollahian F.; Op Den Akker R.; Bedaf S.; Bormann R.; Draper H.; Evers V.; Gelderblom G.J.; Ruiz C.G.; Hewson D.; Hu N.

2013-01-01

With changes in life expectancy across the world, technologies enhancing well-being of individuals, specifically for older people, are subject to a new stream of research and development. In this paper we present the ACCOMPANY project, a pan-European project which focuses on home companion technologies. The projects aims to progress beyond the state of the art in multiple areas such as empathic and social human-robot interaction, robot learning and memory visualisation, monitoring persons and...

A Multimodal Emotion Detection System during Human-Robot Interaction

Science.gov (United States)

Alonso-Martín, Fernando; Malfaz, María; Sequeira, João; Gorostiza, Javier F.; Salichs, Miguel A.

2013-01-01

In this paper, a multimodal user-emotion detection system for social robots is presented. This system is intended to be used during human–robot interaction, and it is integrated as part of the overall interaction system of the robot: the Robotics Dialog System (RDS). Two modes are used to detect emotions: the voice and face expression analysis. In order to analyze the voice of the user, a new component has been developed: Gender and Emotion Voice Analysis (GEVA), which is written using the Chuck language. For emotion detection in facial expressions, the system, Gender and Emotion Facial Analysis (GEFA), has been also developed. This last system integrates two third-party solutions: Sophisticated High-speed Object Recognition Engine (SHORE) and Computer Expression Recognition Toolbox (CERT). Once these new components (GEVA and GEFA) give their results, a decision rule is applied in order to combine the information given by both of them. The result of this rule, the detected emotion, is integrated into the dialog system through communicative acts. Hence, each communicative act gives, among other things, the detected emotion of the user to the RDS so it can adapt its strategy in order to get a greater satisfaction degree during the human–robot dialog. Each of the new components, GEVA and GEFA, can also be used individually. Moreover, they are integrated with the robotic control platform ROS (Robot Operating System). Several experiments with real users were performed to determine the accuracy of each component and to set the final decision rule. The results obtained from applying this decision rule in these experiments show a high success rate in automatic user emotion recognition, improving the results given by the two information channels (audio and visual) separately. PMID:24240598

Two-Stage Hidden Markov Model in Gesture Recognition for Human Robot Interaction

Directory of Open Access Journals (Sweden)

Nhan Nguyen-Duc-Thanh

2012-07-01

Full Text Available Hidden Markov Model (HMM is very rich in mathematical structure and hence can form the theoretical basis for use in a wide range of applications including gesture representation. Most research in this field, however, uses only HMM for recognizing simple gestures, while HMM can definitely be applied for whole gesture meaning recognition. This is very effectively applicable in Human-Robot Interaction (HRI. In this paper, we introduce an approach for HRI in which not only the human can naturally control the robot by hand gesture, but also the robot can recognize what kind of task it is executing. The main idea behind this method is the 2-stages Hidden Markov Model. The 1st HMM is to recognize the prime command-like gestures. Based on the sequence of prime gestures that are recognized from the 1st stage and which represent the whole action, the 2nd HMM plays a role in task recognition. Another contribution of this paper is that we use the output Mixed Gaussian distribution in HMM to improve the recognition rate. In the experiment, we also complete a comparison of the different number of hidden states and mixture components to obtain the optimal one, and compare to other methods to evaluate this performance.

A receptionist robot for Brazilian people: study on interaction involving illiterates

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Trovato Gabriele

2017-04-01

Full Text Available The receptionist job, consisting in providing useful indications to visitors in a public office, is one possible employment of social robots. The design and the behaviour of robots expected to be integrated in human societies are crucial issues, and they are dependent on the culture and society in which the robot should be deployed. We study the factors that could be used in the design of a receptionist robot in Brazil, a country with a mix of races and considerable gaps in economic and educational level. This inequality results in the presence of functional illiterate people, unable to use reading, writing and numeracy skills. We invited Brazilian people, including a group of functionally illiterate subjects, to interact with two types of receptionists differing in physical appearance (agent v mechanical robot and in the sound of the voice (human like v mechanical. Results gathered during the interactions point out a preference for the agent, for the human-like voice and a more intense reaction to stimuli by illiterates. These results provide useful indications that should be considered when designing a receptionist robot, as well as insights on the effect of illiteracy in the interaction.

Social robotics to help children with autism in their interactions through imitation

Directory of Open Access Journals (Sweden)

Pennazio Valentina

2017-06-01

Full Text Available This article aims to reflect on the main variables that make social robotics efficient in an educational and rehabilitative intervention. Social robotics is based on imitation, and the study is designed for children affected by profound autism, aiming for the development of their social interactions. Existing research, at the national and international levels, shows how children with autism can interact more easily with a robotic companion rather than a human peer, considering its less complex and more predictable actions. This contribution also highlights how using robotic platforms helps in teaching children with autism basic social abilities, imitation, communication and interaction; this encourages them to transfer the learned abilities to human interactions with both adults and peers, through human–robot imitative modelling. The results of a pilot study conducted in a kindergarten school in the Liguria region are presented. The study included applying a robotic system, at first in a dyadic child–robot relation, then in a triadic one that also included another child, with the aim of eliciting social and imitative abilities in a child with profound autism.

A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction

Science.gov (United States)

2011-10-01

directly affects the willingness of people to accept robot -produced information, follow robots ’ suggestions, and thus benefit from the advantages inherent...perceived complexity of operation). Consequently, if the perceived risk of using the robot exceeds its perceived benefit , practical operators almost...necessary presence of a human caregiver (Graf, Hans, & Schraft, 2004). Other robotic devices, such as wheelchairs (Yanco, 2001) and exoskeletons (e.g

From Child-Robot Interaction to Child-Robot-Therapist Interaction: A Case Study in Autism

Directory of Open Access Journals (Sweden)

I. Giannopulu

2012-01-01

Full Text Available Troubles in social communication as well as deficits in the cognitive treatment of emotions are supposed to be a fundamental part of autism. We present a case study based on multimodal interaction between a mobile robot and a child with autism in spontaneous, free game play. This case study tells us that the robot mediates the interaction between the autistic child and therapist once the robot-child interaction has been established. In addition, the child uses the robot as a mediator to express positive emotion playing with the therapist. It is thought that the three-pronged interaction i.e., child-robot-therapist could better facilitate the transfer of social and emotional abilities to real life settings. Robot therapy has a high potential to improve the condition of brain activity in autistic children.

An Interactive Astronaut-Robot System with Gesture Control

Directory of Open Access Journals (Sweden)

Jinguo Liu

2016-01-01

Full Text Available Human-robot interaction (HRI plays an important role in future planetary exploration mission, where astronauts with extravehicular activities (EVA have to communicate with robot assistants by speech-type or gesture-type user interfaces embedded in their space suits. This paper presents an interactive astronaut-robot system integrating a data-glove with a space suit for the astronaut to use hand gestures to control a snake-like robot. Support vector machine (SVM is employed to recognize hand gestures and particle swarm optimization (PSO algorithm is used to optimize the parameters of SVM to further improve its recognition accuracy. Various hand gestures from American Sign Language (ASL have been selected and used to test and validate the performance of the proposed system.

Cognitive neuroscience robotics A synthetic approaches to human understanding

CERN Document Server

Ishiguro, Hiroshi; Asada, Minoru; Osaka, Mariko; Fujikado, Takashi

2016-01-01

Cognitive Neuroscience Robotics is the first introductory book on this new interdisciplinary area. This book consists of two volumes, the first of which, Synthetic Approaches to Human Understanding, advances human understanding from a robotics or engineering point of view. The second, Analytic Approaches to Human Understanding, addresses related subjects in cognitive science and neuroscience. These two volumes are intended to complement each other in order to more comprehensively investigate human cognitive functions, to develop human-friendly information and robot technology (IRT) systems, and to understand what kind of beings we humans are. Volume A describes how human cognitive functions can be replicated in artificial systems such as robots, and investigates how artificial systems could acquire intelligent behaviors through interaction with others and their environment.

A Multilayer Hidden Markov Models-Based Method for Human-Robot Interaction

Directory of Open Access Journals (Sweden)

Chongben Tao

2013-01-01

Full Text Available To achieve Human-Robot Interaction (HRI by using gestures, a continuous gesture recognition approach based on Multilayer Hidden Markov Models (MHMMs is proposed, which consists of two parts. One part is gesture spotting and segment module, the other part is continuous gesture recognition module. Firstly, a Kinect sensor is used to capture 3D acceleration and 3D angular velocity data of hand gestures. And then, a Feed-forward Neural Networks (FNNs and a threshold criterion are used for gesture spotting and segment, respectively. Afterwards, the segmented gesture signals are respectively preprocessed and vector symbolized by a sliding window and a K-means clustering method. Finally, symbolized data are sent into Lower Hidden Markov Models (LHMMs to identify individual gestures, and then, a Bayesian filter with sequential constraints among gestures in Upper Hidden Markov Models (UHMMs is used to correct recognition errors created in LHMMs. Five predefined gestures are used to interact with a Kinect mobile robot in experiments. The experimental results show that the proposed method not only has good effectiveness and accuracy, but also has favorable real-time performance.

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.

Socially intelligent robots that understand and respond to human touch

NARCIS (Netherlands)

Jung, Merel Madeleine

Touch is an important nonverbal form of interpersonal interaction which is used to communicate emotions and other social messages. As interactions with social robots are likely to become more common in the near future these robots should also be able to engage in tactile interaction with humans.

Measuring empathy for human and robot hand pain using electroencephalography.

Science.gov (United States)

Suzuki, Yutaka; Galli, Lisa; Ikeda, Ayaka; Itakura, Shoji; Kitazaki, Michiteru

2015-11-03

This study provides the first physiological evidence of humans' ability to empathize with robot pain and highlights the difference in empathy for humans and robots. We performed electroencephalography in 15 healthy adults who observed either human- or robot-hand pictures in painful or non-painful situations such as a finger cut by a knife. We found that the descending phase of the P3 component was larger for the painful stimuli than the non-painful stimuli, regardless of whether the hand belonged to a human or robot. In contrast, the ascending phase of the P3 component at the frontal-central electrodes was increased by painful human stimuli but not painful robot stimuli, though the interaction of ANOVA was not significant, but marginal. These results suggest that we empathize with humanoid robots in late top-down processing similarly to human others. However, the beginning of the top-down process of empathy is weaker for robots than for humans.

A Multi-Sensorial Hybrid Control for Robotic Manipulation in Human-Robot Workspaces

Directory of Open Access Journals (Sweden)

Juan A. Corrales

2011-10-01

Full Text Available Autonomous manipulation in semi-structured environments where human operators can interact is an increasingly common task in robotic applications. This paper describes an intelligent multi-sensorial approach that solves this issue by providing a multi-robotic platform with a high degree of autonomy and the capability to perform complex tasks. The proposed sensorial system is composed of a hybrid visual servo control to efficiently guide the robot towards the object to be manipulated, an inertial motion capture system and an indoor localization system to avoid possible collisions between human operators and robots working in the same workspace, and a tactile sensor algorithm to correctly manipulate the object. The proposed controller employs the whole multi-sensorial system and combines the measurements of each one of the used sensors during two different phases considered in the robot task: a first phase where the robot approaches the object to be grasped, and a second phase of manipulation of the object. In both phases, the unexpected presence of humans is taken into account. This paper also presents the successful results obtained in several experimental setups which verify the validity of the proposed approach.

Student teams practice for regional robotic competition at KSC

Science.gov (United States)

1999-01-01

Student teams (right and left) behind protective walls maneuver their robots on the playing field during practice rounds of the 1999 Southeastern Regional robotic competition at Kennedy Space Center Visitor Complex . Thirty schools from around the country have converged at KSC for the event that pits gladiator robots against each other in an athletic-style competition. The robots have to retrieve pillow-like disks from the floor, as well as climb onto the platform (foreground) and raise the cache of pillows to a height of eight feet. KSC is hosting the event being sponsored by the nonprofit organization For Inspiration and Recognition of Science and Technology, known as FIRST. The FIRST robotics competition is designed to provide students with a hands-on, inside look at engineering and other professional careers.

Using Empathy to Improve Human-Robot Relationships

Science.gov (United States)

Pereira, André; Leite, Iolanda; Mascarenhas, Samuel; Martinho, Carlos; Paiva, Ana

For robots to become our personal companions in the future, they need to know how to socially interact with us. One defining characteristic of human social behaviour is empathy. In this paper, we present a robot that acts as a social companion expressing different kinds of empathic behaviours through its facial expressions and utterances. The robot comments the moves of two subjects playing a chess game against each other, being empathic to one of them and neutral towards the other. The results of a pilot study suggest that users to whom the robot was empathic perceived the robot more as a friend.

A Distributed Tactile Sensor for Intuitive Human-Robot Interfacing

Directory of Open Access Journals (Sweden)

Andrea Cirillo

2017-01-01

Full Text Available Safety of human-robot physical interaction is enabled not only by suitable robot control strategies but also by suitable sensing technologies. For example, if distributed tactile sensors were available on the robot, they could be used not only to detect unintentional collisions, but also as human-machine interface by enabling a new mode of social interaction with the machine. Starting from their previous works, the authors developed a conformable distributed tactile sensor that can be easily conformed to the different parts of the robot body. Its ability to estimate contact force components and to provide a tactile map with an accurate spatial resolution enables the robot to handle both unintentional collisions in safe human-robot collaboration tasks and intentional touches where the sensor is used as human-machine interface. In this paper, the authors present the characterization of the proposed tactile sensor and they show how it can be also exploited to recognize haptic tactile gestures, by tailoring recognition algorithms, well known in the image processing field, to the case of tactile images. In particular, a set of haptic gestures has been defined to test three recognition algorithms on a group of 20 users. The paper demonstrates how the same sensor originally designed to manage unintentional collisions can be successfully used also as human-machine interface.

ROILA : RObot Interaction LAnguage

NARCIS (Netherlands)

Mubin, O.

2011-01-01

The number of robots in our society is increasing rapidly. The number of service robots that interact with everyday people already outnumbers industrial robots. The easiest way to communicate with these service robots, such as Roomba or Nao, would be natural speech. However, the limitations

1st AAU Workshop on Human-Centered Robotics

DEFF Research Database (Denmark)

The 2012 AAU Workshop on Human-Centered Robotics took place on 15 Nov. 2012, at Aalborg University, Aalborg. The workshop provides a platform for robotics researchers, including professors, PhD and Master students to exchange their ideas and latest results. The objective is to foster closer...... interaction among researchers from multiple relevant disciplines in the human-centered robotics, and consequently, to promote collaborations across departments of all faculties towards making our center a center of excellence in robotics. The workshop becomes a great success, with 13 presentations, attracting...... more than 45 participants from AAU, SDU, DTI and industrial companies as well. The proceedings contain 7 full papers selected out from the full papers submitted afterwards on the basis of workshop abstracts. The papers represent major research development of robotics at AAU, including medical robots...

I Reach Faster When I See You Look: Gaze Effects in Human-Human and Human-Robot Face-to-Face Cooperation.

Science.gov (United States)

Boucher, Jean-David; Pattacini, Ugo; Lelong, Amelie; Bailly, Gerrard; Elisei, Frederic; Fagel, Sascha; Dominey, Peter Ford; Ventre-Dominey, Jocelyne

2012-01-01

Human-human interaction in natural environments relies on a variety of perceptual cues. Humanoid robots are becoming increasingly refined in their sensorimotor capabilities, and thus should now be able to manipulate and exploit these social cues in cooperation with their human partners. Previous studies have demonstrated that people follow human and robot gaze, and that it can help them to cope with spatially ambiguous language. Our goal is to extend these findings into the domain of action, to determine how human and robot gaze can influence the speed and accuracy of human action. We report on results from a human-human cooperation experiment demonstrating that an agent's vision of her/his partner's gaze can significantly improve that agent's performance in a cooperative task. We then implement a heuristic capability to generate such gaze cues by a humanoid robot that engages in the same cooperative interaction. The subsequent human-robot experiments demonstrate that a human agent can indeed exploit the predictive gaze of their robot partner in a cooperative task. This allows us to render the humanoid robot more human-like in its ability to communicate with humans. The long term objectives of the work are thus to identify social cooperation cues, and to validate their pertinence through implementation in a cooperative robot. The current research provides the robot with the capability to produce appropriate speech and gaze cues in the context of human-robot cooperation tasks. Gaze is manipulated in three conditions: Full gaze (coordinated eye and head), eyes hidden with sunglasses, and head fixed. We demonstrate the pertinence of these cues in terms of statistical measures of action times for humans in the context of a cooperative task, as gaze significantly facilitates cooperation as measured by human response times.

Human-Robot Interaction: Does Robotic Guidance Force Affect Gait-Related Brain Dynamics during Robot-Assisted Treadmill Walking?

Directory of Open Access Journals (Sweden)

Kristel Knaepen

Full Text Available In order to determine optimal training parameters for robot-assisted treadmill walking, it is essential to understand how a robotic device interacts with its wearer, and thus, how parameter settings of the device affect locomotor control. The aim of this study was to assess the effect of different levels of guidance force during robot-assisted treadmill walking on cortical activity. Eighteen healthy subjects walked at 2 km.h-1 on a treadmill with and without assistance of the Lokomat robotic gait orthosis. Event-related spectral perturbations and changes in power spectral density were investigated during unassisted treadmill walking as well as during robot-assisted treadmill walking at 30%, 60% and 100% guidance force (with 0% body weight support. Clustering of independent components revealed three clusters of activity in the sensorimotor cortex during treadmill walking and robot-assisted treadmill walking in healthy subjects. These clusters demonstrated gait-related spectral modulations in the mu, beta and low gamma bands over the sensorimotor cortex related to specific phases of the gait cycle. Moreover, mu and beta rhythms were suppressed in the right primary sensory cortex during treadmill walking compared to robot-assisted treadmill walking with 100% guidance force, indicating significantly larger involvement of the sensorimotor area during treadmill walking compared to robot-assisted treadmill walking. Only marginal differences in the spectral power of the mu, beta and low gamma bands could be identified between robot-assisted treadmill walking with different levels of guidance force. From these results it can be concluded that a high level of guidance force (i.e., 100% guidance force and thus a less active participation during locomotion should be avoided during robot-assisted treadmill walking. This will optimize the involvement of the sensorimotor cortex which is known to be crucial for motor learning.

Human-Robot Interaction: Does Robotic Guidance Force Affect Gait-Related Brain Dynamics during Robot-Assisted Treadmill Walking?

Science.gov (United States)

Knaepen, Kristel; Mierau, Andreas; Swinnen, Eva; Fernandez Tellez, Helio; Michielsen, Marc; Kerckhofs, Eric; Lefeber, Dirk; Meeusen, Romain

2015-01-01

In order to determine optimal training parameters for robot-assisted treadmill walking, it is essential to understand how a robotic device interacts with its wearer, and thus, how parameter settings of the device affect locomotor control. The aim of this study was to assess the effect of different levels of guidance force during robot-assisted treadmill walking on cortical activity. Eighteen healthy subjects walked at 2 km.h-1 on a treadmill with and without assistance of the Lokomat robotic gait orthosis. Event-related spectral perturbations and changes in power spectral density were investigated during unassisted treadmill walking as well as during robot-assisted treadmill walking at 30%, 60% and 100% guidance force (with 0% body weight support). Clustering of independent components revealed three clusters of activity in the sensorimotor cortex during treadmill walking and robot-assisted treadmill walking in healthy subjects. These clusters demonstrated gait-related spectral modulations in the mu, beta and low gamma bands over the sensorimotor cortex related to specific phases of the gait cycle. Moreover, mu and beta rhythms were suppressed in the right primary sensory cortex during treadmill walking compared to robot-assisted treadmill walking with 100% guidance force, indicating significantly larger involvement of the sensorimotor area during treadmill walking compared to robot-assisted treadmill walking. Only marginal differences in the spectral power of the mu, beta and low gamma bands could be identified between robot-assisted treadmill walking with different levels of guidance force. From these results it can be concluded that a high level of guidance force (i.e., 100% guidance force) and thus a less active participation during locomotion should be avoided during robot-assisted treadmill walking. This will optimize the involvement of the sensorimotor cortex which is known to be crucial for motor learning.

Using Language Games as a Way to Investigate Interactional Engagement in Human-Robot Interaction

DEFF Research Database (Denmark)

Jensen, L. C.

2016-01-01

how students' engagement with a social robot can be systematically investigated and evaluated. For this purpose, I present a small user study in which a robot plays a word formation game with a human, in which engagement is determined by means of an analysis of the 'language games' played...

Face and content validity of Xperience™ Team Trainer: bed-side assistant training simulator for robotic surgery.

Science.gov (United States)

Sessa, Luca; Perrenot, Cyril; Xu, Song; Hubert, Jacques; Bresler, Laurent; Brunaud, Laurent; Perez, Manuela

2018-03-01

In robotic surgery, the coordination between the console-side surgeon and bed-side assistant is crucial, more than in standard surgery or laparoscopy where the surgical team works in close contact. Xperience™ Team Trainer (XTT) is a new optional component for the dv-Trainer ® platform and simulates the patient-side working environment. We present preliminary results for face, content, and the workload imposed regarding the use of the XTT virtual reality platform for the psychomotor and communication skills training of the bed-side assistant in robot-assisted surgery. Participants were categorized into "Beginners" and "Experts". They tested a series of exercises (Pick & Place Laparoscopic Demo, Pick & Place 2 and Team Match Board 1) and completed face validity questionnaires. "Experts" assessed content validity on another questionnaire. All the participants completed a NASA Task Load Index questionnaire to assess the workload imposed by XTT. Twenty-one consenting participants were included (12 "Beginners" and 9 "Experts"). XTT was shown to possess face and content validity, as evidenced by the rankings given on the simulator's ease of use and realism parameters and on the simulator's usefulness for training. Eight out of nine "Experts" judged the visualization of metrics after the exercises useful. However, face validity has shown some weaknesses regarding interactions and instruments. Reasonable workload parameters were registered. XTT demonstrated excellent face and content validity with acceptable workload parameters. XTT could become a useful tool for robotic surgery team training.

Drum-mate: interaction dynamics and gestures in human-humanoid drumming experiments

Science.gov (United States)

Kose-Bagci, Hatice; Dautenhahn, Kerstin; Syrdal, Dag S.; Nehaniv, Chrystopher L.

2010-06-01

This article investigates the role of interaction kinesics in human-robot interaction (HRI). We adopted a bottom-up, synthetic approach towards interactive competencies in robots using simple, minimal computational models underlying the robot's interaction dynamics. We present two empirical, exploratory studies investigating a drumming experience with a humanoid robot (KASPAR) and a human. In the first experiment, the turn-taking behaviour of the humanoid is deterministic and the non-verbal gestures of the robot accompany its drumming to assess the impact of non-verbal gestures on the interaction. The second experiment studies a computational framework that facilitates emergent turn-taking dynamics, whereby the particular dynamics of turn-taking emerge from the social interaction between the human and the humanoid. The results from the HRI experiments are presented and analysed qualitatively (in terms of the participants' subjective experiences) and quantitatively (concerning the drumming performance of the human-robot pair). The results point out a trade-off between the subjective evaluation of the drumming experience from the perspective of the participants and the objective evaluation of the drumming performance. A certain number of gestures was preferred as a motivational factor in the interaction. The participants preferred the models underlying the robot's turn-taking which enable the robot and human to interact more and provide turn-taking closer to 'natural' human-human conversations, despite differences in objective measures of drumming behaviour. The results are consistent with the temporal behaviour matching hypothesis previously proposed in the literature which concerns the effect that the participants adapt their own interaction dynamics to the robot's.

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.

Interactive robots in experimental biology.

Science.gov (United States)

Krause, Jens; Winfield, Alan F T; Deneubourg, Jean-Louis

2011-07-01

Interactive robots have the potential to revolutionise the study of social behaviour because they provide several methodological advances. In interactions with live animals, the behaviour of robots can be standardised, morphology and behaviour can be decoupled (so that different morphologies and behavioural strategies can be combined), behaviour can be manipulated in complex interaction sequences and models of behaviour can be embodied by the robot and thereby be tested. Furthermore, robots can be used as demonstrators in experiments on social learning. As we discuss here, the opportunities that robots create for new experimental approaches have far-reaching consequences for research in fields such as mate choice, cooperation, social learning, personality studies and collective behaviour. Copyright © 2011 Elsevier Ltd. All rights reserved.

Human likeness: cognitive and affective factors affecting adoption of robot-assisted learning systems

Science.gov (United States)

Yoo, Hosun; Kwon, Ohbyung; Lee, Namyeon

2016-07-01

With advances in robot technology, interest in robotic e-learning systems has increased. In some laboratories, experiments are being conducted with humanoid robots as artificial tutors because of their likeness to humans, the rich possibilities of using this type of media, and the multimodal interaction capabilities of these robots. The robot-assisted learning system, a special type of e-learning system, aims to increase the learner's concentration, pleasure, and learning performance dramatically. However, very few empirical studies have examined the effect on learning performance of incorporating humanoid robot technology into e-learning systems or people's willingness to accept or adopt robot-assisted learning systems. In particular, human likeness, the essential characteristic of humanoid robots as compared with conventional e-learning systems, has not been discussed in a theoretical context. Hence, the purpose of this study is to propose a theoretical model to explain the process of adoption of robot-assisted learning systems. In the proposed model, human likeness is conceptualized as a combination of media richness, multimodal interaction capabilities, and para-social relationships; these factors are considered as possible determinants of the degree to which human cognition and affection are related to the adoption of robot-assisted learning systems.

Pupillary Responses to Robotic and Human Emotions: The Uncanny Valley and Media Equation Confirmed

Directory of Open Access Journals (Sweden)

Anne Reuten

2018-05-01

Full Text Available Physiological responses during human–robots interaction are useful alternatives to subjective measures of uncanny feelings for nearly humanlike robots (uncanny valley and comparable emotional responses between humans and robots (media equation. However, no studies have employed the easily accessible measure of pupillometry to confirm the uncanny valley and media equation hypotheses, evidence in favor of the existence of these hypotheses in interaction with emotional robots is scarce, and previous studies have not controlled for low level image statistics across robot appearances. We therefore recorded pupil size of 40 participants that viewed and rated pictures of robotic and human faces that expressed a variety of basic emotions. The robotic faces varied along the dimension of human likeness from cartoonish to humanlike. We strictly controlled for confounding factors by removing backgrounds, hair, and color, and by equalizing low level image statistics. After the presentation phase, participants indicated to what extent the robots appeared uncanny and humanlike, and whether they could imagine social interaction with the robots in real life situations. The results show that robots rated as nearly humanlike scored higher on uncanniness, scored lower on imagined social interaction, evoked weaker pupil dilations, and their emotional expressions were more difficult to recognize. Pupils dilated most strongly to negative expressions and the pattern of pupil responses across emotions was highly similar between robot and human stimuli. These results highlight the usefulness of pupillometry in emotion studies and robot design by confirming the uncanny valley and media equation hypotheses.

A Decentralized Interactive Architecture for Aerial and Ground Mobile Robots Cooperation

OpenAIRE

Harik, El Houssein Chouaib; Guérin, François; Guinand, Frédéric; Brethé, Jean-François; Pelvillain, Hervé

2014-01-01

International audience; —This paper presents a novel decentralized interactive architecture for aerial and ground mobile robots cooperation. The aerial mobile robot is used to provide a global coverage during an area inspection, while the ground mobile robot is used to provide a local coverage of ground features. We include a human-in-the-loop to provide waypoints for the ground mobile robot to progress safely in the inspected area. The aerial mobile robot follows continuously the ground mobi...

Multimodal human-machine interaction for service robots in home-care environments

OpenAIRE

Goetze, Stefan; Fischer, S.; Moritz, Niko; Appell, Jens-E.; Wallhoff, Frank

2012-01-01

This contribution focuses on multimodal interaction techniques for a mobile communication and assistance system on a robot platform. The system comprises of acoustic, visual and haptic input modalities. Feedback is given to the user by a graphical user interface and a speech synthesis system. By this, multimodal and natural communication with the robot system is possible.

Social Moments: A Perspective on Interaction for Social Robotics

OpenAIRE

Durantin, Gautier; Heath, Scott; Wiles, Janet

2017-01-01

During a social interaction, events that happen at different timescales can indicate social meanings. In order to socially engage with humans, robots will need to be able to comprehend and manipulate the social meanings that are associated with these events. We define social moments as events that occur within a social interaction and which can signify a pragmatic or semantic meaning. A challenge for social robots is recognizing social moments that occur on short timescales, which can be on t...

Presence of Life-Like Robot Expressions Influences Children’s Enjoyment of Human-Robot Interactions in the Field

NARCIS (Netherlands)

Cameron, David; Fernando, Samuel; Collins, Emily; Millings, Abigail; Moore, Roger; Sharkey, Amanda; Evers, Vanessa; Prescott, Tony

Emotions, and emotional expression, have a broad influence on the interactions we have with others and are thus a key factor to consider in developing social robots. As part of a collaborative EU project, this study examined the impact of lifelike affective facial expressions, in the humanoid robot

Human-Robot Interaction: Intention Recognition and Mutual Entrainment

Science.gov (United States)

2012-08-18

bility, but only the human arm is modeled, with linear, low-pass-filter type transfer functions [16]. The coupled dynamics in pHRI has been intensively ...be located inside or on the edge of the polygon. IV. DISCUSSION A. Issues in Implementing LIPM on a Mobile Robot Instead of focusing on kinesiology

Playte, a tangible interface for engaging human-robot interaction

DEFF Research Database (Denmark)

Christensen, David Johan; Fogh, Rune; Lund, Henrik Hautop

2014-01-01

This paper describes a tangible interface, Playte, designed for children animating interactive robots. The system supports physical manipulation of behaviors represented by LEGO bricks and allows the user to record and train their own new behaviors. Our objective is to explore several modes of in...

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

Robotic Reconnaissance Missions to Small Bodies and Their Potential Contributions to Human Exploration

Science.gov (United States)

Abell, P. A.; Rivkin, A. S.

2015-01-01

Introduction: Robotic reconnaissance missions to small bodies will directly address aspects of NASA's Asteroid Initiative and will contribute to future human exploration. The NASA Asteroid Initiative is comprised of two major components: the Grand Challenge and the Asteroid Mission. The first component, the Grand Challenge, focuses on protecting Earth's population from asteroid impacts by detecting potentially hazardous objects with enough warning time to either prevent them from impacting the planet, or to implement civil defense procedures. The Asteroid Mission involves sending astronauts to study and sample a near- Earth asteroid (NEA) prior to conducting exploration missions of the Martian system, which includes Phobos and Deimos. The science and technical data obtained from robotic precursor missions that investigate the surface and interior physical characteristics of an object will help identify the pertinent physical properties that will maximize operational efficiency and reduce mission risk for both robotic assets and crew operating in close proximity to, or at the surface of, a small body. These data will help fill crucial strategic knowledge gaps (SKGs) concerning asteroid physical characteristics that are relevant for human exploration considerations at similar small body destinations. Small Body Strategic Knowledge Gaps: For the past several years NASA has been interested in identifying the key SKGs related to future human destinations. These SKGs highlight the various unknowns and/or data gaps of targets that the science and engineering communities would like to have filled in prior to committing crews to explore the Solar System. An action team from the Small Bodies Assessment Group (SBAG) was formed specifically to identify the small body SKGs under the direction of the Human Exploration and Operations Missions Directorate (HEOMD), given NASA's recent interest in NEAs and the Martian moons as potential human destinations [1]. The action team

Experiments with a First Prototype of a Spatial Model of Cultural Meaning through Natural-Language Human-Robot Interaction

Directory of Open Access Journals (Sweden)

Oliver Schürer

2018-01-01

Full Text Available When using assistive systems, the consideration of individual and cultural meaning is crucial for the utility and acceptance of technology. Orientation, communication and interaction are rooted in perception and therefore always happen in material space. We understand that a major problem lies in the difference between human and technical perception of space. Cultural policies are based on meanings including their spatial situation and their rich relationships. Therefore, we have developed an approach where the different perception systems share a hybrid spatial model that is generated by artificial intelligence—a joint effort by humans and assistive systems. The aim of our project is to create a spatial model of cultural meaning based on interaction between humans and robots. We define the role of humanoid robots as becoming our companions. This calls for technical systems to include still inconceivable human and cultural agendas for the perception of space. In two experiments, we tested a first prototype of the communication module that allows a humanoid to learn cultural meanings through a machine learning system. Interaction is achieved by non-verbal and natural-language communication between humanoids and test persons. This helps us to better understand how a spatial model of cultural meaning can be developed.

R3D3 in the Wild: Using A Robot for Turn Management in Multi-Party Interaction with a Virtual Human

NARCIS (Netherlands)

Theune, Mariet; Wiltenburg, Daan; Bode, Max; Linssen, Jeroen

R3D3 is a combination of a virtual human with a non-speaking robot capable of head gestures and emotive gaze behaviour. We use the robot to implement various turn management functions for use in multi-party interaction with R3D3, and present the results of a field study investigating their effects

Singularity now: using the ventricular assist device as a model for future human-robotic physiology.

Science.gov (United States)

Martin, Archer K

2016-04-01

In our 21 st century world, human-robotic interactions are far more complicated than Asimov predicted in 1942. The future of human-robotic interactions includes human-robotic machine hybrids with an integrated physiology, working together to achieve an enhanced level of baseline human physiological performance. This achievement can be described as a biological Singularity. I argue that this time of Singularity cannot be met by current biological technologies, and that human-robotic physiology must be integrated for the Singularity to occur. In order to conquer the challenges we face regarding human-robotic physiology, we first need to identify a working model in today's world. Once identified, this model can form the basis for the study, creation, expansion, and optimization of human-robotic hybrid physiology. In this paper, I present and defend the line of argument that currently this kind of model (proposed to be named "IshBot") can best be studied in ventricular assist devices - VAD.

Integrated Human-Robotic Missions to the Moon and Mars: Mission Operations Design Implications

Science.gov (United States)

Mishkin, Andrew; Lee, Young; Korth, David; LeBlanc, Troy

2007-01-01

For most of the history of space exploration, human and robotic programs have been independent, and have responded to distinct requirements. The NASA Vision for Space Exploration calls for the return of humans to the Moon, and the eventual human exploration of Mars; the complexity of this range of missions will require an unprecedented use of automation and robotics in support of human crews. The challenges of human Mars missions, including roundtrip communications time delays of 6 to 40 minutes, interplanetary transit times of many months, and the need to manage lifecycle costs, will require the evolution of a new mission operations paradigm far less dependent on real-time monitoring and response by an Earthbound operations team. Robotic systems and automation will augment human capability, increase human safety by providing means to perform many tasks without requiring immediate human presence, and enable the transfer of traditional mission control tasks from the ground to crews. Developing and validating the new paradigm and its associated infrastructure may place requirements on operations design for nearer-term lunar missions. The authors, representing both the human and robotic mission operations communities, assess human lunar and Mars mission challenges, and consider how human-robot operations may be integrated to enable efficient joint operations, with the eventual emergence of a unified exploration operations culture.

Evidence of Self-Directed Learning on a High School Robotics Team

Directory of Open Access Journals (Sweden)

Nathan R. Dolenc

2014-12-01

Full Text Available Self-directed learning is described as an individual taking the initiative to engage in a learning experience while assuming responsibility to follow through to its conclusion. Robotics competitions are examples of informal environments that can facilitate self-directed learning. This study examined how mentor involvement, student behavior, and physical workspace contributed to self-directed learning on one robotics competition team. How did mentors transfer responsibility to students? How did students respond to managing a team? Are the physical attributes of a workspace important? The mentor, student, and workplace factors captured in the research showed mentors wanting students to do the work, students assuming leadership roles, and the limited workspace having a positive effect on student productivity.

Children with Autism Spectrum Disorders Make a Fruit Salad with Probo, the Social Robot: An Interaction Study.

Science.gov (United States)

Simut, Ramona E; Vanderfaeillie, Johan; Peca, Andreea; Van de Perre, Greet; Vanderborght, Bram

2016-01-01

Social robots are thought to be motivating tools in play tasks with children with autism spectrum disorders. Thirty children with autism were included using a repeated measurements design. It was investigated if the children's interaction with a human differed from the interaction with a social robot during a play task. Also, it was examined if the two conditions differed in their ability to elicit interaction with a human accompanying the child during the task. Interaction of the children with both partners did not differ apart from the eye-contact. Participants had more eye-contact with the social robot compared to the eye-contact with the human. The conditions did not differ regarding the interaction elicited with the human accompanying the child.

Robotic Billiards: Understanding Humans in Order to Counter Them.

Science.gov (United States)

Nierhoff, Thomas; Leibrandt, Konrad; Lorenz, Tamara; Hirche, Sandra

2016-08-01

Ongoing technological advances in the areas of computation, sensing, and mechatronics enable robotic-based systems to interact with humans in the real world. To succeed against a human in a competitive scenario, a robot must anticipate the human behavior and include it in its own planning framework. Then it can predict the next human move and counter it accordingly, thus not only achieving overall better performance but also systematically exploiting the opponent's weak spots. Pool is used as a representative scenario to derive a model-based planning and control framework where not only the physics of the environment but also a model of the opponent is considered. By representing the game of pool as a Markov decision process and incorporating a model of the human decision-making based on studies, an optimized policy is derived. This enables the robot to include the opponent's typical game style into its tactical considerations when planning a stroke. The results are validated in simulations and real-life experiments with an anthropomorphic robot playing pool against a human.

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.

Building a grid-semantic map for the navigation of service robots through human–robot interaction

Directory of Open Access Journals (Sweden)

Cheng Zhao

2015-11-01

Full Text Available This paper presents an interactive approach to the construction of a grid-semantic map for the navigation of service robots in an indoor environment. It is based on the Robot Operating System (ROS framework and contains four modules, namely Interactive Module, Control Module, Navigation Module and Mapping Module. Three challenging issues have been focused during its development: (i how human voice and robot visual information could be effectively deployed in the mapping and navigation process; (ii how semantic names could combine with coordinate data in an online Grid-Semantic map; and (iii how a localization–evaluate–relocalization method could be used in global localization based on modified maximum particle weight of the particle swarm. A number of experiments are carried out in both simulated and real environments such as corridors and offices to verify its feasibility and performance.

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...

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

Human-robot interaction tests on a novel robot for gait assistance.

Science.gov (United States)

Tagliamonte, Nevio Luigi; Sergi, Fabrizio; Carpino, Giorgio; Accoto, Dino; Guglielmelli, Eugenio

2013-06-01

This paper presents tests on a treadmill-based non-anthropomorphic wearable robot assisting hip and knee flexion/extension movements using compliant actuation. Validation experiments were performed on the actuators and on the robot, with specific focus on the evaluation of intrinsic backdrivability and of assistance capability. Tests on a young healthy subject were conducted. In the case of robot completely unpowered, maximum backdriving torques were found to be in the order of 10 Nm due to the robot design features (reduced swinging masses; low intrinsic mechanical impedance and high-efficiency reduction gears for the actuators). Assistance tests demonstrated that the robot can deliver torques attracting the subject towards a predicted kinematic status.

Real-time multiple human perception with color-depth cameras on a mobile robot.

Science.gov (United States)

Zhang, Hao; Reardon, Christopher; Parker, Lynne E

2013-10-01

The ability to perceive humans is an essential requirement for safe and efficient human-robot interaction. In real-world applications, the need for a robot to interact in real time with multiple humans in a dynamic, 3-D environment presents a significant challenge. The recent availability of commercial color-depth cameras allow for the creation of a system that makes use of the depth dimension, thus enabling a robot to observe its environment and perceive in the 3-D space. Here we present a system for 3-D multiple human perception in real time from a moving robot equipped with a color-depth camera and a consumer-grade computer. Our approach reduces computation time to achieve real-time performance through a unique combination of new ideas and established techniques. We remove the ground and ceiling planes from the 3-D point cloud input to separate candidate point clusters. We introduce the novel information concept, depth of interest, which we use to identify candidates for detection, and that avoids the computationally expensive scanning-window methods of other approaches. We utilize a cascade of detectors to distinguish humans from objects, in which we make intelligent reuse of intermediary features in successive detectors to improve computation. Because of the high computational cost of some methods, we represent our candidate tracking algorithm with a decision directed acyclic graph, which allows us to use the most computationally intense techniques only where necessary. We detail the successful implementation of our novel approach on a mobile robot and examine its performance in scenarios with real-world challenges, including occlusion, robot motion, nonupright humans, humans leaving and reentering the field of view (i.e., the reidentification challenge), human-object and human-human interaction. We conclude with the observation that the incorporation of the depth information, together with the use of modern techniques in new ways, we are able to create an

Effective Human-Robot Collaborative Work for Critical Missions

Data.gov (United States)

National Aeronautics and Space Administration — The objective of this project is to improve human-robot interaction (HRI) in order to enhance the capability of NASA critical missions. This research will focus two...

Mobile Manipulation, Tool Use, and Intuitive Interaction for Cognitive Service Robot Cosero

Directory of Open Access Journals (Sweden)

Jörg Stückler

2016-11-01

Full Text Available Cognitive service robots that shall assist persons in need in performing their activities of daily living have recently received much attention in robotics research.Such robots require a vast set of control and perception capabilities to provide useful assistance through mobile manipulation and human-robot interaction.In this article, we present hardware design, perception, and control methods for our cognitive service robot Cosero.We complement autonomous capabilities with handheld teleoperation interfaces on three levels of autonomy.The robot demonstrated various advanced skills, including the use of tools.With our robot we participated in the annual international RoboCup@Home competitions, winning them three times in a row.

The ultimatum game as measurement tool for anthropomorphism in human-robot interaction

NARCIS (Netherlands)

Torta, E.; Dijk, van E.T.; Ruijten, P.A.M.; Cuijpers, R.H.; Herrmann, G.; Pearson, M.J.; Lenz, A.; et al., xx

2013-01-01

Anthropomorphism is the tendency to attribute human characteristics to non–human entities. This paper presents exploratory work to evaluate how human responses during the ultimatum game vary according to the level of anthropomorphism of the opponent, which was either a human, a humanoid robot or a

Communication of Robot Status to Improve Human-Robot Collaboration

Data.gov (United States)

National Aeronautics and Space Administration — Future space exploration will require humans and robots to collaborate to perform all the necessary tasks. Current robots mostly operate separately from humans due...

Interactive language learning by robots: the transition from babbling to word forms.

Science.gov (United States)

Lyon, Caroline; Nehaniv, Chrystopher L; Saunders, Joe

2012-01-01

The advent of humanoid robots has enabled a new approach to investigating the acquisition of language, and we report on the development of robots able to acquire rudimentary linguistic skills. Our work focuses on early stages analogous to some characteristics of a human child of about 6 to 14 months, the transition from babbling to first word forms. We investigate one mechanism among many that may contribute to this process, a key factor being the sensitivity of learners to the statistical distribution of linguistic elements. As well as being necessary for learning word meanings, the acquisition of anchor word forms facilitates the segmentation of an acoustic stream through other mechanisms. In our experiments some salient one-syllable word forms are learnt by a humanoid robot in real-time interactions with naive participants. Words emerge from random syllabic babble through a learning process based on a dialogue between the robot and the human participant, whose speech is perceived by the robot as a stream of phonemes. Numerous ways of representing the speech as syllabic segments are possible. Furthermore, the pronunciation of many words in spontaneous speech is variable. However, in line with research elsewhere, we observe that salient content words are more likely than function words to have consistent canonical representations; thus their relative frequency increases, as does their influence on the learner. Variable pronunciation may contribute to early word form acquisition. The importance of contingent interaction in real-time between teacher and learner is reflected by a reinforcement process, with variable success. The examination of individual cases may be more informative than group results. Nevertheless, word forms are usually produced by the robot after a few minutes of dialogue, employing a simple, real-time, frequency dependent mechanism. This work shows the potential of human-robot interaction systems in studies of the dynamics of early language

Pragmatic Frames for Teaching and Learning in Human–Robot Interaction: Review and Challenges

Science.gov (United States)

Vollmer, Anna-Lisa; Wrede, Britta; Rohlfing, Katharina J.; Oudeyer, Pierre-Yves

2016-01-01

One of the big challenges in robotics today is to learn from human users that are inexperienced in interacting with robots but yet are often used to teach skills flexibly to other humans and to children in particular. A potential route toward natural and efficient learning and teaching in Human-Robot Interaction (HRI) is to leverage the social competences of humans and the underlying interactional mechanisms. In this perspective, this article discusses the importance of pragmatic frames as flexible interaction protocols that provide important contextual cues to enable learners to infer new action or language skills and teachers to convey these cues. After defining and discussing the concept of pragmatic frames, grounded in decades of research in developmental psychology, we study a selection of HRI work in the literature which has focused on learning–teaching interaction and analyze the interactional and learning mechanisms that were used in the light of pragmatic frames. This allows us to show that many of the works have already used in practice, but not always explicitly, basic elements of the pragmatic frames machinery. However, we also show that pragmatic frames have so far been used in a very restricted way as compared to how they are used in human–human interaction and argue that this has been an obstacle preventing robust natural multi-task learning and teaching in HRI. In particular, we explain that two central features of human pragmatic frames, mostly absent of existing HRI studies, are that (1) social peers use rich repertoires of frames, potentially combined together, to convey and infer multiple kinds of cues; (2) new frames can be learnt continually, building on existing ones, and guiding the interaction toward higher levels of complexity and expressivity. To conclude, we give an outlook on the future research direction describing the relevant key challenges that need to be solved for leveraging pragmatic frames for robot learning and teaching

Humans and Robots. Educational Brief.

Science.gov (United States)

National Aeronautics and Space Administration, Washington, DC.

This brief discusses human movement and robotic human movement simulators. The activity for students in grades 5-12 provides a history of robotic movement and includes making an End Effector for the robotic arms used on the Space Shuttle and the International Space Station (ISS). (MVL)

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...

Robots as Confederates

DEFF Research Database (Denmark)

Fischer, Kerstin

2016-01-01

This paper addresses the use of robots in experimental research for the study of human language, human interaction, and human nature. It is argued that robots make excellent confederates that can be completely controlled, yet which engage human participants in interactions that allow us to study...... numerous linguistic and psychological variables in isolation in an ecologically valid way. Robots thus combine the advantages of observational studies and of controlled experimentation....

Robot, human and communication; Robotto/ningen/comyunikeshon

Energy Technology Data Exchange (ETDEWEB)

Suehiro, T.

1996-04-10

Recently, some interests on the robots working with human beings under the same environment as the human beings and living with the human beings were promoting. In such robots, more suitability for environment and more robustness of system are required than those in conventional robots. Above all, communication of both the human beings and the robots on their cooperations is becoming a new problem. Hitherto, for the industrial robot, cooperation between human beings and robot was limited on its programming. As this was better for repeated operation of the same motion, its adoptable work was limited to some comparatively simpler one in factory and was difficult to change its content partially or to apply the other work. Furthermore, on the remote-controlled intelligent work robot represented by the critical work robot, its cooperation between the human beings and the robot can be conducted with the operation at remote location. In this paper, the communication of the robots lived with the human beings was examined. 17 refs., 1 fig.

Designing human-robot collaborations in industry 4.0: explorative case studies

DEFF Research Database (Denmark)

Kadir, Bzhwen A; Broberg, Ole; Souza da Conceição, Carolina

2018-01-01

We are experiencing an increase in human-robot interactions and the use of collaborative robots (cobots) in industrial work systems. To make full use of cobots, it is essential to understand emerging challenges and opportunities. In this paper, we analyse three successful industrial case studies...... of cobots’ implementation. We highlight the top three challenges and opportunities, from the empirical evidence, relate them to current available literature on the topic, and use them to identify key design factor to consider when designing industrial work system with human-robot collaborations....

Systematic analysis of video data from different human–robot interaction studies: a categorization of social signals during error situations

Science.gov (United States)

Giuliani, Manuel; Mirnig, Nicole; Stollnberger, Gerald; Stadler, Susanne; Buchner, Roland; Tscheligi, Manfred

2015-01-01

Human–robot interactions are often affected by error situations that are caused by either the robot or the human. Therefore, robots would profit from the ability to recognize when error situations occur. We investigated the verbal and non-verbal social signals that humans show when error situations occur in human–robot interaction experiments. For that, we analyzed 201 videos of five human–robot interaction user studies with varying tasks from four independent projects. The analysis shows that there are two types of error situations: social norm violations and technical failures. Social norm violations are situations in which the robot does not adhere to the underlying social script of the interaction. Technical failures are caused by technical shortcomings of the robot. The results of the video analysis show that the study participants use many head movements and very few gestures, but they often smile, when in an error situation with the robot. Another result is that the participants sometimes stop moving at the beginning of error situations. We also found that the participants talked more in the case of social norm violations and less during technical failures. Finally, the participants use fewer non-verbal social signals (for example smiling, nodding, and head shaking), when they are interacting with the robot alone and no experimenter or other human is present. The results suggest that participants do not see the robot as a social interaction partner with comparable communication skills. Our findings have implications for builders and evaluators of human–robot interaction systems. The builders need to consider including modules for recognition and classification of head movements to the robot input channels. The evaluators need to make sure that the presence of an experimenter does not skew the results of their user studies. PMID:26217266

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....

A Self-Organizing Interaction and Synchronization Method between a Wearable Device and Mobile Robot.

Science.gov (United States)

Kim, Min Su; Lee, Jae Geun; Kang, Soon Ju

2016-06-08

In the near future, we can expect to see robots naturally following or going ahead of humans, similar to pet behavior. We call this type of robots "Pet-Bot". To implement this function in a robot, in this paper we introduce a self-organizing interaction and synchronization method between wearable devices and Pet-Bots. First, the Pet-Bot opportunistically identifies its owner without any human intervention, which means that the robot self-identifies the owner's approach on its own. Second, Pet-Bot's activity is synchronized with the owner's behavior. Lastly, the robot frequently encounters uncertain situations (e.g., when the robot goes ahead of the owner but meets a situation where it cannot make a decision, or the owner wants to stop the Pet-Bot synchronization mode to relax). In this case, we have adopted a gesture recognition function that uses a 3-D accelerometer in the wearable device. In order to achieve the interaction and synchronization in real-time, we use two wireless communication protocols: 125 kHz low-frequency (LF) and 2.4 GHz Bluetooth low energy (BLE). We conducted experiments using a prototype Pet-Bot and wearable devices to verify their motion recognition of and synchronization with humans in real-time. The results showed a guaranteed level of accuracy of at least 94%. A trajectory test was also performed to demonstrate the robot's control performance when following or leading a human in real-time.

Evaluation by Expert Dancers of a Robot That Performs Partnered Stepping via Haptic Interaction.

Directory of Open Access Journals (Sweden)

Tiffany L Chen

Full Text Available Our long-term goal is to enable a robot to engage in partner dance for use in rehabilitation therapy, assessment, diagnosis, and scientific investigations of two-person whole-body motor coordination. Partner dance has been shown to improve balance and gait in people with Parkinson's disease and in older adults, which motivates our work. During partner dance, dance couples rely heavily on haptic interaction to convey motor intent such as speed and direction. In this paper, we investigate the potential for a wheeled mobile robot with a human-like upper-body to perform partnered stepping with people based on the forces applied to its end effectors. Blindfolded expert dancers (N=10 performed a forward/backward walking step to a recorded drum beat while holding the robot's end effectors. We varied the admittance gain of the robot's mobile base controller and the stiffness of the robot's arms. The robot followed the participants with low lag (M=224, SD=194 ms across all trials. High admittance gain and high arm stiffness conditions resulted in significantly improved performance with respect to subjective and objective measures. Biomechanical measures such as the human hand to human sternum distance, center-of-mass of leader to center-of-mass of follower (CoM-CoM distance, and interaction forces correlated with the expert dancers' subjective ratings of their interactions with the robot, which were internally consistent (Cronbach's α=0.92. In response to a final questionnaire, 1/10 expert dancers strongly agreed, 5/10 agreed, and 1/10 disagreed with the statement "The robot was a good follower." 2/10 strongly agreed, 3/10 agreed, and 2/10 disagreed with the statement "The robot was fun to dance with." The remaining participants were neutral with respect to these two questions.

Evaluation by Expert Dancers of a Robot That Performs Partnered Stepping via Haptic Interaction

Science.gov (United States)

Chen, Tiffany L.; Bhattacharjee, Tapomayukh; McKay, J. Lucas; Borinski, Jacquelyn E.; Hackney, Madeleine E.; Ting, Lena H.; Kemp, Charles C.

2015-01-01

Our long-term goal is to enable a robot to engage in partner dance for use in rehabilitation therapy, assessment, diagnosis, and scientific investigations of two-person whole-body motor coordination. Partner dance has been shown to improve balance and gait in people with Parkinson's disease and in older adults, which motivates our work. During partner dance, dance couples rely heavily on haptic interaction to convey motor intent such as speed and direction. In this paper, we investigate the potential for a wheeled mobile robot with a human-like upper-body to perform partnered stepping with people based on the forces applied to its end effectors. Blindfolded expert dancers (N=10) performed a forward/backward walking step to a recorded drum beat while holding the robot's end effectors. We varied the admittance gain of the robot's mobile base controller and the stiffness of the robot's arms. The robot followed the participants with low lag (M=224, SD=194 ms) across all trials. High admittance gain and high arm stiffness conditions resulted in significantly improved performance with respect to subjective and objective measures. Biomechanical measures such as the human hand to human sternum distance, center-of-mass of leader to center-of-mass of follower (CoM-CoM) distance, and interaction forces correlated with the expert dancers' subjective ratings of their interactions with the robot, which were internally consistent (Cronbach's α=0.92). In response to a final questionnaire, 1/10 expert dancers strongly agreed, 5/10 agreed, and 1/10 disagreed with the statement "The robot was a good follower." 2/10 strongly agreed, 3/10 agreed, and 2/10 disagreed with the statement "The robot was fun to dance with." The remaining participants were neutral with respect to these two questions. PMID:25993099

The Influence of Social Interaction on the Perception of Emotional Expression: A Case Study with a Robot Head

Science.gov (United States)

Murray, John C.; Cañamero, Lola; Bard, Kim A.; Ross, Marina Davila; Thorsteinsson, Kate

In this paper we focus primarily on the influence that socio-emotional interaction has on the perception of emotional expression by a robot. We also investigate and discuss the importance of emotion expression in socially interactive situations involving human robot interaction (HRI), and show the importance of utilising emotion expression when dealing with interactive robots, that are to learn and develop in socially situated environments. We discuss early expressional development and the function of emotion in communication in humans and how this can improve HRI communications. Finally we provide experimental results showing how emotion-rich interaction via emotion expression can affect the HRI process by providing additional information.

Robotic Nudges: The Ethics of Engineering a More Socially Just Human Being.

Science.gov (United States)

Borenstein, Jason; Arkin, Ron

2016-02-01

Robots are becoming an increasingly pervasive feature of our personal lives. As a result, there is growing importance placed on examining what constitutes appropriate behavior when they interact with human beings. In this paper, we discuss whether companion robots should be permitted to "nudge" their human users in the direction of being "more ethical". More specifically, we use Rawlsian principles of justice to illustrate how robots might nurture "socially just" tendencies in their human counterparts. Designing technological artifacts in such a way to influence human behavior is already well-established but merely because the practice is commonplace does not necessarily resolve the ethical issues associated with its implementation.

Robust Control of a Cable-Driven Soft Exoskeleton Joint for Intrinsic Human-Robot Interaction.

Science.gov (United States)

Jarrett, C; McDaid, A J

2017-07-01

A novel, cable-driven soft joint is presented for use in robotic rehabilitation exoskeletons to provide intrinsic, comfortable human-robot interaction. The torque-displacement characteristics of the soft elastomeric core contained within the joint are modeled. This knowledge is used in conjunction with a dynamic system model to derive a sliding mode controller (SMC) to implement low-level torque control of the joint. The SMC controller is experimentally compared with a baseline feedback-linearised proportional-derivative controller across a range of conditions and shown to be robust to un-modeled disturbances. The torque controller is then tested with six healthy subjects while they perform a selection of activities of daily living, which has validated its range of performance. Finally, a case study with a participant with spastic cerebral palsy is presented to illustrate the potential of both the joint and controller to be used in a physiotherapy setting to assist clinical populations.

Designing robot embodiments for social interaction: Affordances topple realism and aesthetics

NARCIS (Netherlands)

Paauwe, R.A.; Hoorn, J.F.; Konijn, E.A.; Keyson, D.V.

2015-01-01

In the near future, human-like social robots will become indispensable for providing support in various social tasks, in particular for healthcare (e.g., assistance, coaching). The perception of realism, in particular human-like features, can help facilitate mediated social interaction. The current

Designing Robot Embodiments for Social Interaction : Affordances Topple Realism and Aesthetics

NARCIS (Netherlands)

Paauwe, R.A.; Hoorn, J.F.; Konijn, E.A.; Keyson, D.V.

2015-01-01

In the near future, human-like social robots will become indispensable for providing support in various social tasks, in particular for healthcare (e.g., assistance, coaching). The perception of realism, in particular human-like features, can help facilitate mediated social interaction. The current

Bio-inspired motion planning algorithms for autonomous robots facilitating greater plasticity for security applications

Science.gov (United States)

Guo, Yi; Hohil, Myron; Desai, Sachi V.

2007-10-01

Proposed are techniques toward using collaborative robots for infrastructure security applications by utilizing them for mobile sensor suites. A vast number of critical facilities/technologies must be protected against unauthorized intruders. Employing a team of mobile robots working cooperatively can alleviate valuable human resources. Addressed are the technical challenges for multi-robot teams in security applications and the implementation of multi-robot motion planning algorithm based on the patrolling and threat response scenario. A neural network based methodology is exploited to plan a patrolling path with complete coverage. Also described is a proof-of-principle experimental setup with a group of Pioneer 3-AT and Centibot robots. A block diagram of the system integration of sensing and planning will illustrate the robot to robot interaction to operate as a collaborative unit. The proposed approach singular goal is to overcome the limits of previous approaches of robots in security applications and enabling systems to be deployed for autonomous operation in an unaltered environment providing access to an all encompassing sensor suite.

Structure Assembly by a Heterogeneous Team of Robots Using State Estimation, Generalized Joints, and Mobile Parallel Manipulators

Science.gov (United States)

Komendera, Erik E.; Adhikari, Shaurav; Glassner, Samantha; Kishen, Ashwin; Quartaro, Amy

2017-01-01

Autonomous robotic assembly by mobile field robots has seen significant advances in recent decades, yet practicality remains elusive. Identified challenges include better use of state estimation to and reasoning with uncertainty, spreading out tasks to specialized robots, and implementing representative joining methods. This paper proposes replacing 1) self-correcting mechanical linkages with generalized joints for improved applicability, 2) assembly serial manipulators with parallel manipulators for higher precision and stability, and 3) all-in-one robots with a heterogeneous team of specialized robots for agent simplicity. This paper then describes a general assembly algorithm utilizing state estimation. Finally, these concepts are tested in the context of solar array assembly, requiring a team of robots to assemble, bond, and deploy a set of solar panel mockups to a backbone truss to an accuracy not built into the parts. This paper presents the results of these tests.

Quantifying the human-robot interaction forces between a lower limb exoskeleton and healthy users.

Science.gov (United States)

Rathore, Ashish; Wilcox, Matthew; Ramirez, Dafne Zuleima Morgado; Loureiro, Rui; Carlson, Tom

2016-08-01

To counter the many disadvantages of prolonged wheelchair use, patients with spinal cord injuries (SCI) are beginning to turn towards robotic exoskeletons. However, we are currently unaware of the magnitude and distribution of forces acting between the user and the exoskeleton. This is a critical issue, as SCI patients have an increased susceptibility to skin lesions and pressure ulcer development. Therefore, we developed a real-time force measuring apparatus, which was placed at the physical human-robot interface (pHRI) of a lower limb robotic exoskeleton. Experiments captured the dynamics of these interaction forces whilst the participants performed a range of typical stepping actions. Our results indicate that peak forces occurred at the anterior aspect of both the left and right legs, areas that are particularly prone to pressure ulcer development. A significant difference was also found between the average force experienced at the anterior and posterior sensors of the right thigh during the swing phase for different movement primitives. These results call for the integration of instrumented straps as standard in lower limb exoskeletons. They also highlight the potential of such straps to be used as an alternative/complementary interface for the high-level control of lower limb exoskeletons in some patient groups.

Robots and humans: synergy in planetary exploration

Science.gov (United States)

Landis, Geoffrey A.

2004-01-01

How will humans and robots cooperate in future planetary exploration? Are humans and robots fundamentally separate modes of exploration, or can humans and robots work together to synergistically explore the solar system? It is proposed that humans and robots can work together in exploring the planets by use of telerobotic operation to expand the function and usefulness of human explorers, and to extend the range of human exploration to hostile environments. Published by Elsevier Ltd.

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.

Physiological and subjective evaluation of a human-robot object hand-over task.

Science.gov (United States)

Dehais, Frédéric; Sisbot, Emrah Akin; Alami, Rachid; Causse, Mickaël

2011-11-01

In the context of task sharing between a robot companion and its human partners, the notions of safe and compliant hardware are not enough. It is necessary to guarantee ergonomic robot motions. Therefore, we have developed Human Aware Manipulation Planner (Sisbot et al., 2010), a motion planner specifically designed for human-robot object transfer by explicitly taking into account the legibility, the safety and the physical comfort of robot motions. The main objective of this research was to define precise subjective metrics to assess our planner when a human interacts with a robot in an object hand-over task. A second objective was to obtain quantitative data to evaluate the effect of this interaction. Given the short duration, the "relative ease" of the object hand-over task and its qualitative component, classical behavioral measures based on accuracy or reaction time were unsuitable to compare our gestures. In this perspective, we selected three measurements based on the galvanic skin conductance response, the deltoid muscle activity and the ocular activity. To test our assumptions and validate our planner, an experimental set-up involving Jido, a mobile manipulator robot, and a seated human was proposed. For the purpose of the experiment, we have defined three motions that combine different levels of legibility, safety and physical comfort values. After each robot gesture the participants were asked to rate them on a three dimensional subjective scale. It has appeared that the subjective data were in favor of our reference motion. Eventually the three motions elicited different physiological and ocular responses that could be used to partially discriminate them. Copyright © 2011 Elsevier Ltd and the Ergonomics Society. All rights reserved.

Humanoid Robots and Human Society

OpenAIRE

Bahishti, Adam A

2017-01-01

Almost every aspect of modern human life starting from the smartphone to the smart houses you live in has been influenced by science and technology. The field of science and technology has advanced throughout the last few decades. Among those advancements, robots have become significant by managing most of our day-to-day tasks and trying to get close to human lives. As robotics and autonomous systems flourish, human-robot relationships are becoming increasingly important. Recently humanoid ro...

Mini AERCam Inspection Robot for Human Space Missions

Science.gov (United States)

Fredrickson, Steven E.; Duran, Steve; Mitchell, Jennifer D.

2004-01-01

The Engineering Directorate of NASA Johnson Space Center has developed a nanosatellite-class free-flyer intended for future external inspection and remote viewing of human spacecraft. The Miniature Autonomous Extravehicular Robotic Camera (Mini AERCam) technology demonstration unit has been integrated into the approximate form and function of a flight system. The spherical Mini AERCam free flyer is 7.5 inches in diameter and weighs approximately 10 pounds, yet it incorporates significant additional capabilities compared to the 35 pound, 14 inch AERCam Sprint that flew as a Shuttle flight experiment in 1997. Mini AERCam hosts a full suite of miniaturized avionics, instrumentation, communications, navigation, imaging, power, and propulsion subsystems, including digital video cameras and a high resolution still image camera. The vehicle is designed for either remotely piloted operations or supervised autonomous operations including automatic stationkeeping and point-to-point maneuvering. Mini AERCam is designed to fulfill the unique requirements and constraints associated with using a free flyer to perform external inspections and remote viewing of human spacecraft operations. This paper describes the application of Mini AERCam for stand-alone spacecraft inspection, as well as for roles on teams of humans and robots conducting future space exploration missions.

When Humanoid Robots Become Human-Like Interaction Partners: Corepresentation of Robotic Actions

Science.gov (United States)

Stenzel, Anna; Chinellato, Eris; Bou, Maria A. Tirado; del Pobil, Angel P.; Lappe, Markus; Liepelt, Roman

2012-01-01

In human-human interactions, corepresenting a partner's actions is crucial to successfully adjust and coordinate actions with others. Current research suggests that action corepresentation is restricted to interactions between human agents facilitating social interaction with conspecifics. In this study, we investigated whether action…

Specific Human Capital as a Source of Superior Team Performance

OpenAIRE

Egon Franck; Stephan Nüesch; Jan Pieper

2009-01-01

In this paper, we empirically investigate the performance effect of team-specific human capital in highly interactive teams. Based on the tenets of the resource-based view of the firm and on the ideas of typical learning functions, we hypothesize that team members’ shared experience in working together positively impacts team performance, but at diminishing rates. Holding a team’s stock of general human capital and other potential drivers constant, we find support for this prediction. Implica...

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

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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

A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Human-Robot Interaction

Science.gov (United States)

2014-07-01

however, 27 of these articles had insufficient information to calculate effect size. Authors were contacted via email and were given 5 weeks to... Multitasking Personality Robot Personality Communication Mode States Team Collaboration Fatigue Capability In-group Membership Stress

Human futures amongst robot teachers?

DEFF Research Database (Denmark)

Nørgård, Rikke Toft; Bhroin, Niamh Ni; Ess, Charles Melvin

2017-01-01

In 2009 the world’s first robot teacher, Saya, was introduced into a classroom. Saya could express six basic emotions and shout orders like 'be quiet'. Since 2009, instructional robot technologies have emerged around the world and it is estimated that robot teachers may become a regular...... technological feature in the classroom and even 'take over' from human teachers within the next ten to fifteen years.   The paper set out to examine some of the possible ethical implications for human futures in relation to the immanent rise of robot teachers. This is done through combining perspectives...... on technology coming from design, science and technology, education, and philosophy (McCarthy & Wright, 2004; Jasanoff, 2016; Selwyn 2016; Verbeek, 2011). The framework calls attention to how particular robot teachers institute certain educational, experiential and existential terrains within which human...

Influence of facial feedback during a cooperative human-robot task in schizophrenia.

Science.gov (United States)

Cohen, Laura; Khoramshahi, Mahdi; Salesse, Robin N; Bortolon, Catherine; Słowiński, Piotr; Zhai, Chao; Tsaneva-Atanasova, Krasimira; Di Bernardo, Mario; Capdevielle, Delphine; Marin, Ludovic; Schmidt, Richard C; Bardy, Benoit G; Billard, Aude; Raffard, Stéphane

2017-11-03

Rapid progress in the area of humanoid robots offers tremendous possibilities for investigating and improving social competences in people with social deficits, but remains yet unexplored in schizophrenia. In this study, we examined the influence of social feedbacks elicited by a humanoid robot on motor coordination during a human-robot interaction. Twenty-two schizophrenia patients and twenty-two matched healthy controls underwent a collaborative motor synchrony task with the iCub humanoid robot. Results revealed that positive social feedback had a facilitatory effect on motor coordination in the control participants compared to non-social positive feedback. This facilitatory effect was not present in schizophrenia patients, whose social-motor coordination was similarly impaired in social and non-social feedback conditions. Furthermore, patients' cognitive flexibility impairment and antipsychotic dosing were negatively correlated with patients' ability to synchronize hand movements with iCub. Overall, our findings reveal that patients have marked difficulties to exploit facial social cues elicited by a humanoid robot to modulate their motor coordination during human-robot interaction, partly accounted for by cognitive deficits and medication. This study opens new perspectives for comprehension of social deficits in this mental disorder.

Pilot Study of Person Robot Interaction in a Public Transit Space

DEFF Research Database (Denmark)

Svenstrup, Mikael; Bak, Thomas; Maler, Ouri

2009-01-01

This paper describes a study of the effect of a human interactive robot placed in an urban transit space. The underlying hypothesis is that it is possible to create interesting new living spaces and induce value in terms of experiences, information or economics, by putting socially interactive...... showed harder than expected to start interaction with commuters due to their determination and speed towards their goal. Further it was demonstrated that it was possible to track and follow people, who were not beforehand informed about the experiment. The evaluation indicated that the distance...... to initiate interaction was shorter than would be expected for normal human to human interaction....

How does a surgeon’s brain buzz? An EEG coherence study on the interaction between humans and robot

Science.gov (United States)

2013-01-01

Introduction In humans, both primary and non-primary motor areas are involved in the control of voluntary movements. However, the dynamics of functional coupling among different motor areas have not been fully clarified yet. There is to date no research looking to the functional dynamics in the brain of surgeons working in laparoscopy compared with those trained and working in robotic surgery. Experimental procedures We enrolled 16 right-handed trained surgeons and assessed changes in intra- and inter-hemispheric EEG coherence with a 32-channels device during the same motor task with either a robotic or a laparoscopic approach. Estimates of auto and coherence spectra were calculated by a fast Fourier transform algorithm implemented on Matlab 5.3. Results We found increase of coherence in surgeons performing laparoscopy, especially in theta and lower alpha activity, in all experimental conditions (M1 vs. SMA, S1 vs. SMA, S1 vs. pre-SMA and M1 vs. S1; p with different approaches. To the best of our knowledge, this is the first study that tried to assess semi-quantitative differences during the interaction between normal human brain and robotic devices. PMID:23607324

Next Generation Simulation Framework for Robotic and Human Space Missions

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Cameron, Jonathan M.; Balaram, J.; Jain, Abhinandan; Kuo, Calvin; Lim, Christopher; Myint, Steven

2012-01-01

The Dartslab team at NASA's Jet Propulsion Laboratory (JPL) has a long history of developing physics-based simulations based on the Darts/Dshell simulation framework that have been used to simulate many planetary robotic missions, such as the Cassini spacecraft and the rovers that are currently driving on Mars. Recent collaboration efforts between the Dartslab team at JPL and the Mission Operations Directorate (MOD) at NASA Johnson Space Center (JSC) have led to significant enhancements to the Dartslab DSENDS (Dynamics Simulator for Entry, Descent and Surface landing) software framework. The new version of DSENDS is now being used for new planetary mission simulations at JPL. JSC is using DSENDS as the foundation for a suite of software known as COMPASS (Core Operations, Mission Planning, and Analysis Spacecraft Simulation) that is the basis for their new human space mission simulations and analysis. In this paper, we will describe the collaborative process with the JPL Dartslab and the JSC MOD team that resulted in the redesign and enhancement of the DSENDS software. We will outline the improvements in DSENDS that simplify creation of new high-fidelity robotic/spacecraft simulations. We will illustrate how DSENDS simulations are assembled and show results from several mission simulations.

Region of eye contact of humanoid Nao robot is similar to that of a human

NARCIS (Netherlands)

Cuijpers, R.H.; Pol, van der D.; Herrmann, G.; Pearson, M.J.; Lenz, A.; Bremner, P.; Spiers, A.; Leonards, U.

2013-01-01

Eye contact is an important social cue in human-human interaction, but it is unclear how easily it carries over to humanoid robots. In this study we investigated whether the tolerance of making eye contact is similar for the Nao robot as compared to human lookers. We measured the region of eye

Child, Robot and Educational Material : A Triadic Interaction

NARCIS (Netherlands)

Davison, Daniel Patrick

The process in which a child and a robot work together to solve a learning task can be characterised as a triadic interaction. Interactions between the child and robot; the child and learning materials; and the robot and learning materials will each shape the perception and appreciation the child

Child, Robot and Educational Material: A Triadic Interaction

NARCIS (Netherlands)

Davison, Daniel Patrick

The process in which a child and a robot work together to solve a learning task can be characterised as a triadic interaction. Interactions between the child and robot; the child and learning materials; and the robot and learning materials will each shape the perception and appreciation the child

Progress in EEG-Based Brain Robot Interaction Systems

Directory of Open Access Journals (Sweden)

Xiaoqian Mao

2017-01-01

Full Text Available The most popular noninvasive Brain Robot Interaction (BRI technology uses the electroencephalogram- (EEG- based Brain Computer Interface (BCI, to serve as an additional communication channel, for robot control via brainwaves. This technology is promising for elderly or disabled patient assistance with daily life. The key issue of a BRI system is to identify human mental activities, by decoding brainwaves, acquired with an EEG device. Compared with other BCI applications, such as word speller, the development of these applications may be more challenging since control of robot systems via brainwaves must consider surrounding environment feedback in real-time, robot mechanical kinematics, and dynamics, as well as robot control architecture and behavior. This article reviews the major techniques needed for developing BRI systems. In this review article, we first briefly introduce the background and development of mind-controlled robot technologies. Second, we discuss the EEG-based brain signal models with respect to generating principles, evoking mechanisms, and experimental paradigms. Subsequently, we review in detail commonly used methods for decoding brain signals, namely, preprocessing, feature extraction, and feature classification, and summarize several typical application examples. Next, we describe a few BRI applications, including wheelchairs, manipulators, drones, and humanoid robots with respect to synchronous and asynchronous BCI-based techniques. Finally, we address some existing problems and challenges with future BRI techniques.

Fuzzy variable impedance control based on stiffness identification for human-robot cooperation

Science.gov (United States)

Mao, Dachao; Yang, Wenlong; Du, Zhijiang

2017-06-01

This paper presents a dynamic fuzzy variable impedance control algorithm for human-robot cooperation. In order to estimate the intention of human for co-manipulation, a fuzzy inference system is set up to adjust the impedance parameter. Aiming at regulating the output fuzzy universe based on the human arm’s stiffness, an online stiffness identification method is developed. A drag interaction task is conducted on a 5-DOF robot with variable impedance control. Experimental results demonstrate that the proposed algorithm is superior.

Augmented Robotics Dialog System for Enhancing Human–Robot Interaction

Science.gov (United States)

Alonso-Martín, Fernando; Castro-González, Aívaro; de Gorostiza Luengo, Francisco Javier Fernandez; Salichs, Miguel Ángel

2015-01-01

Augmented reality, augmented television and second screen are cutting edge technologies that provide end users extra and enhanced information related to certain events in real time. This enriched information helps users better understand such events, at the same time providing a more satisfactory experience. In the present paper, we apply this main idea to human–robot interaction (HRI), to how users and robots interchange information. The ultimate goal of this paper is to improve the quality of HRI, developing a new dialog manager system that incorporates enriched information from the semantic web. This work presents the augmented robotic dialog system (ARDS), which uses natural language understanding mechanisms to provide two features: (i) a non-grammar multimodal input (verbal and/or written) text; and (ii) a contextualization of the information conveyed in the interaction. This contextualization is achieved by information enrichment techniques that link the extracted information from the dialog with extra information about the world available in semantic knowledge bases. This enriched or contextualized information (information enrichment, semantic enhancement or contextualized information are used interchangeably in the rest of this paper) offers many possibilities in terms of HRI. For instance, it can enhance the robot's pro-activeness during a human–robot dialog (the enriched information can be used to propose new topics during the dialog, while ensuring a coherent interaction). Another possibility is to display additional multimedia content related to the enriched information on a visual device. This paper describes the ARDS and shows a proof of concept of its applications. PMID:26151202

Human-robot collaboration for a shared mission

OpenAIRE

Karami , Abir-Beatrice; Jeanpierre , Laurent; Mouaddib , Abdel-Illah

2010-01-01

International audience; We are interested in collaboration domains between a robot and a human partner, the partners share a common mission without an explicit communication about their plans. The decision process of the robot agent should consider the presence of its human partner. Also, the robot planning should be flexible to human comfortability and all possible changes in the shared environment. To solve the problem of human-robot collaborationwith no communication, we present a model th...

Human Factors Principles in Design of Computer-Mediated Visualization for Robot Missions

Energy Technology Data Exchange (ETDEWEB)

David I Gertman; David J Bruemmer

2008-12-01

With increased use of robots as a resource in missions supporting countermine, improvised explosive devices (IEDs), and chemical, biological, radiological nuclear and conventional explosives (CBRNE), fully understanding the best means by which to complement the human operator’s underlying perceptual and cognitive processes could not be more important. Consistent with control and display integration practices in many other high technology computer-supported applications, current robotic design practices rely highly upon static guidelines and design heuristics that reflect the expertise and experience of the individual designer. In order to use what we know about human factors (HF) to drive human robot interaction (HRI) design, this paper reviews underlying human perception and cognition principles and shows how they were applied to a threat detection domain.

Toward Multimodal Human-Robot Interaction to Enhance Active Participation of Users in Gait Rehabilitation.

Science.gov (United States)

Gui, Kai; Liu, Honghai; Zhang, Dingguo

2017-11-01

Robotic exoskeletons for physical rehabilitation have been utilized for retraining patients suffering from paraplegia and enhancing motor recovery in recent years. However, users are not voluntarily involved in most systems. This paper aims to develop a locomotion trainer with multiple gait patterns, which can be controlled by the active motion intention of users. A multimodal human-robot interaction (HRI) system is established to enhance subject's active participation during gait rehabilitation, which includes cognitive HRI (cHRI) and physical HRI (pHRI). The cHRI adopts brain-computer interface based on steady-state visual evoked potential. The pHRI is realized via admittance control based on electromyography. A central pattern generator is utilized to produce rhythmic and continuous lower joint trajectories, and its state variables are regulated by cHRI and pHRI. A custom-made leg exoskeleton prototype with the proposed multimodal HRI is tested on healthy subjects and stroke patients. The results show that voluntary and active participation can be effectively involved to achieve various assistive gait patterns.

Toward a tactile language for human-robot interaction: two studies of tacton learning and performance.

Science.gov (United States)

Barber, Daniel J; Reinerman-Jones, Lauren E; Matthews, Gerald

2015-05-01

Two experiments were performed to investigate the feasibility for robot-to-human communication of a tactile language using a lexicon of standardized tactons (tactile icons) within a sentence. Improvements in autonomous systems technology and a growing demand within military operations are spurring interest in communication via vibrotactile displays. Tactile communication may become an important element of human-robot interaction (HRI), but it requires the development of messaging capabilities approaching the communication power of the speech and visual signals used in the military. In Experiment 1 (N = 38), we trained participants to identify sets of directional, dynamic, and static tactons and tested performance and workload following training. In Experiment 2 (N = 76), we introduced an extended training procedure and tested participants' ability to correctly identify two-tacton phrases. We also investigated the impact of multitasking on performance and workload. Individual difference factors were assessed. Experiment 1 showed that participants found dynamic and static tactons difficult to learn, but the enhanced training procedure in Experiment 2 produced competency in performance for all tacton categories. Participants in the latter study also performed well on two-tacton phrases and when multitasking. However, some deficits in performance and elevation of workload were observed. Spatial ability predicted some aspects of performance in both studies. Participants may be trained to identify both single tactons and tacton phrases, demonstrating the feasibility of developing a tactile language for HRI. Tactile communication may be incorporated into multi-modal communication systems for HRI. It also has potential for human-human communication in challenging environments. © 2014, Human Factors and Ergonomics Society.

An Interactive Human Interface Arm Robot with the Development of Food Aid

Directory of Open Access Journals (Sweden)

NASHWAN D. Zaki

2012-03-01

Full Text Available A robotic system for the disabled who needs supports at meal is proposed. A feature of this system is that the robotic aid system can communicate with the operator using the speech recognition and speech synthesis functions. Another feature is that the robotic aid system uses an image processing, and by doing this the system can recognize the environmental situations of the dishes, cups and so on. Due to this image processing function, the operator does not need to specify the position and the posture of the dishes and target objects. Furthermore, combination communication between speech and image processing will enables a friendly man-machine to communicate with each other, since speech and visual information are essential in the human communication.

Human-machine Interface for Presentation Robot

Czech Academy of Sciences Publication Activity Database

Krejsa, Jiří; Ondroušek, V.

2012-01-01

Roč. 6, č. 2 (2012), s. 17-21 ISSN 1897-8649 Institutional research plan: CEZ:AV0Z20760514 Keywords : human-robot interface * mobile robot * presentation robot Subject RIV: JD - Computer Applications, Robotics

A remote lab for experiments with a team of mobile robots.

Science.gov (United States)

Casini, Marco; Garulli, Andrea; Giannitrapani, Antonio; Vicino, Antonio

2014-09-04

In this paper, a remote lab for experimenting with a team of mobile robots is presented. Robots are built with the LEGO Mindstorms technology and user-defined control laws can be directly coded in the Matlab programming language and validated on the real system. The lab is versatile enough to be used for both teaching and research purposes. Students can easily go through a number of predefined mobile robotics experiences without having to worry about robot hardware or low-level programming languages. More advanced experiments can also be carried out by uploading custom controllers. The capability to have full control of the vehicles, together with the possibility to define arbitrarily complex environments through the definition of virtual obstacles, makes the proposed facility well suited to quickly test and compare different control laws in a real-world scenario. Moreover, the user can simulate the presence of different types of exteroceptive sensors on board of the robots or a specific communication architecture among the agents, so that decentralized control strategies and motion coordination algorithms can be easily implemented and tested. A number of possible applications and real experiments are presented in order to illustrate the main features of the proposed mobile robotics remote lab.

A Remote Lab for Experiments with a Team of Mobile Robots

Directory of Open Access Journals (Sweden)

Marco Casini

2014-09-01

Full Text Available In this paper, a remote lab for experimenting with a team of mobile robots is presented. Robots are built with the LEGO Mindstorms technology and user-defined control laws can be directly coded in the Matlab programming language and validated on the real system. The lab is versatile enough to be used for both teaching and research purposes. Students can easily go through a number of predefined mobile robotics experiences without having to worry about robot hardware or low-level programming languages. More advanced experiments can also be carried out by uploading custom controllers. The capability to have full control of the vehicles, together with the possibility to define arbitrarily complex environments through the definition of virtual obstacles, makes the proposed facility well suited to quickly test and compare different control laws in a real-world scenario. Moreover, the user can simulate the presence of different types of exteroceptive sensors on board of the robots or a specific communication architecture among the agents, so that decentralized control strategies and motion coordination algorithms can be easily implemented and tested. A number of possible applications and real experiments are presented in order to illustrate the main features of the proposed mobile robotics remote lab.

Advances in Robotics and Virtual Reality

CERN Document Server

Hassanien, Aboul

2012-01-01

A beyond human knowledge and reach, robotics is strongly involved in tackling challenges of new emerging multidisciplinary fields. Together with humans, robots are busy exploring and working on the new generation of ideas and problems whose solution is otherwise impossible to find. The future is near when robots will sense, smell and touch people and their lives. Behind this practical aspect of human-robotics, there is a half a century spanned robotics research, which transformed robotics into a modern science. The Advances in Robotics and Virtual Reality is a compilation of emerging application areas of robotics. The book covers robotics role in medicine, space exploration and also explains the role of virtual reality as a non-destructive test bed which constitutes a premise of further advances towards new challenges in robotics. This book, edited by two famous scientists with the support of an outstanding team of fifteen authors, is a well suited reference for robotics researchers and scholars from related ...

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.

Nasa's Ant-Inspired Swarmie Robots

Science.gov (United States)

Leucht, Kurt W.

2016-01-01

As humans push further beyond the grasp of earth, robotic missions in advance of human missions will play an increasingly important role. These robotic systems will find and retrieve valuable resources as part of an in-situ resource utilization (ISRU) strategy. They will need to be highly autonomous while maintaining high task performance levels. NASA Kennedy Space Center has teamed up with the Biological Computation Lab at the University of New Mexico to create a swarm of small, low-cost, autonomous robots to be used as a ground-based research platform for ISRU missions. The behavior of the robot swarm mimics the central-place foraging strategy of ants to find and collect resources in a previously unmapped environment and return those resources to a central site. This talk will guide the audience through the Swarmie robot project from its conception by students in a New Mexico research lab to its robot trials in an outdoor parking lot at NASA. The software technologies and techniques used on the project will be discussed, as well as various challenges and solutions that were encountered by the development team along the way.

Brain Computer Interfaces for Enhanced Interaction with Mobile Robot Agents

Science.gov (United States)

2016-07-27

SECURITY CLASSIFICATION OF: Brain Computer Interfaces (BCIs) show great potential in allowing humans to interact with computational environments in a...Distribution Unlimited UU UU UU UU 27-07-2016 17-Sep-2013 16-Sep-2014 Final Report: Brain Computer Interfaces for Enhanced Interactions with Mobile Robot...published in peer-reviewed journals: Number of Papers published in non peer-reviewed journals: Final Report: Brain Computer Interfaces for Enhanced

Fundamentals of soft robot locomotion.

Science.gov (United States)

Calisti, M; Picardi, G; Laschi, C

2017-05-01

Soft robotics and its related technologies enable robot abilities in several robotics domains including, but not exclusively related to, manipulation, manufacturing, human-robot interaction and locomotion. Although field applications have emerged for soft manipulation and human-robot interaction, mobile soft robots appear to remain in the research stage, involving the somehow conflictual goals of having a deformable body and exerting forces on the environment to achieve locomotion. This paper aims to provide a reference guide for researchers approaching mobile soft robotics, to describe the underlying principles of soft robot locomotion with its pros and cons, and to envisage applications and further developments for mobile soft robotics. © 2017 The Author(s).

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

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

Designing Emotionally Expressive Robots

DEFF Research Database (Denmark)

Tsiourti, Christiana; Weiss, Astrid; Wac, Katarzyna

2017-01-01

Socially assistive agents, be it virtual avatars or robots, need to engage in social interactions with humans and express their internal emotional states, goals, and desires. In this work, we conducted a comparative study to investigate how humans perceive emotional cues expressed by humanoid...... robots through five communication modalities (face, head, body, voice, locomotion) and examined whether the degree of a robot's human-like embodiment affects this perception. In an online survey, we asked people to identify emotions communicated by Pepper -a highly human-like robot and Hobbit – a robot...... for robots....

Detecting Biological Motion for Human–Robot Interaction: A Link between Perception and Action

Directory of Open Access Journals (Sweden)

Alessia Vignolo

2017-06-01

Full Text Available One of the fundamental skills supporting safe and comfortable interaction between humans is their capability to understand intuitively each other’s actions and intentions. At the basis of this ability is a special-purpose visual processing that human brain has developed to comprehend human motion. Among the first “building blocks” enabling the bootstrapping of such visual processing is the ability to detect movements performed by biological agents in the scene, a skill mastered by human babies in the first days of their life. In this paper, we present a computational model based on the assumption that such visual ability must be based on local low-level visual motion features, which are independent of shape, such as the configuration of the body and perspective. Moreover, we implement it on the humanoid robot iCub, embedding it into a software architecture that leverages the regularities of biological motion also to control robot attention and oculomotor behaviors. In essence, we put forth a model in which the regularities of biological motion link perception and action enabling a robotic agent to follow a human-inspired sensory-motor behavior. We posit that this choice facilitates mutual understanding and goal prediction during collaboration, increasing the pleasantness and safety of the interaction.

Reconnaissance and Autonomy for Small Robots (RASR) team: MAGIC 2010 challenge

Science.gov (United States)

Lacaze, Alberto; Murphy, Karl; Del Giorno, Mark; Corley, Katrina

2012-06-01

The Reconnaissance and Autonomy for Small Robots (RASR) team developed a system for the coordination of groups of unmanned ground vehicles (UGVs) that can execute a variety of military relevant missions in dynamic urban environments. Historically, UGV operations have been primarily performed via tele-operation, requiring at least one dedicated operator per robot, and requiring substantial real-time bandwidth to accomplish those missions. Our team goal was to develop a system that can provide long-term value to the war-fighter, utilizing MAGIC-2010 as a stepping stone. To that end, we self-imposed a set of constraints that would force us to develop technology that could readily be used by the military in the near term: • Use a relevant (deployed) platform • Use low-cost, reliable sensors • Develop an expandable and modular control system with innovative software algorithms to minimize the computing footprint required • Minimize required communications bandwidth and handle communication losses • Minimize additional power requirements to maximize battery life and mission duration

Human Assisted Robotic Vehicle Studies - A conceptual end-to-end mission architecture

Science.gov (United States)

Lehner, B. A. E.; Mazzotta, D. G.; Teeney, L.; Spina, F.; Filosa, A.; Pou, A. Canals; Schlechten, J.; Campbell, S.; Soriano, P. López

2017-11-01

With current space exploration roadmaps indicating the Moon as a proving ground on the way to human exploration of Mars, it is clear that human-robotic partnerships will play a key role for successful future human space missions. This paper details a conceptual end-to-end architecture for an exploration mission in cis-lunar space with a focus on human-robot interactions, called Human Assisted Robotic Vehicle Studies (HARVeSt). HARVeSt will build on knowledge of plant growth in space gained from experiments on-board the ISS and test the first growth of plants on the Moon. A planned deep space habitat will be utilised as the base of operations for human-robotic elements of the mission. The mission will serve as a technology demonstrator not only for autonomous tele-operations in cis-lunar space but also for key enabling technologies for future human surface missions. The successful approach of the ISS will be built on in this mission with international cooperation. Mission assets such as a modular rover will allow for an extendable mission and to scout and prepare the area for the start of an international Moon Village.

Avoiding Local Optima with Interactive Evolutionary Robotics

Science.gov (United States)

2012-07-09

the top of a flight of stairs selects for climbing ; suspending the robot and the target object above the ground and creating rungs between the two will...REPORT Avoiding Local Optimawith Interactive Evolutionary Robotics 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: The main bottleneck in evolutionary... robotics has traditionally been the time required to evolve robot controllers. However with the continued acceleration in computational resources, the

Children with Autism Spectrum Disorders Make a Fruit Salad with Probo, the Social Robot: An Interaction Study

Science.gov (United States)

Simut, Ramona E.; Vanderfaeillie, Johan; Peca, Andreea; Van de Perre, Greet; Vanderborght, Bram

2016-01-01

Social robots are thought to be motivating tools in play tasks with children with autism spectrum disorders. Thirty children with autism were included using a repeated measurements design. It was investigated if the children's interaction with a human differed from the interaction with a social robot during a play task. Also, it was examined if…

Acceptance and Attitudes Toward a Human-like Socially Assistive Robot by Older Adults.

Science.gov (United States)

Louie, Wing-Yue Geoffrey; McColl, Derek; Nejat, Goldie

2014-01-01

Recent studies have shown that cognitive and social interventions are crucial to the overall health of older adults including their psychological, cognitive, and physical well-being. However, due to the rapidly growing elderly population of the world, the resources and people to provide these interventions is lacking. Our work focuses on the use of social robotic technologies to provide person-centered cognitive interventions. In this article, we investigate the acceptance and attitudes of older adults toward the human-like expressive socially assistive robot Brian 2.1 in order to determine if the robot's human-like assistive and social characteristics would promote the use of the robot as a cognitive and social interaction tool to aid with activities of daily living. The results of a robot acceptance questionnaire administered during a robot demonstration session with a group of 46 elderly adults showed that the majority of the individuals had positive attitudes toward the socially assistive robot and its intended applications.

Exploring multimodal robotic interaction through storytelling for aphasics

NARCIS (Netherlands)

Mubin, O.; Al Mahmud, A.; Abuelma'atti, O.; England, D.

2008-01-01

In this poster, we propose the design of a multimodal robotic interaction mechanism that is intended to be used by Aphasics for storytelling. Through limited physical interaction, mild to moderate aphasic people can interact with a robot that may help them to be more active in their day to day

Application of Human-Autonomy Teaming (HAT) Patterns to Reduce Crew Operations (RCO)

Science.gov (United States)

Shively, R. Jay; Brandt, Summer L.; Lachter, Joel; Matessa, Mike; Sadler, Garrett; Battiste, Henri

2016-01-01

Unmanned aerial systems, robotics, advanced cockpits, and air traffic management are all examples of domains that are seeing dramatic increases in automation. While automation may take on some tasks previously performed by humans, humans will still be required, for the foreseeable future, to remain in the system. The collaboration with humans and these increasingly autonomous systems will begin to resemble cooperation between teammates, rather than simple task allocation. It is critical to understand this human-autonomy teaming (HAT) to optimize these systems in the future. One methodology to understand HAT is by identifying recurring patterns of HAT that have similar characteristics and solutions. This paper applies a methodology for identifying HAT patterns to an advanced cockpit project.

A taxonomy for user-healthcare robot interaction.

Science.gov (United States)

Bzura, Conrad; Im, Hosung; Liu, Tammy; Malehorn, Kevin; Padir, Taskin; Tulu, Bengisu

2012-01-01

This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologies and user acceptance of robotics. Characterization of the user, or in this case the patient, is a primary focus of the paper, as they present a unique new role as robot users. While therapeutic and monitoring-related applications for robots are still relatively uncommon, we believe they will begin to grow and thus it is important that the spurring relationship between robot and patient is well understood.

Visual and tactile interfaces for bi-directional human robot communication

Science.gov (United States)

Barber, Daniel; Lackey, Stephanie; Reinerman-Jones, Lauren; Hudson, Irwin

2013-05-01

Seamless integration of unmanned and systems and Soldiers in the operational environment requires robust communication capabilities. Multi-Modal Communication (MMC) facilitates achieving this goal due to redundancy and levels of communication superior to single mode interaction using auditory, visual, and tactile modalities. Visual signaling using arm and hand gestures is a natural method of communication between people. Visual signals standardized within the U.S. Army Field Manual and in use by Soldiers provide a foundation for developing gestures for human to robot communication. Emerging technologies using Inertial Measurement Units (IMU) enable classification of arm and hand gestures for communication with a robot without the requirement of line-of-sight needed by computer vision techniques. These devices improve the robustness of interpreting gestures in noisy environments and are capable of classifying signals relevant to operational tasks. Closing the communication loop between Soldiers and robots necessitates them having the ability to return equivalent messages. Existing visual signals from robots to humans typically require highly anthropomorphic features not present on military vehicles. Tactile displays tap into an unused modality for robot to human communication. Typically used for hands-free navigation and cueing, existing tactile display technologies are used to deliver equivalent visual signals from the U.S. Army Field Manual. This paper describes ongoing research to collaboratively develop tactile communication methods with Soldiers, measure classification accuracy of visual signal interfaces, and provides an integration example including two robotic platforms.

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.

Parents' Appraisals of the Animacy and Likability of Socially Interactive Robots for Intervening with Young Children with Disabilities. Social Robots Research Reports, Number 2

Science.gov (United States)

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

2013-01-01

Findings from a survey of parents' ratings of seven different human-like qualities of four socially interactive robots are reported. The four robots were Popchilla, Keepon, Kaspar, and CosmoBot. The participants were 96 parents and other primary caregivers of young children with disabilities 1 to 12 years of age. Results showed that Popchilla, a…

A design-centred framework for social human-robot interaction

NARCIS (Netherlands)

Bartneck, C.; Forlizzi, J.

2004-01-01

Robots currently integrate into our everyday lives, but little is known about how they can act socially. In this paper, we propose a definition of social robots and describe a framework that classifies properties of social robots. The properties consist of form, modality, social norms, autonomy, and

Human-Robot Control Strategies for the NASA/DARPA Robonaut

Science.gov (United States)

Diftler, M. A.; Culbert, Chris J.; Ambrose, Robert O.; Huber, E.; Bluethmann, W. J.

2003-01-01

The Robotic Systems Technology Branch at the NASA Johnson Space Center (JSC) is currently developing robot systems to reduce the Extra-Vehicular Activity (EVA) and planetary exploration burden on astronauts. One such system, Robonaut, is capable of interfacing with external Space Station systems that currently have only human interfaces. Robonaut is human scale, anthropomorphic, and designed to approach the dexterity of a space-suited astronaut. Robonaut can perform numerous human rated tasks, including actuating tether hooks, manipulating flexible materials, soldering wires, grasping handrails to move along space station mockups, and mating connectors. More recently, developments in autonomous control and perception for Robonaut have enabled dexterous, real-time man-machine interaction. Robonaut is now capable of acting as a practical autonomous assistant to the human, providing and accepting tools by reacting to body language. A versatile, vision-based algorithm for matching range silhouettes is used for monitoring human activity as well as estimating tool pose.

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, ...

Improving Human/Autonomous System Teaming Through Linguistic Analysis

Science.gov (United States)

Meszaros, Erica L.

2016-01-01