Pose estimation-based path planning for a tracked mobile robot traversing uneven terrains

OpenAIRE

Jun , Jae-Yun; Saut , Jean-Philippe; Benamar , Faïz

2015-01-01

International audience; A novel path-planning algorithm is proposed for a tracked mobile robot to traverse uneven terrains, which can efficiently search for stability sub-optimal paths. This algorithm consists of combining two RRT-like algorithms (the Transition-based RRT (T-RRT) and the Dynamic-Domain RRT (DD-RRT) algorithms) bidirectionally and of representing the robot-terrain interaction with the robot’s quasi-static tip-over stability measure (assuming that the robot traverses uneven ter...

Fractional path planning and path tracking

International Nuclear Information System (INIS)

Melchior, P.; Jallouli-Khlif, R.; Metoui, B.

2011-01-01

This paper presents the main results of the application of fractional approach in path planning and path tracking. A new robust path planning design for mobile robot was studied in dynamic environment. The normalized attractive force applied to the robot is based on a fictitious fractional attractive potential. This method allows to obtain robust path planning despite robot mass variation. The danger level of each obstacles is characterized by the fractional order of the repulsive potential of the obstacles. Under these conditions, the robot dynamic behavior was studied by analyzing its X - Y path planning with dynamic target or dynamic obstacles. The case of simultaneously mobile obstacles and target is also considered. The influence of the robot mass variation is studied and the robustness analysis of the obtained path shows the robustness improvement due to the non integer order properties. Pre shaping approach is used to reduce system vibration in motion control. Desired systems inputs are altered so that the system finishes the requested move without residual vibration. This technique, developed by N.C. Singer and W.P.Seering, is used for flexible structure control, particularly in the aerospace field. In a previous work, this method was extended for explicit fractional derivative systems and applied to second generation CRONE control, the robustness was also studied. CRONE (the French acronym of C ommande Robuste d'Ordre Non Entier ) control system design is a frequency-domain based methodology using complex fractional integration.

Autonomously Implemented Versatile Path Planning for Mobile Robots Based on Cellular Automata and Ant Colony

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Adel Akbarimajd

2012-02-01

Full Text Available A path planning method for mobile robots based on two dimensional cellular automata is proposed. The method can be applied for environments with both concave and convex obstacles. It is also appropriate for multi-robot problems as well as dynamic environments. In order to develop the planning method, environment of the robot is decomposed to a rectangular grid and the automata is defined with four states including Robot cell, Free cell, Goal cell and Obstacle cell. Evolution rules of automata are proposed in order to direct the robot toward its goal. CA based path planner method is afterwards modified by a colony technique to be applicable for concave obstacles. Then a layered architecture is proposed to autonomously implement the planning algorithm. The architecture employs an abstraction approach which makes the complexity manageable. An important feature of the architecture is internal artifacts that have some beliefs about the world. Most actions of the robot are planned and performed with respect to these artifacts.

Path Planning and Navigation for Mobile Robots in a Hybrid Sensor Network without Prior Location Information

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Zheng Zhang

2013-03-01

Full Text Available In a hybrid wireless sensor network with mobile and static nodes, which have no prior geographical knowledge, successful navigation for mobile robots is one of the main challenges. In this paper, we propose two novel navigation algorithms for outdoor environments, which permit robots to travel from one static node to another along a planned path in the sensor field, namely the RAC and the IMAP algorithms. Using this, the robot can navigate without the help of a map, GPS or extra sensor modules, only using the received signal strength indication (RSSI and odometry. Therefore, our algorithms have the advantage of being cost-effective. In addition, a path planning algorithm to schedule mobile robots' travelling paths is presented, which focuses on shorter distances and robust paths for robots by considering the RSSI-Distance characteristics. The simulations and experiments conducted with an autonomous mobile robot show the effectiveness of the proposed algorithms in an outdoor environment.

A new multiple robot path planning algorithm: dynamic distributed particle swarm optimization.

Science.gov (United States)

Ayari, Asma; Bouamama, Sadok

2017-01-01

Multiple robot systems have become a major study concern in the field of robotic research. Their control becomes unreliable and even infeasible if the number of robots increases. In this paper, a new dynamic distributed particle swarm optimization (D 2 PSO) algorithm is proposed for trajectory path planning of multiple robots in order to find collision-free optimal path for each robot in the environment. The proposed approach consists in calculating two local optima detectors, LOD pBest and LOD gBest . Particles which are unable to improve their personal best and global best for predefined number of successive iterations would be replaced with restructured ones. Stagnation and local optima problems would be avoided by adding diversity to the population, without losing the fast convergence characteristic of PSO. Experiments with multiple robots are provided and proved effectiveness of such approach compared with the distributed PSO.

A Novel Randomized Search Technique for Multiple Mobile Robot Paths Planning In Repetitive Dynamic Environment

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Vahid Behravesh

2012-08-01

Full Text Available Presented article is studying the issue of path navigating for numerous robots. Our presented approach is based on both priority and the robust method for path finding in repetitive dynamic. Presented model can be generally implementable and useable: We do not assume any restriction regarding the quantity of levels of freedom for robots, and robots of diverse kinds can be applied at the same time. We proposed a random method and hill-climbing technique in the area based on precedence plans, which is used to determine a solution to a given trajectory planning problem and to make less the extent of total track. Our method plans trajectories for particular robots in the setting-time scope. Therefore, in order to specifying the interval of constant objects similar to other robots and the extent of the tracks which is traversed. For measuring the hazard for robots to conflict with each other it applied a method based on probability of the movements of robots. This algorithm applied to real robots with successful results. The proposed method performed and judged on both real robots and in simulation. We performed sequence of100tests with 8 robots for comparing with coordination method and current performances are effective. However, maximizing the performance is still possible. These performances estimations performed on Windows operating system and 3GHz Intel Pentium IV with and compiles with GCC 3.4. We used our PCGA robot for all experiments.  For a large environment of 19×15m2where we accomplished 40tests, our model is competent to plan high-quality paths in a severely short time (less than a second. Moreover, this article utilized lookup tables to keep expenses the formerly navigated robots made, increasing the number of robots don’t expand computation time.

Mobile Robots Path Planning Using the Overall Conflict Resolution and Time Baseline Coordination

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Yong Ma

2014-01-01

Full Text Available This paper aims at resolving the path planning problem in a time-varying environment based on the idea of overall conflict resolution and the algorithm of time baseline coordination. The basic task of the introduced path planning algorithms is to fulfill the automatic generation of the shortest paths from the defined start poses to their end poses with consideration of generous constraints for multiple mobile robots. Building on this, by using the overall conflict resolution, within the polynomial based paths, we take into account all the constraints including smoothness, motion boundary, kinematics constraints, obstacle avoidance, and safety constraints among robots together. And time baseline coordination algorithm is proposed to process the above formulated problem. The foremost strong point is that much time can be saved with our approach. Numerical simulations verify the effectiveness of our approach.

Constrained VPH+: a local path planning algorithm for a bio-inspired crawling robot with customized ultrasonic scanning sensor.

Science.gov (United States)

Rao, Akshay; Elara, Mohan Rajesh; Elangovan, Karthikeyan

This paper aims to develop a local path planning algorithm for a bio-inspired, reconfigurable crawling robot. A detailed description of the robotic platform is first provided, and the suitability for deployment of each of the current state-of-the-art local path planners is analyzed after an extensive literature review. The Enhanced Vector Polar Histogram algorithm is described and reformulated to better fit the requirements of the platform. The algorithm is deployed on the robotic platform in crawling configuration and favorably compared with other state-of-the-art local path planning algorithms.

Knowledge-inducing Global Path Planning for Robots in Environment with Hybrid Terrain

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Yi-nan Guo

2010-09-01

Full Text Available In complex environment with hybrid terrain, different regions may have different terrain. Path planning for robots in such environment is an open NP-complete problem, which lacks effective methods. The paper develops a novel global path planning method based on common sense and evolution knowledge by adopting dual evolution structure in culture algorithms. Common sense describes terrain information and feasibility of environment, which is used to evaluate and select the paths. Evolution knowledge describes the angle relationship between the path and the obstacles, or the common segments of paths, which is used to judge and repair infeasible individuals. Taken two types of environments with different obstacles and terrain as examples, simulation results indicate that the algorithm can effectively solve path planning problem in complex environment and decrease the computation complexity for judgment and repair of infeasible individuals. It also can improve the convergence speed and have better computation stability.

A Novel Path Planning for Robots Based on Rapidly-Exploring Random Tree and Particle Swarm Optimizer Algorithm

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Zhou Feng

2013-09-01

Full Text Available A based on Rapidly-exploring Random Tree(RRT and Particle Swarm Optimizer (PSO for path planning of the robot is proposed.First the grid method is built to describe the working space of the mobile robot,then the Rapidly-exploring Random Tree algorithm is used to obtain the global navigation path,and the Particle Swarm Optimizer algorithm is adopted to get the better path.Computer experiment results demonstrate that this novel algorithm can plan an optimal path rapidly in a cluttered environment.The successful obstacle avoidance is achieved,and the model is robust and performs reliably.

Path-Constrained Motion Planning for Robotics Based on Kinematic Constraints

NARCIS (Netherlands)

Dijk, van N.J.M.; Wouw, van de N.; Pancras, W.C.M.; Nijmeijer, H.

2007-01-01

Common robotic tracking tasks consist of motions along predefined paths. The design of time-optimal path-constrained trajectories for robotic applications is discussed in this paper. To increase industrial applicability, the proposed method accounts for robot kinematics together with actuator

Research and Implementation of Robot Path Planning Based onVSLAM

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Wang Zi-Qiang

2018-01-01

Full Text Available In order to solve the problem of warehouse logistics robots planpath in different scenes, this paper proposes a method based on visual simultaneous localization and mapping (VSLAM to build grid map of different scenes and use A* algorithm to plan path on the grid map. Firstly, we use VSLAMto reconstruct the environment in three-dimensionally. Secondly, based on the three-dimensional environment data, we calculate the accessibility of each grid to prepare occupied grid map (OGM for terrain description. Rely on the terrain information, we use the A* algorithm to solve path planning problem. We also optimize the A* algorithm and improve algorithm efficiency. Lastly, we verify the effectiveness and reliability of the proposed method by simulation and experimental results.

New Design of Mobile Robot Path Planning with Randomly Moving Obstacles

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T. A. Salih

2013-05-01

Full Text Available The navigation of a mobile robot in an unknown environment has always been a very challenging task. In order to achieve safe and autonomous navigation, the mobile robot needs to sense the surrounding environment and plans a collision-free path. This paper focuses on designing and implementing a mobile robot which has the ability of navigating smoothly in an unknown environment, avoiding collisions, without having to stop in front of obstacles, detecting leakage of combustible gases and transmitting a message of detection results to the civil defense unit automatically through the Internet to the E-mail. This design uses the implementation of artificial neural network (ANN on a new technology represented by Field Programmable Analog Array (FPAA for controlling the motion of the robot. The robot with the proposed controller is tested and has completed the required objective successfully.

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

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Nizar Hadi Abbas

2016-07-01

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

Path Planning for Non-Circular, Non-Holonomic Robots in Highly Cluttered Environments.

Science.gov (United States)

Samaniego, Ricardo; Lopez, Joaquin; Vazquez, Fernando

2017-08-15

This paper presents an algorithm for finding a solution to the problem of planning a feasible path for a slender autonomous mobile robot in a large and cluttered environment. The presented approach is based on performing a graph search on a kinodynamic-feasible lattice state space of high resolution; however, the technique is applicable to many search algorithms. With the purpose of allowing the algorithm to consider paths that take the robot through narrow passes and close to obstacles, high resolutions are used for the lattice space and the control set. This introduces new challenges because one of the most computationally expensive parts of path search based planning algorithms is calculating the cost of each one of the actions or steps that could potentially be part of the trajectory. The reason for this is that the evaluation of each one of these actions involves convolving the robot's footprint with a portion of a local map to evaluate the possibility of a collision, an operation that grows exponentially as the resolution is increased. The novel approach presented here reduces the need for these convolutions by using a set of offline precomputed maps that are updated, by means of a partial convolution, as new information arrives from sensors or other sources. Not only does this improve run-time performance, but it also provides support for dynamic search in changing environments. A set of alternative fast convolution methods are also proposed, depending on whether the environment is cluttered with obstacles or not. Finally, we provide both theoretical and experimental results from different experiments and applications.

Welding Robot Collision-Free Path Optimization

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Xuewu Wang

2017-02-01

Full Text Available Reasonable welding path has a significant impact on welding efficiency, and a collision-free path should be considered first in the process of welding robot path planning. The shortest path length is considered as an optimization objective, and obstacle avoidance is considered as the constraint condition in this paper. First, a grid method is used as a modeling method after the optimization objective is analyzed. For local collision-free path planning, an ant colony algorithm is selected as the search strategy. Then, to overcome the shortcomings of the ant colony algorithm, a secondary optimization is presented to improve the optimization performance. Finally, the particle swarm optimization algorithm is used to realize global path planning. Simulation results show that the desired welding path can be obtained based on the optimization strategy.

Towards heterogeneous robot team path planning: acquisition of multiple routes with a modified spline-based algorithm

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Lavrenov Roman

2017-01-01

Full Text Available Our research focuses on operation of a heterogeneous robotic group that carries out point-to point navigation in GPS-denied dynamic environment, applying a combined local and global planning approach. In this paper, we introduce a homotopy-based high-level planner, which uses a modified splinebased path-planning algorithm. The algorithm utilizes Voronoi graph for global planning and a set of optimization criteria for local improvements of selected paths. The simulation was implemented in Matlab environment.

Learning to improve path planning performance

International Nuclear Information System (INIS)

Chen, Pang C.

1995-04-01

In robotics, path planning refers to finding a short. collision-free path from an initial robot configuration to a desired configuratioin. It has to be fast to support real-time task-level robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To remedy this situation, we present and analyze a learning algorithm that uses past experience to increase future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a speedup-learning framework in which a slow but capable planner may be improved both cost-wise and capability-wise by a faster but less capable planner coupled with experience. The basic algorithm is suitable for stationary environments, and can be extended to accommodate changing environments with on-demand experience repair and object-attached experience abstraction. To analyze the algorithm, we characterize the situations in which the adaptive planner is useful, provide quantitative bounds to predict its behavior, and confirm our theoretical results with experiments in path planning of manipulators. Our algorithm and analysis are sufficiently, general that they may also be applied to other planning domains in which experience is useful

Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery

Energy Technology Data Exchange (ETDEWEB)

Vandewouw, Marlee M., E-mail: marleev@mie.utoronto.ca; Aleman, Dionne M. [Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8 (Canada); Jaffray, David A. [Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario M5G 2M9 (Canada)

2016-08-15

Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, are used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.

Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery

International Nuclear Information System (INIS)

Vandewouw, Marlee M.; Aleman, Dionne M.; Jaffray, David A.

2016-01-01

Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, are used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.

Path Planning of Free-Floating Robot in Cartesian Space Using Direct Kinematics

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Wenfu Xu

2007-03-01

Full Text Available Dynamic singularities make it difficult to plan the Cartesian path of free-floating robot. In order to avoid its effect, the direct kinematic equations are used for path planning in the paper. Here, the joint position, rate and acceleration are bounded. Firstly, the joint trajectories are parameterized by polynomial or sinusoidal functions. And the two parametric functions are compared in details. It is the first contribution of the paper that polynomial functions can be used when the joint angles are limited(In the similar work of other researchers, only sinusoidla functions could be used. Secondly, the joint functions are normalized and the system of equations about the parameters is established by integrating the differential kinematics equations. Normalization is another contribution of the paper. After normalization, the boundary of the parameters is determined beforehand, and the general criterion to assign the initial guess of the unknown parameters is supplied. The criterion is independent on the planning conditions such as the total time tf. Finally, the parametes are solved by the iterative Newtonian method. Modification of tf may not result in the recalculation of the parameters. Simulation results verify the path planning method.

Path Planning of Free-Floating Robot in Cartesian Space Using Direct Kinematics

Directory of Open Access Journals (Sweden)

Wenfu Xu

2008-11-01

Full Text Available Dynamic singularities make it difficult to plan the Cartesian path of freefloating robot. In order to avoid its effect, the direct kinematic equations are used for path planning in the paper. Here, the joint position, rate and acceleration are bounded. Firstly, the joint trajectories are parameterized by polynomial or sinusoidal functions. And the two parametric functions are compared in details. It is the first contribution of the paper that polynomial functions can be used when the joint angles are limited(In the similar work of other researchers, only sinusoidla functions could be used. Secondly, the joint functions are normalized and the system of equations about the parameters is established by integrating the differential kinematics equations. Normalization is another contribution of the paper. After normalization, the boundary of the parameters is determined beforehand, and the general criterion to assign the initial guess of the unknown parameters is supplied. The criterion is independent on the planning conditions such as the total time tf. Finally, the parametes are solved by the iterative Newtonian method. Modification of tf may not result in the recalculation of the parameters. Simulation results verify the path planning method.

Interactive multi-objective path planning through a palette-based user interface

Science.gov (United States)

Shaikh, Meher T.; Goodrich, Michael A.; Yi, Daqing; Hoehne, Joseph

2016-05-01

n a problem where a human uses supervisory control to manage robot path-planning, there are times when human does the path planning, and if satisfied commits those paths to be executed by the robot, and the robot executes that plan. In planning a path, the robot often uses an optimization algorithm that maximizes or minimizes an objective. When a human is assigned the task of path planning for robot, the human may care about multiple objectives. This work proposes a graphical user interface (GUI) designed for interactive robot path-planning when an operator may prefer one objective over others or care about how multiple objectives are traded off. The GUI represents multiple objectives using the metaphor of an artist's palette. A distinct color is used to represent each objective, and tradeoffs among objectives are balanced in a manner that an artist mixes colors to get the desired shade of color. Thus, human intent is analogous to the artist's shade of color. We call the GUI an "Adverb Palette" where the word "Adverb" represents a specific type of objective for the path, such as the adverbs "quickly" and "safely" in the commands: "travel the path quickly", "make the journey safely". The novel interactive interface provides the user an opportunity to evaluate various alternatives (that tradeoff between different objectives) by allowing her to visualize the instantaneous outcomes that result from her actions on the interface. In addition to assisting analysis of various solutions given by an optimization algorithm, the palette has additional feature of allowing the user to define and visualize her own paths, by means of waypoints (guiding locations) thereby spanning variety for planning. The goal of the Adverb Palette is thus to provide a way for the user and robot to find an acceptable solution even though they use very different representations of the problem. Subjective evaluations suggest that even non-experts in robotics can carry out the planning tasks with a

Singularities of robot mechanisms numerical computation and avoidance path planning

CERN Document Server

Bohigas, Oriol; Ros, Lluís

2017-01-01

This book presents the singular configurations associated with a robot mechanism, together with robust methods for their computation, interpretation, and avoidance path planning. Having such methods is essential as singularities generally pose problems to the normal operation of a robot, but also determine the workspaces and motion impediments of its underlying mechanical structure. A distinctive feature of this volume is that the methods are applicable to nonredundant mechanisms of general architecture, defined by planar or spatial kinematic chains interconnected in an arbitrary way. Moreover, singularities are interpreted as silhouettes of the configuration space when seen from the input or output spaces. This leads to a powerful image that explains the consequences of traversing singular configurations, and all the rich information that can be extracted from them. The problems are solved by means of effective branch-and-prune and numerical continuation methods that are of independent interest in themselves...

Disordered and Multiple Destinations Path Planning Methods for Mobile Robot in Dynamic Environment

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Yong-feng Dong

2016-01-01

Full Text Available In the smart home environment, aiming at the disordered and multiple destinations path planning, the sequencing rule is proposed to determine the order of destinations. Within each branching process, the initial feasible path set is generated according to the law of attractive destination. A sinusoidal adaptive genetic algorithm is adopted. It can calculate the crossover probability and mutation probability adaptively changing with environment at any time. According to the cultural-genetic algorithm, it introduces the concept of reducing turns by parallelogram and reducing length by triangle in the belief space, which can improve the quality of population. And the fallback strategy can help to jump out of the “U” trap effectively. The algorithm analyses the virtual collision in dynamic environment with obstacles. According to the different collision types, different strategies are executed to avoid obstacles. The experimental results show that cultural-genetic algorithm can overcome the problems of premature and convergence of original algorithm effectively. It can avoid getting into the local optimum. And it is more effective for mobile robot path planning. Even in complex environment with static and dynamic obstacles, it can avoid collision safely and plan an optimal path rapidly at the same time.

Optimal Path Planner for Mobile Robot in 2D Environment

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Valeri Kroumov

2004-06-01

Full Text Available The problem of path planning for the case of a mobile robot moving in an environment filled with obstacles with known shapes and positions is studied. A path planner based on the genetic algorithm approach, which generates optimal in length path is proposed. The population member paths are generated by another algorithm, which uses for description of the obstacles an artificial annealing neural network and is based on potential field approach. The resulting path is piecewise linear with changing directions at the corners of the obstacles. Because of this feature, the inverse kinematics problems in controlling differential drive robots are simply solved: to drive the robot to some goal pose (x, y, theta, the robot can be spun in place until it is aimed at (x, y, then driven forward until it is at (x, y, and then spun in place until the required goal orientation

A path planning method for robot end effector motion using the curvature theory of the ruled surfaces

Science.gov (United States)

Güler, Fatma; Kasap, Emin

Using the curvature theory for the ruled surfaces a technique for robot trajectory planning is presented. This technique ensures the calculation of robot’s next path. The positional variation of the Tool Center Point (TCP), linear velocity, angular velocity are required in the work area of the robot. In some circumstances, it may not be physically achievable and a re-computation of the robot trajectory might be necessary. This technique is suitable for re-computation of the robot trajectory. We obtain different robot trajectories which change depending on the darboux angle function and define trajectory ruled surface family with a common trajectory curve with the rotation trihedron. Also, the motion of robot end effector is illustrated with examples.

Path Planning with a Lazy Significant Edge Algorithm (LSEA

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Joseph Polden

2013-04-01

Full Text Available Probabilistic methods have been proven to be effective for robotic path planning in a geometrically complex environment. In this paper, we propose a novel approach, which utilizes a specialized roadmap expansion phase, to improve lazy probabilistic path planning. This expansion phase analyses roadmap connectivity information to bias sampling towards objects in the workspace that have not yet been navigated by the robot. A new method to reduce the number of samples required to navigate narrow passages is also proposed and tested. Experimental results show that the new algorithm is more efficient than the traditional path planning methodologies. It was able to generate solutions for a variety of path planning problems faster, using fewer samples to arrive at a valid solution.

Path Planning Method in Multi-obstacle Marine Environment

Science.gov (United States)

Zhang, Jinpeng; Sun, Hanxv

2017-12-01

In this paper, an improved algorithm for particle swarm optimization is proposed for the application of underwater robot in the complex marine environment. Not only did consider to avoid obstacles when path planning, but also considered the current direction and the size effect on the performance of the robot dynamics. The algorithm uses the trunk binary tree structure to construct the path search space and A * heuristic search method is used in the search space to find a evaluation standard path. Then the particle swarm algorithm to optimize the path by adjusting evaluation function, which makes the underwater robot in the current navigation easier to control, and consume less energy.

Software for Project-Based Learning of Robot Motion Planning

Science.gov (United States)

Moll, Mark; Bordeaux, Janice; Kavraki, Lydia E.

2013-01-01

Motion planning is a core problem in robotics concerned with finding feasible paths for a given robot. Motion planning algorithms perform a search in the high-dimensional continuous space of robot configurations and exemplify many of the core algorithmic concepts of search algorithms and associated data structures. Motion planning algorithms can…

Curvature-Continuous 3D Path-Planning Using QPMI Method

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Seong-Ryong Chang

2015-06-01

Full Text Available It is impossible to achieve vertex movement and rapid velocity control in aerial robots and aerial vehicles because of momentum from the air. A continuous-curvature path ensures such robots and vehicles can fly with stable and continuous movements. General continuous path-planning methods use spline interpolation, for example B-spline and Bézier curves. However, these methods cannot be directly applied to continuous path planning in a 3D space. These methods use a subset of the waypoints to decide curvature and some waypoints are not included in the planned path. This paper proposes a method for constructing a curvature-continuous path in 3D space that includes every waypoint. The movements in each axis, x, y and z, are separated by the parameter u. Waypoint groups are formed, each with its own continuous path derived using quadratic polynomial interpolation. The membership function then combines each continuous path into one continuous path. The continuity of the path is verified and the curvature-continuous path is produced using the proposed method.

Mission-directed path planning for planetary rover exploration

Science.gov (United States)

Tompkins, Paul

2005-07-01

Robotic rovers uniquely benefit planetary exploration---they enable regional exploration with the precision of in-situ measurements, a combination impossible from an orbiting spacecraft or fixed lander. Mission planning for planetary rover exploration currently utilizes sophisticated software for activity planning and scheduling, but simplified path planning and execution approaches tailored for localized operations to individual targets. This approach is insufficient for the investigation of multiple, regionally distributed targets in a single command cycle. Path planning tailored for this task must consider the impact of large scale terrain on power, speed and regional access; the effect of route timing on resource availability; the limitations of finite resource capacity and other operational constraints on vehicle range and timing; and the mutual influence between traverses and upstream and downstream stationary activities. Encapsulating this reasoning in an efficient autonomous planner would allow a rover to continue operating rationally despite significant deviations from an initial plan. This research presents mission-directed path planning that enables an autonomous, strategic reasoning capability for robotic explorers. Planning operates in a space of position, time and energy. Unlike previous hierarchical approaches, it treats these dimensions simultaneously to enable globally-optimal solutions. The approach calls on a near incremental search algorithm designed for planning and re-planning under global constraints, in spaces of higher than two dimensions. Solutions under this method specify routes that avoid terrain obstacles, optimize the collection and use of rechargable energy, satisfy local and global mission constraints, and account for the time and energy of interleaved mission activities. Furthermore, the approach efficiently re-plans in response to updates in vehicle state and world models, and is well suited to online operation aboard a robot

Path Planning and Replanning for Mobile Robot Navigation on 3D Terrain: An Approach Based on Geodesic

Directory of Open Access Journals (Sweden)

Kun-Lin Wu

2016-01-01

Full Text Available In this paper, mobile robot navigation on a 3D terrain with a single obstacle is addressed. The terrain is modelled as a smooth, complete manifold with well-defined tangent planes and the hazardous region is modelled as an enclosing circle with a hazard grade tuned radius representing the obstacle projected onto the terrain to allow efficient path-obstacle intersection checking. To resolve the intersections along the initial geodesic, by resorting to the geodesic ideas from differential geometry on surfaces and manifolds, we present a geodesic-based planning and replanning algorithm as a new method for obstacle avoidance on a 3D terrain without using boundary following on the obstacle surface. The replanning algorithm generates two new paths, each a composition of two geodesics, connected via critical points whose locations are found to be heavily relying on the exploration of the terrain via directional scanning on the tangent plane at the first intersection point of the initial geodesic with the circle. An advantage of this geodesic path replanning procedure is that traversability of terrain on which the detour path traverses could be explored based on the local Gauss-Bonnet Theorem of the geodesic triangle at the planning stage. A simulation demonstrates the practicality of the analytical geodesic replanning procedure for navigating a constant speed point robot on a 3D hill-like terrain.

Side-to-side 3D coverage path planning approach for agricultural robots to minimize skip/overlap areas between swaths

DEFF Research Database (Denmark)

Hameed, Ibrahim; la Cour-Harbo, Anders; Osen, O. L.

2016-01-01

Automated path planning is important for the automation and optimization of field operations. It can provide the waypoints required for guidance, navigation and control of agricultural robots and autonomous tractors throughout the execution of these field operations. In agriculture, field...... operations are usually repeated in the same field and from year to year as well, therefore, it should be carried out in a manner that minimizes environmental impact and cost taking into account the topographic land features. Current 3D terrain field coverage path planning algorithms are simply 2D coverage...

Flexible integration of path-planning capabilities

Science.gov (United States)

Stobie, Iain C.; Tambe, Milind; Rosenbloom, Paul S.

1993-05-01

Robots pursuing complex goals must plan paths according to several criteria of quality, including shortness, safety, speed and planning time. Many sources and kinds of knowledge, such as maps, procedures and perception, may be available or required. Both the quality criteria and sources of knowledge may vary widely over time, and in general they will interact. One approach to address this problem is to express all criteria and goals numerically in a single weighted graph, and then to search this graph to determine a path. Since this is problematic with symbolic or uncertain data and interacting criteria, we propose that what is needed instead is an integration of many kinds of planning capabilities. We describe a hybrid approach to integration, based on experiments with building simulated mobile robots using Soar, an integrated problem-solving and learning system. For flexibility, we have implemented a combination of internal planning, reactive capabilities and specialized tools. We illustrate how these components can complement each other's limitations and produce plans which integrate geometric and task knowledge.

Rough terrain motion planning for actively reconfigurable mobile robots

International Nuclear Information System (INIS)

Brunner, Michael

2015-01-01

In the aftermath of the Tohoku earthquake and the nuclear meltdown at the power plant of Fukushima Daiichi in 2011, reconfigurable robots like the iRobot Packbot were deployed. Instead of humans, the robots were used to investigate contaminated areas. Other incidents are the two major earthquakes in Northern Italy in May 2012. Besides many casualties, a large number of historical buildings was severely damaged. Due to the imminent danger of collapse, it was too dangerous for rescue personnel to enter many of the buildings. Therefore, the sites were inspected by reconfigurable robots, which are able to traverse the rubble and debris of the partially destroyed buildings. This thesis develops a navigation system enabling wheeled and tracked robots to safely traverse rough terrain and challenging structures. It consists of a planning mechanism and a controller. The focus of this thesis, however, is on the contribution to motion planning. The planning scheme employs a hierarchical approach to motion planning for actively reconfigurable robots in rough environments. Using a map of the environment the algorithm estimates the traversability under the consideration of uncertainties. Based on this analysis, an initial path search determines an approximate solution with respect to the robot's operating limits.Subsequently, a detailed planning step refines the initial path where it is required. The refinement step considers the robot's actuators and stability in addition to the quantities of the first search. Determining the robot-terrain interaction is very important in rough terrain. This thesis presents two path refinement approaches: a deterministic and a randomized approach. The experimental evaluation investigates the separate components of the planning scheme, the robot-terrain interaction for instance.In simulation as well as in real world experiments the evaluation demonstrates the necessity of such a planning algorithm in rough terrain and it provides

Rough terrain motion planning for actively reconfigurable mobile robots

Energy Technology Data Exchange (ETDEWEB)

Brunner, Michael

2015-02-05

In the aftermath of the Tohoku earthquake and the nuclear meltdown at the power plant of Fukushima Daiichi in 2011, reconfigurable robots like the iRobot Packbot were deployed. Instead of humans, the robots were used to investigate contaminated areas. Other incidents are the two major earthquakes in Northern Italy in May 2012. Besides many casualties, a large number of historical buildings was severely damaged. Due to the imminent danger of collapse, it was too dangerous for rescue personnel to enter many of the buildings. Therefore, the sites were inspected by reconfigurable robots, which are able to traverse the rubble and debris of the partially destroyed buildings. This thesis develops a navigation system enabling wheeled and tracked robots to safely traverse rough terrain and challenging structures. It consists of a planning mechanism and a controller. The focus of this thesis, however, is on the contribution to motion planning. The planning scheme employs a hierarchical approach to motion planning for actively reconfigurable robots in rough environments. Using a map of the environment the algorithm estimates the traversability under the consideration of uncertainties. Based on this analysis, an initial path search determines an approximate solution with respect to the robot's operating limits.Subsequently, a detailed planning step refines the initial path where it is required. The refinement step considers the robot's actuators and stability in addition to the quantities of the first search. Determining the robot-terrain interaction is very important in rough terrain. This thesis presents two path refinement approaches: a deterministic and a randomized approach. The experimental evaluation investigates the separate components of the planning scheme, the robot-terrain interaction for instance.In simulation as well as in real world experiments the evaluation demonstrates the necessity of such a planning algorithm in rough terrain and it provides

A New Method of Global Path Planning for AGV

Institute of Scientific and Technical Information of China (English)

SHI En-xiu; HUANG Yu-mei

2006-01-01

Path planning is important in the research of a mobile robot (MR). Methods for it have been used in different applications. An automated guided vehicle(AGV), which is a kind of MR, is used in a flexible manufacturing system(FMS). Path planning for it is essential to improve the efficiency of FMS. A new method was proposed with known obstacle space FMS in this paper. FMS is described by the Augmented Pos Matrix of a Machine (APMM) and Relative Pos Matrix of Machines (RPMM), which is smaller. The optimum path can be obtained according to the probability of the path and the maximal probability path. The suggested algorithm of path planning was good performance through simulation result: simplicity, saving time and reliability.

Planning paths through a spatial hierarchy - Eliminating stair-stepping effects

Science.gov (United States)

Slack, Marc G.

1989-01-01

Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to operate incrementally, thereby accounting for unexpected events in the operating space.

Design and performance analysis of global path planning techniques for autonomous mobile robots in grid environments

Directory of Open Access Journals (Sweden)

Imen Chaari

2017-03-01

Full Text Available This article presents the results of the 2-year iroboapp research project that aims at devising path planning algorithms for large grid maps with much faster execution times while tolerating very small slacks with respect to the optimal path. We investigated both exact and heuristic methods. We contributed with the design, analysis, evaluation, implementation and experimentation of several algorithms for grid map path planning for both exact and heuristic methods. We also designed an innovative algorithm called relaxed A-star that has linear complexity with relaxed constraints, which provides near-optimal solutions with an extremely reduced execution time as compared to A-star. We evaluated the performance of the different algorithms and concluded that relaxed A-star is the best path planner as it provides a good trade-off among all the metrics, but we noticed that heuristic methods have good features that can be exploited to improve the solution of the relaxed exact method. This led us to design new hybrid algorithms that combine our relaxed A-star with heuristic methods which improve the solution quality of relaxed A-star at the cost of slightly higher execution time, while remaining much faster than A* for large-scale problems. Finally, we demonstrate how to integrate the relaxed A-star algorithm in the robot operating system as a global path planner and show that it outperforms its default path planner with an execution time 38% faster on average.

Radial polar histogram: obstacle avoidance and path planning for robotic cognition and motion control

Science.gov (United States)

Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig

2012-01-01

In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's Intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.

Motion Planning in Multi-robot Systems using Timed Automata

DEFF Research Database (Denmark)

Andersen, Michael. S.; Jensen, Rune S.; Bak, Thomas

This paper dscribes how interacting timed automata can be used to model, analyze, and verify motion planning problems for systems with multiple mobile robots. The method assumes an infra-structure of simple unicycle type robots, moving om a planar grid. The motion of the robots, including simple...... kinematics, is captured in an automata formalism that allows formal composition and symbolic reasoning. The verification software UppAal is used to verify specification requirements formulated in computational tree logic (CTL), generating all feasible trajectories that satisfy specifications. The results...... of the planning are demonstrateted in a testbed that allows execution of the planned paths and motion primitives by synchronizing the planning results from UppAal with actual robotic vehicles. The planning problem may be modified online by moving obstacles in the physical environment, which causes a re...

Path Planning Methods in an Environment with Obstacles (A Review

Directory of Open Access Journals (Sweden)

W. Liu

2018-01-01

Full Text Available Planning the path is the most important task in the mobile robot navigation. This task involves basically three aspects. First, the planned path must run from a given starting point to a given endpoint. Secondly, it should ensure robot’s collision-free movement. Thirdly, among all the possible paths that meet the first two requirements it must be, in a certain sense, optimal.Methods of path planning can be classified according to different characteristics. In the context of using intelligent technologies, they can be divided into traditional methods and heuristic ones. By the nature of the environment, it is possible to divide planning methods into planning methods in a static environment and in a dynamic one (it should be noted, however, that a static environment is rare. Methods can also be divided according to the completeness of information about the environment, namely methods with complete information (in this case the issue is a global path planning and methods with incomplete information (usually, this refers to the situational awareness in the immediate vicinity of the robot, in this case it is a local path planning. Note that incomplete information about the environment can be a consequence of the changing environment, i.e. in a dynamic environment, there is, usually, a local path planning.Literature offers a great deal of methods for path planning where various heuristic techniques are used, which, as a rule, result from the denotative meaning of the problem being solved. This review discusses the main approaches to the problem solution. Here we can distinguish five classes of basic methods: graph-based methods, methods based on cell decomposition, use of potential fields, optimization methods, фтв methods based on intelligent technologies.Many methods of path planning, as a result, give a chain of reference points (waypoints connecting the beginning and end of the path. This should be seen as an intermediate result. The problem

Artificial pheromone for path selection by a foraging swarm of robots.

Science.gov (United States)

Campo, Alexandre; Gutiérrez, Alvaro; Nouyan, Shervin; Pinciroli, Carlo; Longchamp, Valentin; Garnier, Simon; Dorigo, Marco

2010-11-01

Foraging robots involved in a search and retrieval task may create paths to navigate faster in their environment. In this context, a swarm of robots that has found several resources and created different paths may benefit strongly from path selection. Path selection enhances the foraging behavior by allowing the swarm to focus on the most profitable resource with the possibility for unused robots to stop participating in the path maintenance and to switch to another task. In order to achieve path selection, we implement virtual ants that lay artificial pheromone inside a network of robots. Virtual ants are local messages transmitted by robots; they travel along chains of robots and deposit artificial pheromone on the robots that are literally forming the chain and indicating the path. The concentration of artificial pheromone on the robots allows them to decide whether they are part of a selected path. We parameterize the mechanism with a mathematical model and provide an experimental validation using a swarm of 20 real robots. We show that our mechanism favors the selection of the closest resource is able to select a new path if a selected resource becomes unavailable and selects a newly detected and better resource when possible. As robots use very simple messages and behaviors, the system would be particularly well suited for swarms of microrobots with minimal abilities.

Software for project-based learning of robot motion planning

Science.gov (United States)

Moll, Mark; Bordeaux, Janice; Kavraki, Lydia E.

2013-12-01

Motion planning is a core problem in robotics concerned with finding feasible paths for a given robot. Motion planning algorithms perform a search in the high-dimensional continuous space of robot configurations and exemplify many of the core algorithmic concepts of search algorithms and associated data structures. Motion planning algorithms can be explained in a simplified two-dimensional setting, but this masks many of the subtleties and complexities of the underlying problem. We have developed software for project-based learning of motion planning that enables deep learning. The projects that we have developed allow advanced undergraduate students and graduate students to reflect on the performance of existing textbook algorithms and their own variations on such algorithms. Formative assessment has been conducted at three institutions. The core of the software used for this teaching module is also used within the Robot Operating System, a widely adopted platform by the robotics research community. This allows for transfer of knowledge and skills to robotics research projects involving a large variety robot hardware platforms.

Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm

Science.gov (United States)

Iswanto, Wahyunggoro, Oyas; Cahyadi, Adha Imam

2017-04-01

The paper aims to present a design algorithm for multi quadrotor lanes in order to move towards the goal quickly and avoid obstacles in an area with obstacles. There are several problems in path planning including how to get to the goal position quickly and avoid static and dynamic obstacles. To overcome the problem, therefore, the paper presents fuzzy logic algorithm and fuzzy cell decomposition algorithm. Fuzzy logic algorithm is one of the artificial intelligence algorithms which can be applied to robot path planning that is able to detect static and dynamic obstacles. Cell decomposition algorithm is an algorithm of graph theory used to make a robot path map. By using the two algorithms the robot is able to get to the goal position and avoid obstacles but it takes a considerable time because they are able to find the shortest path. Therefore, this paper describes a modification of the algorithms by adding a potential field algorithm used to provide weight values on the map applied for each quadrotor by using decentralized controlled, so that the quadrotor is able to move to the goal position quickly by finding the shortest path. The simulations conducted have shown that multi-quadrotor can avoid various obstacles and find the shortest path by using the proposed algorithms.

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning.

Science.gov (United States)

Trinh, Lan Anh; Ekström, Mikael; Cürüklü, Baran

2018-01-01

Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta * algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta * algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning

Directory of Open Access Journals (Sweden)

Lan Anh Trinh

2018-06-01

Full Text Available Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta* algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta* algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The

Pure-Pursuit Reactive Path Tracking for Nonholonomic Mobile Robots with a 2D Laser Scanner

Directory of Open Access Journals (Sweden)

Jesús Morales

2009-01-01

Full Text Available Due to its simplicity and efficiency, the pure-pursuit path tracking method has been widely employed for planned navigation of nonholonomic ground vehicles. In this paper, we investigate the application of this technique for reactive tracking of paths that are implicitly defined by perceived environmental features. Goal points are obtained through an efficient interpretation of range data from an onboard 2D laser scanner to follow persons, corridors, and walls. Moreover, this formulation allows that a robotic mission can be composed of a combination of different types of path segments. These techniques have been successfully tested in the tracked mobile robot Auriga-α in an indoor environment.

MPC-Based Path Following Control of an Omnidirectional Mobile Robot with Consideration of Robot Constraints

Directory of Open Access Journals (Sweden)

Kiattisin Kanjanawanishkul

2015-01-01

Full Text Available In this paper, the path following problem of an omnidirectional mobile robot (OMR has been studied. Unlike nonholonomic mobile robots, translational and rotational movements of OMRs can be controlled simultaneously and independently. However the constraints of translational and rotational velocities are coupled through the OMR's orientation angle. Therefore, a combination of a virtual-vehicle concept and a model predictive control (MPC strategy is proposed in this work to handle both robot constraints and the path following problem. Our proposed control scheme allows the OMR to follow the reference path successfully and safely, as illustrated in simulation experiments. The forward velocity is close to the desired one and the desired orientation angle is achieved at a given point on the path, while the robot's wheel velocities are maintained within boundaries.

Integrated assignment and path planning

Science.gov (United States)

Murphey, Robert A.

2005-11-01

A surge of interest in unmanned systems has exposed many new and challenging research problems across many fields of engineering and mathematics. These systems have the potential of transforming our society by replacing dangerous and dirty jobs with networks of moving machines. This vision is fundamentally separate from the modern view of robotics in that sophisticated behavior is realizable not by increasing individual vehicle complexity, but instead through collaborative teaming that relies on collective perception, abstraction, decision making, and manipulation. Obvious examples where collective robotics will make an impact include planetary exploration, space structure assembly, remote and undersea mining, hazardous material handling and clean-up, and search and rescue. Nonetheless, the phenomenon driving this technology trend is the increasing reliance of the US military on unmanned vehicles, specifically, aircraft. Only a few years ago, following years of resistance to the use of unmanned systems, the military and civilian leadership in the United States reversed itself and have recently demonstrated surprisingly broad acceptance of increasingly pervasive use of unmanned platforms in defense surveillance, and even attack. However, as rapidly as unmanned systems have gained acceptance, the defense research community has discovered the technical pitfalls that lie ahead, especially for operating collective groups of unmanned platforms. A great deal of talent and energy has been devoted to solving these technical problems, which tend to fall into two categories: resource allocation of vehicles to objectives, and path planning of vehicle trajectories. An extensive amount of research has been conducted in each direction, yet, surprisingly, very little work has considered the integrated problem of assignment and path planning. This dissertation presents a framework for studying integrated assignment and path planning and then moves on to suggest an exact

Transition Analysis and Its Application to Global Path Determination for a Biped Climbing Robot

Directory of Open Access Journals (Sweden)

Haifei Zhu

2018-01-01

Full Text Available Biped climbing robots are considered good assistants and (or substitutes for human workers carrying out high-rise truss-associated routine tasks. Flexible locomotion on three-dimensional complex trusses is a fundamental skill for these robots. In particular, the capability to transit from one structural member to another is paramount for switching objects to be climbed upon. In this paper, we study member-to-member transition and its utility in global path searching for biped climbing robots. To compute operational regions for transition, hierarchical inspection of safety, reachability, and accessibility of grips is taken into account. A novel global path rapid determination approach is subsequently proposed based on the transition analysis. This scheme is efficient for finding feasible routes with respect to the overall structural environment, which also benefits the subsequent grip and motion planning. Simulations are conducted with Climbot, our self-developed biped climbing robot, to verify the efficiency of the presented method. Results show that our proposed method is able to accurately determine the operational region for transition within tens of milliseconds and can obtain global paths within seconds in general.

Trajectory Planning with Pose Feedback for a Dual-Arm Space Robot

Directory of Open Access Journals (Sweden)

Yicheng Liu

2016-01-01

Full Text Available In order to obtain high precision path tracking for a dual-arm space robot, a trajectory planning method with pose feedback is proposed to be introduced into the design process in this paper. Firstly, pose error kinematic models are derived from the related kinematics and desired pose command for the end-effector and the base, respectively. On this basis, trajectory planning with pose feedback is proposed from a control perspective. Theoretical analyses show that the proposed trajectory planning algorithm can guarantee that pose error converges to zero exponentially for both the end-effector and the base when the robot is out of singular configuration. Compared with the existing algorithms, the proposed algorithm can lead to higher precision path tracking for the end-effector. Furthermore, the algorithm renders the system good anti-interference property for the base. Simulation results demonstrate the effectiveness of the proposed trajectory planning algorithm.

Using a virtual world for robot planning

Science.gov (United States)

Benjamin, D. Paul; Monaco, John V.; Lin, Yixia; Funk, Christopher; Lyons, Damian

2012-06-01

We are building a robot cognitive architecture that constructs a real-time virtual copy of itself and its environment, including people, and uses the model to process perceptual information and to plan its movements. This paper describes the structure of this architecture. The software components of this architecture include PhysX for the virtual world, OpenCV and the Point Cloud Library for visual processing, and the Soar cognitive architecture that controls the perceptual processing and task planning. The RS (Robot Schemas) language is implemented in Soar, providing the ability to reason about concurrency and time. This Soar/RS component controls visual processing, deciding which objects and dynamics to render into PhysX, and the degree of detail required for the task. As the robot runs, its virtual model diverges from physical reality, and errors grow. The Match-Mediated Difference component monitors these errors by comparing the visual data with corresponding data from virtual cameras, and notifies Soar/RS of significant differences, e.g. a new object that appears, or an object that changes direction unexpectedly. Soar/RS can then run PhysX much faster than real-time and search among possible future world paths to plan the robot's actions. We report experimental results in indoor environments.

Robot vision for nuclear advanced robot

International Nuclear Information System (INIS)

Nakayama, Ryoichi; Okano, Hideharu; Kuno, Yoshinori; Miyazawa, Tatsuo; Shimada, Hideo; Okada, Satoshi; Kawamura, Astuo

1991-01-01

This paper describes Robot Vision and Operation System for Nuclear Advanced Robot. This Robot Vision consists of robot position detection, obstacle detection and object recognition. With these vision techniques, a mobile robot can make a path and move autonomously along the planned path. The authors implemented the above robot vision system on the 'Advanced Robot for Nuclear Power Plant' and tested in an environment mocked up as nuclear power plant facilities. Since the operation system for this robot consists of operator's console and a large stereo monitor, this system can be easily operated by one person. Experimental tests were made using the Advanced Robot (nuclear robot). Results indicate that the proposed operation system is very useful, and can be operate by only person. (author)

Concurrent Path Planning with One or More Humanoid Robots

Science.gov (United States)

Sanders, Adam M. (Inventor); Reiland, Matthew J. (Inventor)

2014-01-01

A robotic system includes a controller and one or more robots each having a plurality of robotic joints. Each of the robotic joints is independently controllable to thereby execute a cooperative work task having at least one task execution fork, leading to multiple independent subtasks. The controller coordinates motion of the robot(s) during execution of the cooperative work task. The controller groups the robotic joints into task-specific robotic subsystems, and synchronizes motion of different subsystems during execution of the various subtasks of the cooperative work task. A method for executing the cooperative work task using the robotic system includes automatically grouping the robotic joints into task-specific subsystems, and assigning subtasks of the cooperative work task to the subsystems upon reaching a task execution fork. The method further includes coordinating execution of the subtasks after reaching the task execution fork.

A study on an autonomous pipeline maintenance robot, 8

International Nuclear Information System (INIS)

Fukuda, Toshio; Hosokai, Hidemi; Niitsu, Shunichi; Kaneshige, Masanori; Iwasaki, Shinnosuke.

1990-01-01

This paper deals with the path planning and sensing planning expert system with learning functions for the pipeline inspection and maintenance robot, Mark IV. The robot can carry out inspection tasks to autonomously detect malfunctions in a plant pipeline system. Furthermore, the robot becomes more intelligent by adding the following functions: (1) the robot, Mark IV, is capable of inspecting surfaces of storage tanks as well as pipeline outer surfaces; (2) in path planning, the robot has a learning function using information generated in the past such as a moving path, task level and control commands of the robot; (3) in inspecting a pipeline system with plant equipment such as valves, franges, T- and L-joints, the robot is capable of inspecting continuous surfaces in pipeline. Thus, together with the improved path planning expert system (PPES) and the sensing planning expert system (SPES), the Mark IV robot becomes intelligent enough to automatically carry out given inspection tasks. (author)

Automatic Operation For A Robot Lawn Mower

Science.gov (United States)

Huang, Y. Y.; Cao, Z. L.; Oh, S. J.; Kattan, E. U.; Hall, E. L.

1987-02-01

A domestic mobile robot, lawn mower, which performs the automatic operation mode, has been built up in the Center of Robotics Research, University of Cincinnati. The robot lawn mower automatically completes its work with the region filling operation, a new kind of path planning for mobile robots. Some strategies for region filling of path planning have been developed for a partly-known or a unknown environment. Also, an advanced omnidirectional navigation system and a multisensor-based control system are used in the automatic operation. Research on the robot lawn mower, especially on the region filling of path planning, is significant in industrial and agricultural applications.

Vehicle path-planning in three dimensions using optics analogs for optimizing visibility and energy cost

Science.gov (United States)

Rowe, Neil C.; Lewis, David H.

1989-01-01

Path planning is an important issue for space robotics. Finding safe and energy-efficient paths in the presence of obstacles and other constraints can be complex although important. High-level (large-scale) path planning for robotic vehicles was investigated in three-dimensional space with obstacles, accounting for: (1) energy costs proportional to path length; (2) turn costs where paths change trajectory abruptly; and (3) safety costs for the danger associated with traversing a particular path due to visibility or invisibility from a fixed set of observers. Paths optimal with respect to these cost factors are found. Autonomous or semi-autonomous vehicles were considered operating either in a space environment around satellites and space platforms, or aircraft, spacecraft, or smart missiles operating just above lunar and planetary surfaces. One class of applications concerns minimizing detection, as for example determining the best way to make complex modifications to a satellite without being observed by hostile sensors; another example is verifying there are no paths (holes) through a space defense system. Another class of applications concerns maximizing detection, as finding a good trajectory between mountain ranges of a planet while staying reasonably close to the surface, or finding paths for a flight between two locations that maximize the average number of triangulation points available at any time along the path.

A Novel Passive Path Following Controller for a Rehabilitation Robot

National Research Council Canada - National Science Library

Zhang, X; Behal, A; Dawson, D. M; Chen, J

2004-01-01

.... Motivated by a nonholonomic kinematic constraint, a dynamic path generator is designed to trace a desired contour in the robot's workspace when an interaction force is applied at the robot's end-effector...

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.

Cooperative Path-Planning for Multi-Vehicle Systems

Directory of Open Access Journals (Sweden)

Qichen Wang

2014-11-01

Full Text Available In this paper, we propose a collision avoidance algorithm for multi-vehicle systems, which is a common problem in many areas, including navigation and robotics. In dynamic environments, vehicles may become involved in potential collisions with each other, particularly when the vehicle density is high and the direction of travel is unrestricted. Cooperatively planning vehicle movement can effectively reduce and fairly distribute the detour inconvenience before subsequently returning vehicles to their intended paths. We present a novel method of cooperative path planning for multi-vehicle systems based on reinforcement learning to address this problem as a decision process. A dynamic system is described as a multi-dimensional space formed by vectors as states to represent all participating vehicles’ position and orientation, whilst considering the kinematic constraints of the vehicles. Actions are defined for the system to transit from one state to another. In order to select appropriate actions whilst satisfying the constraints of path smoothness, constant speed and complying with a minimum distance between vehicles, an approximate value function is iteratively developed to indicate the desirability of every state-action pair from the continuous state space and action space. The proposed scheme comprises two phases. The convergence of the value function takes place in the former learning phase, and it is then used as a path planning guideline in the subsequent action phase. This paper summarizes the concept and methodologies used to implement this online cooperative collision avoidance algorithm and presents results and analysis regarding how this cooperative scheme improves upon two baseline schemes where vehicles make movement decisions independently.

Continuous path control of a 5-DOF parallel-serial hybrid robot

International Nuclear Information System (INIS)

Uchiyama, Takuma; Terada, Hidetsugu; Mitsuya, Hironori

2010-01-01

Using the 5-degree of freedom parallel-serial hybrid robot, to realize the de-burring, new forward and inverse kinematic calculation methods based on the 'off-line teaching' method are proposed. This hybrid robot consists of a parallel stage section and a serial stage section. Considering this point, each section is calculated individually. And the continuous path control algorithm of this hybrid robot is proposed. To verify the usefulness, a prototype robot is tested which is controlled based on the proposed methods. This verification includes a positioning test and a pose test. The positioning test evaluates the continuous path of the tool center point. The pose test evaluates the pose on the tool center point. As the result, it is confirmed that this hybrid robot moves correctly using the proposed methods

Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

Energy Technology Data Exchange (ETDEWEB)

Tuvshinjargal, Doopalam; Lee, Deok Jin [Kunsan National University, Gunsan (Korea, Republic of)

2015-06-15

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

Efficient Kinect Sensor-Based Reactive Path Planning Method for Autonomous Mobile Robots in Dynamic Environments

International Nuclear Information System (INIS)

Tuvshinjargal, Doopalam; Lee, Deok Jin

2015-01-01

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments

Intelligent robot action planning

Energy Technology Data Exchange (ETDEWEB)

Vamos, T; Siegler, A

1982-01-01

Action planning methods used in intelligent robot control are discussed. Planning is accomplished through environment understanding, environment representation, task understanding and planning, motion analysis and man-machine communication. These fields are analysed in detail. The frames of an intelligent motion planning system are presented. Graphic simulation of the robot's environment and motion is used to support the planning. 14 references.

Spline-based automatic path generation of welding robot

Institute of Scientific and Technical Information of China (English)

Niu Xuejuan; Li Liangyu

2007-01-01

This paper presents a flexible method for the representation of welded seam based on spline interpolation. In this method, the tool path of welding robot can be generated automatically from a 3D CAD model. This technique has been implemented and demonstrated in the FANUC Arc Welding Robot Workstation. According to the method, a software system is developed using VBA of SolidWorks 2006. It offers an interface between SolidWorks and ROBOGUIDE, the off-line programming software of FANUC robot. It combines the strong modeling function of the former and the simulating function of the latter. It also has the capability of communication with on-line robot. The result data have shown its high accuracy and strong reliability in experiments. This method will improve the intelligence and the flexibility of the welding robot workstation.

Dynamic Arc Fitting Path Follower for Skid-Steered Mobile Robots

Directory of Open Access Journals (Sweden)

Peter Lepej

2015-10-01

Full Text Available Many applications, such as surveillance, inspection or search and rescue operations, can be performed with autonomous robots. Our aim is a control of modular autonomous systems in rescue robotics. One of the basic problems with autonomous robotics is the execution part where the control commands (translation and rotational velocities are produced for mobile bases. Therefore we have focused on this area because there is only a small amount of available path following software for skid-steered mobile robots. Our goal was to develop a velocity controller that could be used for multiple skid-steered mobile bases. We considered differential drive mobile bases such as tracked skid-steering mobile bases. Our approach is based on an arc fitting algorithm, which takes into account the robot constraints and kinematical model. It produces a continuous trajectory where fitting to the given path is adapted based on given parameters. Moreover, we have included orientation angle compensation while the mobile robot is moving and ground inclination compensation. Our rescue robot is described, together with the simulation setup and algorithm implementation. We compared our algorithm to the Hector-based software and curvature velocity approach. The results for the proposed algorithm are shown for the simulation results and the experiment.

Strategy for robot motion and path planning in robot taping

Science.gov (United States)

Yuan, Qilong; Chen, I.-Ming; Lembono, Teguh Santoso; Landén, Simon Nelson; Malmgren, Victor

2016-06-01

Covering objects with masking tapes is a common process for surface protection in processes like spray painting, plasma spraying, shot peening, etc. Manual taping is tedious and takes a lot of effort of the workers. The taping process is a special process which requires correct surface covering strategy and proper attachment of the masking tape for an efficient surface protection. We have introduced an automatic robot taping system consisting of a robot manipulator, a rotating platform, a 3D scanner and specially designed taping end-effectors. This paper mainly talks about the surface covering strategies for different classes of geometries. The methods and corresponding taping tools are introduced for taping of following classes of surfaces: Cylindrical/extended surfaces, freeform surfaces with no grooves, surfaces with grooves, and rotational symmetrical surfaces. A collision avoidance algorithm is introduced for the robot taping manipulation. With further improvements on segmenting surfaces of taping parts and tape cutting mechanisms, such taping solution with the taping tool and the taping methodology can be combined as a very useful and practical taping package to assist humans in this tedious and time costly work.

A study on an autonomous pipeline maintenance robot, 5

International Nuclear Information System (INIS)

Fukuda, Toshio; Hosokai, Hidemi; Otsuka, Masashi.

1989-01-01

The path planning is very important for the pipeline maintenance robot because there are many obstacles on pipeline such as flanges and T-joints and others, and because pipelines are constructed as a connected network in a very complicated way. Furthermore the maintenance robot Mark III previously reported has the ability to transit from one pipe to another the path planner should consider. The expert system especially aimed for path planning, named PPES (Path Planning Expert System), is described in this paper. A human-operator has only to give some tasks to this system. This system automatically replies with the optimal path, which is based on the calculation of the task levels and list of some control commands. Task level is a criterion to determine one optimal path. It consists of the difference of potential energies, the static joint torques, velocity of the robot, step numbers of the grippers' or body's movement, which the robot requires. This system also has graphic illustrations, so that the operator can easily check and understand the plant map and the result of the path planning. (author)

Path following mobile robot in the presence of velocity constraints

DEFF Research Database (Denmark)

Bak, Martin; Poulsen, Niels Kjølstad; Ravn, Ole

2001-01-01

This paper focuses on path following algorithms for mobile robots with velocity constraints on the wheels. The path considered consists of straight lines intersected with given angles. We present a fast real-time receding horizon controller which anticipates the intersections and smoothly control...

Planning strategies for the Ambler walking robot

Science.gov (United States)

Wettergreen, David; Thomas, Hans; Thorpe, Chuck

1990-01-01

A hierarchy of planning strategies is proposed and explained for a walking robot called the Ambler. The hierarchy decomposes planning into levels of trajectory, gait, and footfall. An abstraction of feasible traversability allows the Ambler's trajectory planner to identify acceptable trajectories by finding paths that guarantee footfalls without specifying exactly which footfalls. Leg and body moves that achieve this trajectory can be generated by the Ambler's gait planner, which incorporates pattern constraints and measures of utility to search for the best next move. By combining constraints from the quality and details of the terrain, the Ambler's footfall planner can select footfalls that insure stability and remain within the tolerances of the gait.

Path planning in changeable environments

NARCIS (Netherlands)

Nieuwenhuisen, D.

2007-01-01

This thesis addresses path planning in changeable environments. In contrast to traditional path planning that deals with static environments, in changeable environments objects are allowed to change their configurations over time. In many cases, path planning algorithms must facilitate quick

Neural Networks in Mobile Robot Motion

Directory of Open Access Journals (Sweden)

Danica Janglová

2004-03-01

Full Text Available This paper deals with a path planning and intelligent control of an autonomous robot which should move safely in partially structured environment. This environment may involve any number of obstacles of arbitrary shape and size; some of them are allowed to move. We describe our approach to solving the motion-planning problem in mobile robot control using neural networks-based technique. Our method of the construction of a collision-free path for moving robot among obstacles is based on two neural networks. The first neural network is used to determine the “free” space using ultrasound range finder data. The second neural network “finds” a safe direction for the next robot section of the path in the workspace while avoiding the nearest obstacles. Simulation examples of generated path with proposed techniques will be presented.

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

Science.gov (United States)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

Intelligent coverage path planning for agricultural robots and autonomous machines on three-dimensional terrain

DEFF Research Database (Denmark)

Hameed, Ibahim

2014-01-01

Field operations should be done in a manner that minimizes time and travels over the field surface. Automated and intelligent path planning can help to find the best coverage path so that costs of various field operations can be minimized. The algorithms for generating an optimized field coverage...

Trajectory Planning of Mobile robot in Unstructured Environment for Multiple Objects

Directory of Open Access Journals (Sweden)

Muhammad Arshad

2012-01-01

Full Text Available In this paper we have presented a novel technique for the navigation and path formulation of wheeled mobile robot. In a given environment having obstacles, a path is generated from the given initial and final position of the robot. Based on the global knowledge of the environment a global path is formulated initially. This global path considers all the known obstacles in the environment and must avoid collision with these obstacles, i.e. the formulated path must be safe (collision free. For global path formulation strategic schemes have been employed using the a priori knowledge of the environment. The global path is fed to the robot. When unknown obstacles come in the path of the robot, it must deviate from the given global path and should generate a local path to avoid collision with the new unknown obstacle. By using sensors data the reactive schemes have been implemented for local path formulation. For local path formulation the path has been subdivided into intermediate steps known as sub goals. In the existing approaches known and unknown objects are considered separately. But in some of the practical applications known and unknown objects need to be considered simultaneously. This paper considers the problem of robot motion formulation in an environment having already known obstacles and unknown new moving objects. A Novel algorithm has been developed which incorporates local path planner, optimization and navigation modules. As unknown objects can appear in the environment randomly therefore uncertainty in the environment has been considered.

视觉移动机器人的模糊智能路径规划%Intelligent Path Planning of Vision- Based Mobile Robot with Fuzzy Approach

Institute of Scientific and Technical Information of China (English)

张一巍; 黄源清

2002-01-01

The path planning problem for intelligent mobile robots inwbves two main problems: the represent of task emionment including obstacles and the development of a strategy to determine a collision - free route. In this paper, new approaches have been developed to solve these problems .The first problem was solve using the fuzzy system approach, which represent obstacles with a circle. The other problem was overcome throughthe use of a strategy selector, which chooses the best stategy between velocity control strategy and direction control strategy.

Neurosurgical robotic arm drilling navigation system.

Science.gov (United States)

Lin, Chung-Chih; Lin, Hsin-Cheng; Lee, Wen-Yo; Lee, Shih-Tseng; Wu, Chieh-Tsai

2017-09-01

The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process. The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled-through. Three kinds of experiment were designed. The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto-stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non-drilled-through cases (8.42% and 4.21% in control groups 1 and 2). The system may be useful for neurosurgical robotic arm drilling navigation. Copyright © 2016 John Wiley & Sons, Ltd.

An Architecture for Robot Assemblt Task Planning

DEFF Research Database (Denmark)

Sun, Hongyan

1999-01-01

This paper discusses an integrated robot assembly task planning system architecture. In such an integrated system, the robot motion commands produced from the planning system can be validated before done-loading for actual execution.......This paper discusses an integrated robot assembly task planning system architecture. In such an integrated system, the robot motion commands produced from the planning system can be validated before done-loading for actual execution....

TP-Space RRT – Kinematic Path Planning of Non-Holonomic Any-Shape Vehicles

Directory of Open Access Journals (Sweden)

Jose Luis Blanco

2015-05-01

Full Text Available The autonomous navigation of vehicles typically combines two kinds of methods: a path is first planned, and then the robot is driven by a local obstacle-avoidance controller. The present work, which focuses on path planning, proposes an extension to the well-known rapidly-exploring random tree (RRT algorithm to allow its integration with a trajectory parameter-space (TP-space as an efficient method to detect collision-free, kinematically-feasible paths for arbitrarily-shaped vehicles. In contrast to original RRT, this proposal generates navigation trees, with poses as nodes, whose edges are all kinematically-feasible paths, suitable to being accurately followed by vehicles driven by pure reactive algorithms. Initial experiments demonstrate the suitability of the method with an Ackermann-steering vehicle model whose severe kinematic constraints cannot be obviated. An important result that sets this work apart from previous research is the finding that employing several families of potential trajectories to expand the tree, which can be done efficiently under the TP-space formalism, improves the optimality of the planned trajectories. A reference C++ implementation has been released as open-source.

Solving the empty space problem in robot path planning by mathematical morphology

NARCIS (Netherlands)

Roerdink, J.B.T.M.

1993-01-01

In this paper we formulate a morphological approach to path planning problems, in particular with respect to the empty­-space problem, that is, the question of finding the allowed states for an object, moving in a space with obstacles. Our approach is based upon a recent generalization of

A study on in-pipe inspection mobile robots, 3

International Nuclear Information System (INIS)

Fukuda, Toshio; Hosokai, Hidemi; Uemura, Masahiro.

1990-01-01

This paper deals with inspection path planning for in-pipe inspection mobile robots which have the capability of moving through complicated pipeline networks. It is imperative that the robot systems have an inspection path planning system for such networks for their reasonable and rational operation, controlled by themselves or by the operators. The planning mainly requires two projects: the selection of the place to put the robot in or out, and the generation of the paths in the networks. This system provides the for complicated problems with plural inspection points using a basic strategy of systematically producing patterns and dividing partial problems of simple searches based on rules. (author)

An Improved Path-Generating Regulator for Two-Wheeled Robots to Track the Circle/Arc Passage

Directory of Open Access Journals (Sweden)

Jun Dai

2014-01-01

Full Text Available The improved path-generating regulator (PGR is proposed to path track the circle/arc passage for two-wheeled robots. The PGR, which is a control method for robots so as to orient its heading toward the tangential direction of one of the curves belonging to the family of path functions, is applied to navigation problem originally. Driving environments for robots are usually roads, streets, paths, passages, and ridges. These tracks can be seen as they consist of straight lines and arcs. In the case of small interval, arc can be regarded as straight line approximately; therefore we extended the PGR to drive the robot move along circle/arc passage based on the theory that PGR to track the straight passage. In addition, the adjustable look-ahead method is proposed to improve the robot trajectory convergence property to the target circle/arc. The effectiveness is proved through MATLAB simulations on both the comparisons with the PGR and the improved PGR with adjustable look-ahead method. The results of numerical simulations show that the adjustable look-ahead method has better convergence property and stronger capacity of resisting disturbance.

Path following control of planar snake robots using virtual holonomic constraints: theory and experiments.

Science.gov (United States)

Rezapour, Ehsan; Pettersen, Kristin Y; Liljebäck, Pål; Gravdahl, Jan T; Kelasidi, Eleni

This paper considers path following control of planar snake robots using virtual holonomic constraints. In order to present a model-based path following control design for the snake robot, we first derive the Euler-Lagrange equations of motion of the system. Subsequently, we define geometric relations among the generalized coordinates of the system, using the method of virtual holonomic constraints. These appropriately defined constraints shape the geometry of a constraint manifold for the system, which is a submanifold of the configuration space of the robot. Furthermore, we show that the constraint manifold can be made invariant by a suitable choice of feedback. In particular, we analytically design a smooth feedback control law to exponentially stabilize the constraint manifold. We show that enforcing the appropriately defined virtual holonomic constraints for the configuration variables implies that the robot converges to and follows a desired geometric path. Numerical simulations and experimental results are presented to validate the theoretical approach.

Optimization approaches for robot trajectory planning

Directory of Open Access Journals (Sweden)

Carlos Llopis-Albert

2018-03-01

Full Text Available The development of optimal trajectory planning algorithms for autonomous robots is a key issue in order to efficiently perform the robot tasks. This problem is hampered by the complex environment regarding the kinematics and dynamics of robots with several arms and/or degrees of freedom (dof, the design of collision-free trajectories and the physical limitations of the robots. This paper presents a review about the existing robot motion planning techniques and discusses their pros and cons regarding completeness, optimality, efficiency, accuracy, smoothness, stability, safety and scalability.

Multi-robot caravanning

KAUST Repository

Denny, Jory; Giese, Andrew; Mahadevan, Aditya; Marfaing, Arnaud; Glockenmeier, Rachel; Revia, Colton; Rodriguez, Samuel; Amato, Nancy M.

2013-01-01

of waypoints. At the heart of our algorithm is the use of leader election to efficiently exploit the unique environmental knowledge available to each robot in order to plan paths for the group, which makes it general enough to work with robots that have

Cooperative path planning of unmanned aerial vehicles

CERN Document Server

Tsourdos, Antonios; Shanmugavel, Madhavan

2010-01-01

An invaluable addition to the literature on UAV guidance and cooperative control, Cooperative Path Planning of Unmanned Aerial Vehicles is a dedicated, practical guide to computational path planning for UAVs. One of the key issues facing future development of UAVs is path planning: it is vital that swarm UAVs/ MAVs can cooperate together in a coordinated manner, obeying a pre-planned course but able to react to their environment by communicating and cooperating. An optimized path is necessary in order to ensure a UAV completes its mission efficiently, safely, and successfully. Focussing on the path planning of multiple UAVs for simultaneous arrival on target, Cooperative Path Planning of Unmanned Aerial Vehicles also offers coverage of path planners that are applicable to land, sea, or space-borne vehicles. Cooperative Path Planning of Unmanned Aerial Vehicles is authored by leading researchers from Cranfield University and provides an authoritative resource for researchers, academics and engineers working in...

Implementation of a Mobile Robot Platform Navigating in Dynamic Environment

Directory of Open Access Journals (Sweden)

Belaidi Hadjira

2017-01-01

Full Text Available Currently, problems of autonomous wheeled mobile robots in unknown environments are great challenge. Obstacle avoidance and path planning are the back bone of autonomous control as it makes robot able to reach its destination without collision. Dodging obstacles in dynamic and uncertain environment is the most complex part of obstacle avoidance and path planning tasks. This work deals with the implementation of an easy approach of static and dynamic obstacles avoidance. The robot starts by executing a free optimal path loaded into its controller; then, it uses its sensors to avoid the unexpected obstacles which may occur in that path during navigation.

Cooperative organic mine avoidance path planning

Science.gov (United States)

McCubbin, Christopher B.; Piatko, Christine D.; Peterson, Adam V.; Donnald, Creighton R.; Cohen, David

2005-06-01

The JHU/APL Path Planning team has developed path planning techniques to look for paths that balance the utility and risk associated with different routes through a minefield. Extending on previous years' efforts, we investigated real-world Naval mine avoidance requirements and developed a tactical decision aid (TDA) that satisfies those requirements. APL has developed new mine path planning techniques using graph based and genetic algorithms which quickly produce near-minimum risk paths for complicated fitness functions incorporating risk, path length, ship kinematics, and naval doctrine. The TDA user interface, a Java Swing application that obtains data via Corba interfaces to path planning databases, allows the operator to explore a fusion of historic and in situ mine field data, control the path planner, and display the planning results. To provide a context for the minefield data, the user interface also renders data from the Digital Nautical Chart database, a database created by the National Geospatial-Intelligence Agency containing charts of the world's ports and coastal regions. This TDA has been developed in conjunction with the COMID (Cooperative Organic Mine Defense) system. This paper presents a description of the algorithms, architecture, and application produced.

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.

The Planning of Straight Line Trajectory in Robotics Using Interactive Graphics

Directory of Open Access Journals (Sweden)

Kesheng Wang

1987-07-01

Full Text Available The planning of straight line trajectory using the interactive computer graphics simulation of robot manipulator movement is discussed. This new approach to straight line motion planning improves the 'bound deviation joint paths' developed by R. M. Taylor (1979. The new approach has three characteristics: (1 linear interpolation in joint space; (2 unequal intervals for interpolating knot points; (3 using interactive computer graphics to assure that the maximum deviation in the whole segment is less than the pre-specified values. The structure and mathematical basis of a computer program developed for this purpose are presented.

Strategic Team AI Path Plans: Probabilistic Pathfinding

Directory of Open Access Journals (Sweden)

Tng C. H. John

2008-01-01

Full Text Available This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002, in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006. We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.

Motion planning for multiple robots

NARCIS (Netherlands)

Aronov, B.; Berg, de M.; van der Stappen, A.F.; Svestka, P.; Vleugels, J.M.

1999-01-01

We study the motion-planning problem for pairs and triples of robots operating in a shared workspace containing n obstacles. A standard way to solve such problems is to view the collection of robots as one composite robot, whose number of degrees of freedom is d , the sum of the numbers of degrees

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

Classification of obstacle shape for generating walking path of humanoid robot

International Nuclear Information System (INIS)

Park, Chan Soo; Kim, Do Ik

2013-01-01

To generate the walking path of a humanoid robot in an unknown environment, the shapes of obstacles around the robot should be detected accurately. However, doing so incurs a very large computational cast. Therefore this study proposes a method to classify the obstacle shape into three types: a shape small enough for the robot to go over, a shape planar enough for the robot foot to make contact with, and an uncertain shape that must be avoided by the robot. To classify the obstacle shape, first, the range and the number of the obstacles is detected. If an obstacle can make contact with the robot foot, the shape of an obstacle is accurately derived. If an obstacle has uncertain shape or small size, the shape of an obstacle is not detected to minimize the computational load. Experimental results show that the proposed algorithm efficiently classifies the shapes of obstacles around the robot in real time with low computational load

Classification of obstacle shape for generating walking path of humanoid robot

Energy Technology Data Exchange (ETDEWEB)

Park, Chan Soo; Kim, Do Ik [Korea Institute of Science and Technology, Seoul (Korea, Republic of)

2013-02-15

To generate the walking path of a humanoid robot in an unknown environment, the shapes of obstacles around the robot should be detected accurately. However, doing so incurs a very large computational cast. Therefore this study proposes a method to classify the obstacle shape into three types: a shape small enough for the robot to go over, a shape planar enough for the robot foot to make contact with, and an uncertain shape that must be avoided by the robot. To classify the obstacle shape, first, the range and the number of the obstacles is detected. If an obstacle can make contact with the robot foot, the shape of an obstacle is accurately derived. If an obstacle has uncertain shape or small size, the shape of an obstacle is not detected to minimize the computational load. Experimental results show that the proposed algorithm efficiently classifies the shapes of obstacles around the robot in real time with low computational load.

Walking path-planning method for multiple radiation areas

International Nuclear Information System (INIS)

Liu, Yong-kuo; Li, Meng-kun; Peng, Min-jun; Xie, Chun-li; Yuan, Cheng-qian; Wang, Shuang-yu; Chao, Nan

2016-01-01

Highlights: • Radiation environment modeling method is designed. • Path-evaluating method and segmented path-planning method are proposed. • Path-planning simulation platform for radiation environment is built. • The method avoids to be misled by minimum dose path in single area. - Abstract: Based on minimum dose path-searching method, walking path-planning method for multiple radiation areas was designed to solve minimum dose path problem in single area and find minimum dose path in the whole space in this paper. Path-planning simulation platform was built using C# programming language and DirectX engine. The simulation platform was used in simulations dealing with virtual nuclear facilities. Simulation results indicated that the walking-path planning method is effective in providing safety for people walking in nuclear facilities.

Environmental restoration and waste management: Robotics technology development program: Robotics 5-year program plan

International Nuclear Information System (INIS)

1991-01-01

This plan covers robotics Research, Development, Demonstration, Testing, activities in the Program for the next five years. These activities range from bench-scale R ampersand D to fullscale hot demonstrations at DOE sites. This plan outlines applications of existing technology to near-term needs, the development and application of enhanced technology for longer-term needs, and an initiation of advanced technology development to meet those needs beyond the five-year plan. The objective of the Robotic Technology Development (RTDP) is to develop and apply robotics technologies that will enable Environmental Restoration and Waste Management operations at DOE sites to be safer, faster and cheaper. Five priority DOE sites were visited in March 1990 to identify needs for robotics technology in ER ampersand WM operations. This 5-Year Program Plan for the RTDP detailed annual plans for robotics technology development based on identified needs. This 5-Year Program Plan discusses the overall approach to be adopted by the RTDP to aggressively develop robotics technology and contains discussions of the Program Management Plan, Site Visit and Needs Summary, Approach to Needs-Directed Technical Development, Application-Specific Technical Development, and Cross-Cutting and Advanced Technology. Integrating application-specific ER ampersand WM needs, the current state of robotics technology, and the potential benefits (in terms of faster, safer, and cheaper) of new technology, the Plan develops application-specific road maps for robotics RDDT ampersand E for the period FY 1991 through FY 1995. In addition, the Plan identifies areas where longer-term research in robotics will have a high payoff in the 5- to 20-year time frame. 12 figs

Effective programming of energy consuming industrial robot systems

International Nuclear Information System (INIS)

Trnka, K.; Pinter, T.; Knazik, M.; Bozek, P.

2012-01-01

This paper discusses the problem of effective motion planning for industrial robots. The first part dealt with current method for off-line motion planning. In the second part is presented the work done with one of the simulation system with automatic trajectory generation and off-line programming capability [4]. An spot welding process is involved. The practical application of this step strongly depends on the method for robot path optimization with high accuracy, thus, transform the path into a time and energy optimal robot program for the real world, which is discussed in the third step. (Authors)

Visibility-based optimal path and motion planning

CERN Document Server

Wang, Paul Keng-Chieh

2015-01-01

This monograph deals with various visibility-based path and motion planning problems motivated by real-world applications such as exploration and mapping planetary surfaces, environmental surveillance using stationary or mobile robots, and imaging of global air/pollutant circulation. The formulation and solution of these problems call for concepts and methods from many areas of applied mathematics including computational geometry, set-covering, non-smooth optimization, combinatorial optimization and optimal control. Emphasis is placed on the formulation of new problems and methods of approach to these problems. Since geometry and visualization play important roles in the understanding of these problems, intuitive interpretations of the basic concepts are presented before detailed mathematical development. The development of a particular topic begins with simple cases illustrated by specific examples, and then progresses forward to more complex cases. The intended readers of this monograph are primarily studen...

Study on State Transition Method Applied to Motion Planning for a Humanoid Robot

Directory of Open Access Journals (Sweden)

Xuyang Wang

2008-11-01

Full Text Available This paper presents an approach of motion planning for a humanoid robot using a state transition method. In this method, motion planning is simplified by introducing a state-space to describe the whole motion series. And each state in the state-space corresponds to a contact state specified during the motion. The continuous motion is represented by a sequence of discrete states. The concept of the transition between two neighboring states, that is the state transition, can be realized by using some traditional path planning methods. Considering the dynamical stability of the robot, a state transition method based on search strategy is proposed. Different sets of trajectories are generated by using a variable 5th-order polynomial interpolation method. After quantifying the stabilities of these trajectories, the trajectories with the largest stability margin are selected as the final state transition trajectories. Rising motion process is exemplified to validate the method and the simulation results show the proposed method to be feasible and effective.

The application of Markov decision process in restaurant delivery robot

Science.gov (United States)

Wang, Yong; Hu, Zhen; Wang, Ying

2017-05-01

As the restaurant delivery robot is often in a dynamic and complex environment, including the chairs inadvertently moved to the channel and customers coming and going. The traditional path planning algorithm is not very ideal. To solve this problem, this paper proposes the Markov dynamic state immediate reward (MDR) path planning algorithm according to the traditional Markov decision process. First of all, it uses MDR to plan a global path, then navigates along this path. When the sensor detects there is no obstructions in front state, increase its immediate state reward value; when the sensor detects there is an obstacle in front, plan a global path that can avoid obstacle with the current position as the new starting point and reduce its state immediate reward value. This continues until the target is reached. When the robot learns for a period of time, it can avoid those places where obstacles are often present when planning the path. By analyzing the simulation experiment, the algorithm has achieved good results in the global path planning under the dynamic environment.

Vision-based Navigation and Reinforcement Learning Path Finding for Social Robots

OpenAIRE

Pérez Sala, Xavier

2010-01-01

We propose a robust system for automatic Robot Navigation in uncontrolled en- vironments. The system is composed by three main modules: the Arti cial Vision module, the Reinforcement Learning module, and the behavior control module. The aim of the system is to allow a robot to automatically nd a path that arrives to a pre xed goal. Turn and straight movements in uncontrolled environments are automatically estimated and controlled using the proposed modules. The Arti cial Vi...

11th International Workshop on the Algorithmic Foundations of Robotics

CERN Document Server

Amato, Nancy; Isler, Volkan; Stappen, A

2015-01-01

This carefully edited volume is the outcome of the eleventh edition of the Workshop on Algorithmic Foundations of Robotics (WAFR), which is the premier venue showcasing cutting edge research in algorithmic robotics. The eleventh WAFR, which was held August 3-5, 2014 at Boğaziçi University in Istanbul, Turkey continued this tradition. This volume contains extended versions of the 42 papers presented at WAFR. These contributions highlight the cutting edge research in classical robotics problems (e.g.  manipulation, motion, path, multi-robot and kinodynamic planning), geometric and topological computation in robotics as well novel applications such as informative path planning, active sensing and surgical planning.  This book - rich by topics and authoritative contributors - is a unique reference on the current developments and new directions in the field of algorithmic foundations.  

The development of fire detection robot

OpenAIRE

Sucuoğlu, Hilmi Saygın

2015-01-01

The aim of this thesis is to design and manufacture a fire detection robot that especially operates in industrial areas for fire inspection and early detection. Robot is designed and implemented to track prescribed paths with obstacle avoidance function through obstacle avoidance and motion planning units and to scan the environment in order to detect fire source using fire detection unit. Robot is able to track patrolling routes using virtual lines that defined to the motion planning unit. ...

Environmental restoration and waste management: Robotics technology development program: Robotics 5-year program plan

International Nuclear Information System (INIS)

1991-01-01

This plan covers robotics Research, Development, Demonstration, Testing and Evaluation activities in the Program for the next five years. These activities range from bench-scale R ampersand D to full-scale hot demonstrations at DOE sites. This plan outlines applications of existing technology to near-term needs, the development and application of enhanced technology for longer-term needs, and initiation of advanced technology development to meet those needs beyond the five-year plan. The objective of the Robotic Technology Development Program (RTDP) is to develop and apply robotics technologies that will enable Environmental Restoration and Waste Management (ER ampersand WM) operations at DOE sites to be safer, faster and cheaper. Five priority DOE sites were visited in March 1990 to identify needs for robotics technology in ER ampersand WM operations. This 5-Year Program Plan for the RTDP detailed annual plans for robotics technology development based on identified needs. In July 1990 a forum was held announcing the robotics program. Over 60 organizations (industrial, university, and federal laboratory) made presentations on their robotics capabilities. To stimulate early interactions with the ER ampersand WM activities at DOE sites, as well as with the robotics community, the RTDP sponsored four technology demonstrations related to ER ampersand WM needs. These demonstrations integrated commercial technology with robotics technology developed by DOE in support of areas such as nuclear reactor maintenance and the civilian reactor waste program. 2 figs

Motion and operation planning of robotic systems background and practical approaches

CERN Document Server

Gomez-Barvo, Fernando

2015-01-01

This book addresses the broad multi-disciplinary topic of robotics, and presents the basic techniques for motion and operation planning in robotics systems. Gathering contributions from experts in diverse and wide ranging fields, it offers an overview of the most recent and cutting-edge practical applications of these methodologies. It covers both theoretical and practical approaches, and elucidates the transition from theory to implementation. An extensive analysis is provided, including humanoids, manipulators, aerial robots and ground mobile robots. ‘Motion and Operation Planning of Robotic Systems’ addresses the following topics: *The theoretical background of robotics. *Application of motion planning techniques to manipulators, such as serial and parallel manipulators. *Mobile robots planning, including robotic applications related to aerial robots, large scale robots and traditional wheeled robots. *Motion planning for humanoid robots. An invaluable reference text for graduate students and researche...

A Velocity-Level Bi-Criteria Optimization Scheme for Coordinated Path Tracking of Dual Robot Manipulators Using Recurrent Neural Network.

Science.gov (United States)

Xiao, Lin; Zhang, Yongsheng; Liao, Bolin; Zhang, Zhijun; Ding, Lei; Jin, Long

2017-01-01

A dual-robot system is a robotic device composed of two robot arms. To eliminate the joint-angle drift and prevent the occurrence of high joint velocity, a velocity-level bi-criteria optimization scheme, which includes two criteria (i.e., the minimum velocity norm and the repetitive motion), is proposed and investigated for coordinated path tracking of dual robot manipulators. Specifically, to realize the coordinated path tracking of dual robot manipulators, two subschemes are first presented for the left and right robot manipulators. After that, such two subschemes are reformulated as two general quadratic programs (QPs), which can be formulated as one unified QP. A recurrent neural network (RNN) is thus presented to solve effectively the unified QP problem. At last, computer simulation results based on a dual three-link planar manipulator further validate the feasibility and the efficacy of the velocity-level optimization scheme for coordinated path tracking using the recurrent neural network.

Control of wheeled mobile robot in restricted environment

Science.gov (United States)

Ali, Mohammed A. H.; En, Chang Yong

2018-03-01

This paper presents a simulation and practical control system for wheeled mobile robot in restricted environment. A wheeled mobile robot with 3 wheels is fabricated and controlled by proportional derivative active force control (PD-AFC) to move in a pre-planned restricted environment to maintain the tracking errors at zero level. A control system with two loops, outer by PD controller and inner loop by Active Force Control, are designed to control the wheeled mobile robot. Fuzzy logic controller is implemented in the Active force Control to estimate the inertia matrix that will be used to calculate the actual torque applied on the wheeled mobile robot. The mobile robot is tested in two different trajectories, namely are circular and straight path. The actual path and desired path are compared.

Planning and decision making for aerial robots

CERN Document Server

Bestaoui Sebbane, Yasmina

2014-01-01

This book provides an introduction to the emerging field of planning and decision making for aerial robots. An aerial robot is the ultimate form of Unmanned Aerial Vehicle, an aircraft endowed with built-in intelligence, requiring no direct human control and able to perform a specific task. It must be able to fly within a partially structured environment, to react and adapt to changing environmental conditions and to accommodate for the uncertainty that exists in the physical world. An aerial robot can be termed as a physical agent that exists and flies in the real 3D world, can sense its environment and act on it to achieve specific goals. So throughout this book, an aerial robot will also be termed as an agent.   Fundamental problems in aerial robotics include the tasks of spatial motion, spatial sensing and spatial reasoning. Reasoning in complex environments represents a difficult problem. The issues specific to spatial reasoning are planning and decision making. Planning deals with the trajectory algori...

IMPERA: Integrated Mission Planning for Multi-Robot Systems

Directory of Open Access Journals (Sweden)

Daniel Saur

2015-10-01

Full Text Available This paper presents the results of the project IMPERA (Integrated Mission Planning for Distributed Robot Systems. The goal of IMPERA was to realize an extraterrestrial exploration scenario using a heterogeneous multi-robot system. The main challenge was the development of a multi-robot planning and plan execution architecture. The robot team consists of three heterogeneous robots, which have to explore an unknown environment and collect lunar drill samples. The team activities are described using the language ALICA (A Language for Interactive Agents. Furthermore, we use the mission planning system pRoPhEt MAS (Reactive Planning Engine for Multi-Agent Systems to provide an intuitive interface to generate team activities. Therefore, we define the basic skills of our team with ALICA and define the desired goal states by using a logic description. Based on the skills, pRoPhEt MAS creates a valid ALICA plan, which will be executed by the team. The paper describes the basic components for communication, coordinated exploration, perception and object transportation. Finally, we evaluate the planning engine pRoPhEt MAS in the IMPERA scenario. In addition, we present further evaluation of pRoPhEt MAS in more dynamic environments.

ON TRAVERSABILITY COST EVALUATION FROM PROPRIOCEPTIVE SENSING FOR A CRAWLING ROBOT

Directory of Open Access Journals (Sweden)

Jakub Mrva

2015-12-01

Full Text Available Traversability characteristics of the robot working environment are crucial in planning an efficient path for a robot operating in rough unstructured areas. In the literature, approaches to wheeled or tracked robots can be found, but a relatively little attention is given to walking multi-legged robots. Moreover, the existing approaches for terrain traversability assessment seem to be focused on gathering key features from a terrain model acquired from range data or camera image and only occasionally supplemented with proprioceptive sensing that expresses the interaction of the robot with the terrain. This paper addresses the problem of traversability cost evaluation based on proprioceptive sensing for a hexapod walking robot while optimizing different criteria. We present several methods of evaluating the robot-terrain interaction that can be used as a cost function for an assessment of the robot motion that can be utilized in high-level path-planning algorithms.

Multi-robot caravanning

KAUST Repository

Denny, Jory

2013-11-01

We study multi-robot caravanning, which is loosely defined as the problem of a heterogeneous team of robots visiting specific areas of an environment (waypoints) as a group. After formally defining this problem, we propose a novel solution that requires minimal communication and scales with the number of waypoints and robots. Our approach restricts explicit communication and coordination to occur only when robots reach waypoints, and relies on implicit coordination when moving between a given pair of waypoints. At the heart of our algorithm is the use of leader election to efficiently exploit the unique environmental knowledge available to each robot in order to plan paths for the group, which makes it general enough to work with robots that have heterogeneous representations of the environment. We implement our approach both in simulation and on a physical platform, and characterize the performance of the approach under various scenarios. We demonstrate that our approach can successfully be used to combine the planning capabilities of different agents. © 2013 IEEE.

A Piecewise Acceleration-Optimal and Smooth-Jerk Trajectory Planning Method for Robot Manipulator along a Predefined Path

Directory of Open Access Journals (Sweden)

Yuan Chen

2011-09-01

Full Text Available This paper proposes a piecewise acceleration-optimal and smooth-jerk trajectory planning method of robot manipulator. The optimal objective function is given by the weighted sum of two terms having opposite effects: the maximal acceleration and the minimal jerk. Some computing techniques are proposed to determine the optimal solution. These techniques take both the time intervals between two interpolation points and the control points of B-spline function as optimal variables, redefine the kinematic constraints as the constraints of optimal variables, and reformulate the objective function in matrix form. The feasibility of the optimal method is illustrated by simulation and experimental results with pan mechanism for cooking robot.

The application of Markov decision process with penalty function in restaurant delivery robot

Science.gov (United States)

Wang, Yong; Hu, Zhen; Wang, Ying

2017-05-01

As the restaurant delivery robot is often in a dynamic and complex environment, including the chairs inadvertently moved to the channel and customers coming and going. The traditional Markov decision process path planning algorithm is not save, the robot is very close to the table and chairs. To solve this problem, this paper proposes the Markov Decision Process with a penalty term called MDPPT path planning algorithm according to the traditional Markov decision process (MDP). For MDP, if the restaurant delivery robot bumps into an obstacle, the reward it receives is part of the current status reward. For the MDPPT, the reward it receives not only the part of the current status but also a negative constant term. Simulation results show that the MDPPT algorithm can plan a more secure path.

Trajectory Planning for Robots in Dynamic Human Environments

DEFF Research Database (Denmark)

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

2010-01-01

This paper present a trajectory planning algorithm for a robot operating in dynamic human environments. Environments such as pedestrian streets, hospital corridors and train stations. We formulate the problem as planning a minimal cost trajectory through a potential field, defined from...... is enhanced to direct the search and account for the kinodynamic robot constraints. Compared to standard RRT, the algorithm proposed here find the robot control input that will drive the robot towards a new sampled point in the configuration space. The effect of the input is simulated, to add a reachable...

RSMDP-based Robust Q-learning for Optimal Path Planning in a Dynamic Environment

Directory of Open Access Journals (Sweden)

Yunfei Zhang

2014-07-01

Full Text Available This paper presents arobust Q-learning method for path planningin a dynamic environment. The method consists of three steps: first, a regime-switching Markov decision process (RSMDP is formed to present the dynamic environment; second a probabilistic roadmap (PRM is constructed, integrated with the RSMDP and stored as a graph whose nodes correspond to a collision-free world state for the robot; and third, an onlineQ-learning method with dynamic stepsize, which facilitates robust convergence of the Q-value iteration, is integrated with the PRM to determine an optimal path for reaching the goal. In this manner, the robot is able to use past experience for improving its performance in avoiding not only static obstacles but also moving obstacles, without knowing the nature of the obstacle motion. The use ofregime switching in the avoidance of obstacles with unknown motion is particularly innovative.  The developed approach is applied to a homecare robot in computer simulation. The results show that the online path planner with Q-learning is able torapidly and successfully converge to the correct path.

Trajectory planning of mobile robots using indirect solution of optimal control method in generalized point-to-point task

Science.gov (United States)

Nazemizadeh, M.; Rahimi, H. N.; Amini Khoiy, K.

2012-03-01

This paper presents an optimal control strategy for optimal trajectory planning of mobile robots by considering nonlinear dynamic model and nonholonomic constraints of the system. The nonholonomic constraints of the system are introduced by a nonintegrable set of differential equations which represent kinematic restriction on the motion. The Lagrange's principle is employed to derive the nonlinear equations of the system. Then, the optimal path planning of the mobile robot is formulated as an optimal control problem. To set up the problem, the nonlinear equations of the system are assumed as constraints, and a minimum energy objective function is defined. To solve the problem, an indirect solution of the optimal control method is employed, and conditions of the optimality derived as a set of coupled nonlinear differential equations. The optimality equations are solved numerically, and various simulations are performed for a nonholonomic mobile robot to illustrate effectiveness of the proposed method.

A 3D motion planning framework for snake robots

OpenAIRE

Liljebäck, Pål; Pettersen, Kristin Ytterstad; Stavdahl, Øyvind; Gravdahl, Jan Tommy

2014-01-01

- Author's postprint This paper presents a motion planning framework for three-dimensional body shape control of snake robots. Whereas conventional motion planning approaches define the body shape of snake robots in terms of their individual joint angles, the proposed framework allows the body shape to be specified in terms of Cartesian coordinates in the environment of the robot. This approach simplifies motion planning since Cartesian coordinates are more intuitively mapped to the overal...

Sensor-guided parking system for a carlike robot

Science.gov (United States)

Jiang, Kaichum; Seneviratne, L. D.

1998-07-01

This paper presents an automated parking strategy for a car- like mobile robot. The study considers general parking manoeuvre cases for a rectangular robot, including parallel parking. The robot is constructed simulating a conventional car, which is subject to non-holonomic constraints and thus only has two degrees of freedom. The parking space is considered as rectangular, and detected by ultrasonic sensors mounted on the robot. A motion planning algorithm develops a collision-free path for parking, taking into account the non- holonomic constraints acting on the car-like robot. A research into general car maneuvers has been conducted and useful results have been achieved. The motion planning algorithm uses these results, combined with configuration space method, to produce a collision-free path for parallel parking, depending on the parking space detected. A control program in the form of a graphical user interface has been developed for users to operate the system with ease. The strategy is implemented on a modified B12 mobile robot. The strategy presented has the potential for application in automobiles.

Faster-than-real-time robot simulation for plan development and robot safety

International Nuclear Information System (INIS)

Crane, C.D. III; Dalton, R.; Ogles, J.; Tulenko, J.S.; Zhou, X.

1990-01-01

The University of Florida, in cooperation with the Universities of Texas, Tennessee, and Michigan and Oak Ridge National Laboratory (ORNL), is developing an advanced robotic system for the US Department of Energy under the University Program for Robotics for Advanced Reactors. As part of this program, the University of Florida has been pursuing the development of a faster-than-real-time robotic simulation program for planning and control of mobile robotic operations to ensure the efficient and safe operation of mobile robots in nuclear power plants and other hazardous environments

Picking Robot Arm Trajectory Planning Method

Directory of Open Access Journals (Sweden)

Zhang Zhiyong

2014-01-01

Full Text Available The picking robot arm is scheduled to complete picking tasks in the working space, to overcome the shaking vibration to improve the picking stability, its movement should follow specific consistence trajectory points. Usually we should give definite multiple feature picking points, map their inverse kinematics to the joint space, establish motion equation for the corresponding point in the joint space, then follow these equations motion for the interpolation on the joint so that we can meet the movement requirements. Trajectory planning is decisive significance for accuracy and stability of controlling robot arm. The key issue that picking arm complete picking task will be come true by trajectory planning, namely, robot arm track the desired trajectory. which based on kinematics and statics picking analysis in a joint space according to the requirements of picking tasks, and obtain the position and orientation for picking robot arm, study and calculate the theory of trajectory parameters timely.

An optimized field coverage planning approach for navigation of agricultural robots in fields involving obstacle areas

DEFF Research Database (Denmark)

Hameed, Ibahim; Bochtis, D.; Sørensen, C.A.

2013-01-01

-field obstacle areas, the headland paths generation for the field and each obstacle area, the implementation of a genetic algorithm to optimize the sequence that the field robot vehicle will follow to visit the blocks, and an algorithmically generation of the task sequences derived from the farmer practices......Technological advances combined with the demand of cost efficiency and environmental considerations lead farmers to review their practices towards the adoption of new managerial approaches including enhanced automation. The application of field robots is one of the most promising advances among....... This approach has proven that it is possible to capture the practices of farmers and embed these practices in an algorithmic description providing a complete field area coverage plan in a form prepared for execution by the navigation system of a field robot....

Automatic Motion Generation for Robotic Milling Optimizing Stiffness with Sample-Based Planning

Directory of Open Access Journals (Sweden)

Julian Ricardo Diaz Posada

2017-01-01

Full Text Available Optimal and intuitive robotic machining is still a challenge. One of the main reasons for this is the lack of robot stiffness, which is also dependent on the robot positioning in the Cartesian space. To make up for this deficiency and with the aim of increasing robot machining accuracy, this contribution describes a solution approach for optimizing the stiffness over a desired milling path using the free degree of freedom of the machining process. The optimal motion is computed based on the semantic and mathematical interpretation of the manufacturing process modeled on its components: product, process and resource; and by configuring automatically a sample-based motion problem and the transition-based rapid-random tree algorithm for computing an optimal motion. The approach is simulated on a CAM software for a machining path revealing its functionality and outlining future potentials for the optimal motion generation for robotic machining processes.

Path Planning of Mobile Elastic Robotic Arms by Indirect Approach of Optimal Control

Directory of Open Access Journals (Sweden)

Moharam Habibnejad Korayem

2011-03-01

Full Text Available Finding optimal trajectory is critical in several applications of robot manipulators. This paper is applied the open-loop optimal control approach for generating the optimal trajectory of the flexible mobile manipulators in point-to-point motion. This method is based on the Pontryagin-s minimum principle that by providing a two-point boundary value problem is solved the problem. This problem is known to be complex in particular when combined motion of the base and manipulator, non-holonomic constraint of the base and highly non-linear and complicated dynamic equations as a result of flexible nature of links are taken into account. The study emphasizes on modeling of the complete optimal control problem by remaining all nonlinear state and costate variables as well as control constraints. In this method, designer can compromise between different objectives by considering the proper penalty matrices and it yields to choose the proper trajectory among the various paths. The effectiveness and capability of the proposed approach are demonstrated through simulation studies. Finally, to verify the proposed method, the simulation results obtained from the model are compared with the results of those available in the literature.

Research on Semi-automatic Bomb Fetching for an EOD Robot

Directory of Open Access Journals (Sweden)

Qian Jun

2008-11-01

Full Text Available An EOD robot system, SUPER-PLUS, which has a novel semi-automatic bomb fetching function is presented in this paper. With limited support of human, SUPER-PLUS scans the cluttered environment with a wrist-mounted laser distance sensor and plans the manipulator a collision free path to fetch the bomb. The model construction of manipulator, bomb and environment, C-space map, path planning and the operation procedure are introduced in detail. The semi-automatic bomb fetching function has greatly improved the operation performance of EOD robot.

Research on Semi-Automatic Bomb Fetching for an EOD Robot

Directory of Open Access Journals (Sweden)

Zeng Jian-Jun

2007-06-01

Full Text Available An EOD robot system, SUPER-PLUS, which has a novel semi-automatic bomb fetching function is presented in this paper. With limited support of human, SUPER-PLUS scans the cluttered environment with a wrist-mounted laser distance sensor and plans the manipulator a collision free path to fetch the bomb. The model construction of manipulator, bomb and environment, C-space map, path planning and the operation procedure are introduced in detail. The semi-automatic bomb fetching function has greatly improved the operation performance of EOD robot.

Multibody system dynamics, robotics and control

CERN Document Server

Gerstmayr, Johannes

2013-01-01

The volume contains 19 contributions by international experts in the field of multibody system dynamics, robotics and control. The book aims to bridge the gap between the modeling of mechanical systems by means of multibody dynamics formulations and robotics. In the classical approach, a multibody dynamics model contains a very high level of detail, however, the application of such models to robotics or control is usually limited. The papers aim to connect the different scientific communities in multibody dynamics, robotics and control. Main topics are flexible multibody systems, humanoid robots, elastic robots, nonlinear control, optimal path planning, and identification.

A Motion Planning Method for Omnidirectional Mobile Robot Based on the Anisotropic Characteristics

Directory of Open Access Journals (Sweden)

Chuntao Leng

2008-11-01

Full Text Available A more suitable motion planning method for an omni-directional mobile robot (OMR, an improved APF method (iAPF, is proposed in this paper by introducing the revolving factor into the artificial potential field (APF. Accordingly, the motion direction derived from traditional artificial potential field (tAPF is regulated. The maximum velocity, maximum acceleration and energy consumption of the OMR moving in different directions are analyzed, based on the kinematic and dynamic constraints of an OMR, and the anisotropy of OMR is presented in this paper. Then the novel concept of an Anisotropic-Function is proposed to indicate the quality of motion in different directions, which can make a very favorable trade-off between time-optimality, stability and efficacy-optimality. In order to obtain the optimal motion, the path that the robot can take in order to avoid the obstacle safely and reach the goal in a shorter path is deduced. Finally, simulations and experiments are carried out to demonstrate that the motion resulting from the iAPF is high-speed, highly stable and highly efficient when compared to the tAPF.

Marine Robot Autonomy

CERN Document Server

2013-01-01

Autonomy for Marine Robots provides a timely and insightful overview of intelligent autonomy in marine robots. A brief history of this emerging field is provided, along with a discussion of the challenges unique to the underwater environment and their impact on the level of intelligent autonomy required.  Topics covered at length examine advanced frameworks, path-planning, fault tolerance, machine learning, and cooperation as relevant to marine robots that need intelligent autonomy.  This book also: Discusses and offers solutions for the unique challenges presented by more complex missions and the dynamic underwater environment when operating autonomous marine robots Includes case studies that demonstrate intelligent autonomy in marine robots to perform underwater simultaneous localization and mapping  Autonomy for Marine Robots is an ideal book for researchers and engineers interested in the field of marine robots.      

Minimum dose method for walking-path planning of nuclear facilities

International Nuclear Information System (INIS)

Liu, Yong-kuo; Li, Meng-kun; Xie, Chun-li; Peng, Min-jun; Wang, Shuang-yu; Chao, Nan; Liu, Zhong-kun

2015-01-01

Highlights: • For radiation environment, the environment model is proposed. • For the least dose walking path problem, a path-planning method is designed. • The path-planning virtual–real mixed simulation program is developed. • The program can plan walking path and simulate. - Abstract: A minimum dose method based on staff walking road network model was proposed for the walking-path planning in nuclear facilities. A virtual–reality simulation program was developed using C# programming language and Direct X engine. The simulation program was used in simulations dealing with virtual nuclear facilities. Simulation results indicated that the walking-path planning method was effective in providing safety for people walking in nuclear facilities

Solar-based navigation for robotic explorers

Science.gov (United States)

Shillcutt, Kimberly Jo

2000-12-01

This thesis introduces the application of solar position and shadowing information to robotic exploration. Power is a critical resource for robots with remote, long-term missions, so this research focuses on the power generation capabilities of robotic explorers during navigational tasks, in addition to power consumption. Solar power is primarily considered, with the possibility of wind power also contemplated. Information about the environment, including the solar ephemeris, terrain features, time of day, and surface location, is incorporated into a planning structure, allowing robots to accurately predict shadowing and thus potential costs and gains during navigational tasks. By evaluating its potential to generate and expend power, a robot can extend its lifetime and accomplishments. The primary tasks studied are coverage patterns, with a variety of plans developed for this research. The use of sun, terrain and temporal information also enables new capabilities of identifying and following sun-synchronous and sun-seeking paths. Digital elevation maps are combined with an ephemeris algorithm to calculate the altitude and azimuth of the sun from surface locations, and to identify and map shadows. Solar navigation path simulators use this information to perform searches through two-dimensional space, while considering temporal changes. Step by step simulations of coverage patterns also incorporate time in addition to location. Evaluations of solar and wind power generation, power consumption, area coverage, area overlap, and time are generated for sets of coverage patterns, with on-board environmental information linked to the simulations. This research is implemented on the Nomad robot for the Robotic Antarctic Meteorite Search. Simulators have been developed for coverage pattern tests, as well as for sun-synchronous and sun-seeking path searches. Results of field work and simulations are reported and analyzed, with demonstrated improvements in efficiency

Integrating Robot Task Planning into Off-Line Programming Systems

DEFF Research Database (Denmark)

Sun, Hongyan; Kroszynski, Uri

1988-01-01

a system architecture for integrated robot task planning. It identifies and describes the components considered necessary for implementation. The focus is on functionality of these elements as well as on the information flow. A pilot implementation of such an integrated system architecture for a robot......The addition of robot task planning in off-line programming systems aims at improving the capability of current state-of-the-art commercially available off-line programming systems, by integrating modeling, task planning, programming and simulation together under one platform. This article proposes...... assembly task is discussed....

Feasible Path Planning for Autonomous Vehicles

Directory of Open Access Journals (Sweden)

Vu Trieu Minh

2014-01-01

Full Text Available The objective of this paper is to find feasible path planning algorithms for nonholonomic vehicles including flatness, polynomial, and symmetric polynomial trajectories subject to the real vehicle dynamical constraints. Performances of these path planning methods are simulated and compared to evaluate the more realistic and smoother generated trajectories. Results show that the symmetric polynomial algorithm provides the smoothest trajectory. Therefore, this algorithm is recommended for the development of an automatic control for autonomous vehicles.

Visual identification and similarity measures used for on-line motion planning of autonomous robots in unknown environments

Science.gov (United States)

Martínez, Fredy; Martínez, Fernando; Jacinto, Edwar

2017-02-01

In this paper we propose an on-line motion planning strategy for autonomous robots in dynamic and locally observable environments. In this approach, we first visually identify geometric shapes in the environment by filtering images. Then, an ART-2 network is used to establish the similarity between patterns. The proposed algorithm allows that a robot establish its relative location in the environment, and define its navigation path based on images of the environment and its similarity to reference images. This is an efficient and minimalist method that uses the similarity of landmark view patterns to navigate to the desired destination. Laboratory tests on real prototypes demonstrate the performance of the algorithm.

Dynamic Modelling and Adaptive Traction Control for Mobile Robots

Directory of Open Access Journals (Sweden)

A. Albagul

2004-09-01

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

A survey on inspecting structures using robotic systems

Directory of Open Access Journals (Sweden)

Randa Almadhoun

2016-11-01

Full Text Available Advancements in robotics and autonomous systems are being deployed nowadays in many application domains such as search and rescue, industrial automation, domestic services and healthcare. These systems are developed to tackle tasks in some of the most challenging, labour intensive and dangerous environments. Inspecting structures (e.g. bridges, buildings, ships, wind turbines and aircrafts is considered a hard task for humans to perform and of critical importance since missing any details could affect the structure’s performance and integrity. Additionally, structure inspection is time and resource intensive and should be performed as efficiently and accurately as possible. Inspecting various structures has been reported in the literature using different robotic platforms to: inspect difficult to reach areas and detect various types of faults and anomalies. Typically, inspection missions involve performing three main tasks: coverage path planning, shape, model or surface reconstruction and the actual inspection of the structure. Coverage path planning ensures the generation of an optimized path that guarantees the complete coverage of the structure of interest in order to gather highly accurate information to be used for shape/model reconstruction. This article aims to provide an overview of the recent work and breakthroughs in the field of coverage path planning and model reconstruction, with focus on 3D reconstruction, for the purpose of robotic inspection.

Manipulator motion planning for high-speed robotic laser cutting

OpenAIRE

Dolgui , Alexandre; Pashkevich , Anatol

2009-01-01

Abstract Recent advances in laser technology, and especially the essential increase of the cutting speed, motivate amending the existing robot path methods, which do not allow the complete utilisation of the actuator capabilities as well as neglect some particularities in the mechanical design of the wrist of the manipulator arm. This research addresses the optimisation of the 6-axes robot motions for continuous contour tracking while considering the redundancy caused by the tool a...

Robot path Planning Using  SIFT and Sonar Sensor Fusion

DEFF Research Database (Denmark)

Plascencia, Alfredo; Raposo, Hector

2007-01-01

and evidential grid maps, respectively. The approach is illustrated using actual measurements from a laboratory robot. The sensory information is obtained from a sonar array and the Scale Invariant Feature Transform (SIFT) algorithm. Finally, the resulting two evidential maps based on Bayes and Dempster theories...

Multi-Robot Motion Planning: A Timed Automata Approach

DEFF Research Database (Denmark)

Quottrup, Michael Melholt; Bak, Thomas; Izadi-Zamanabadi, Roozbeh

2004-01-01

This paper describes how a network of interacting timed automata can be used to model, analyze, and verify motion planning problems in a scenario with multiple robotic vehicles. The method presupposes an infra-structure of robots with feed-back controllers obeying simple restriction on a planar...... grid. The automata formalism merely presents a high-level model of environment, robots and control, but allows composition and formal symbolic reasoning about coordinated solutions. Composition is achieved through synchronization, and the verification software UPPAAL is used for a symbolic verification...... then subsequently be used as a high-level motion plan for the robots. This paper reports on the timed automata framework, results of two verification experiments, promise of the approach, and gives a perspective for future research....

Multi-Robot Motion Planning: A Timed Automata Approach

DEFF Research Database (Denmark)

Quottrup, Michael Melholt; Bak, Thomas; Izadi-Zamanabadi, Roozbeh

This paper describes how a network of interacting timed automata can be used to model, analyze, and verify motion planning problems in a scenario with multiple robotic vehicles. The method presupposes an infra-structure of robots with feed-back controllers obeying simple restriction on a planar...... grid. The automata formalism merely presents a high-level model of environment, robots and control, but allows composition and formal symbolic reasoning about coordinated solutions. Composition is achieved through synchronization, and the verification software UPPAAL is used for a symbolic verification...... then subsequently be used as a high-level motion plan for the robots. This paper reports on the timed automata framework, results of two verification experiments, promise of the approach, and gives a perspective for future research....

Robots and lattice automata

CERN Document Server

Adamatzky, Andrew

2015-01-01

The book gives a comprehensive overview of the state-of-the-art research and engineering in theory and application of Lattice Automata in design and control of autonomous Robots. Automata and robots share the same notional meaning. Automata (originated from the latinization of the Greek word “αυτόματον”) as self-operating autonomous machines invented from ancient years can be easily considered the first steps of robotic-like efforts. Automata are mathematical models of Robots and also they are integral parts of robotic control systems. A Lattice Automaton is a regular array or a collective of finite state machines, or automata. The Automata update their states by the same rules depending on states of their immediate neighbours. In the context of this book, Lattice Automata are used in developing modular reconfigurable robotic systems, path planning and map exploration for robots, as robot controllers, synchronisation of robot collectives, robot vision, parallel robotic actuators. All chapters are...

Autonomous guided vehicles methods and models for optimal path planning

CERN Document Server

Fazlollahtabar, Hamed

2015-01-01

  This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with A...

Repetitive motion planning and control of redundant robot manipulators

CERN Document Server

Zhang, Yunong

2013-01-01

Repetitive Motion Planning and Control of Redundant Robot Manipulators presents four typical motion planning schemes based on optimization techniques, including the fundamental RMP scheme and its extensions. These schemes are unified as quadratic programs (QPs), which are solved by neural networks or numerical algorithms. The RMP schemes are demonstrated effectively by the simulation results based on various robotic models; the experiments applying the fundamental RMP scheme to a physical robot manipulator are also presented. As the schemes and the corresponding solvers presented in the book have solved the non-repetitive motion problems existing in redundant robot manipulators, it is of particular use in applying theoretical research based on the quadratic program for redundant robot manipulators in industrial situations. This book will be a valuable reference work for engineers, researchers, advanced undergraduate and graduate students in robotics fields. Yunong Zhang is a professor at The School of Informa...

Laser speckle velocimetry for robot manufacturing

Science.gov (United States)

Charrett, Thomas O. H.; Bandari, Yashwanth K.; Michel, Florent; Ding, Jialuo; Williams, Stewart W.; Tatam, Ralph P.

2017-06-01

A non-contact speckle correlation sensor for the measurement of robotic tool speed is presented for use in robotic manufacturing and is capable of measuring the in-plane relative velocities between a robot end-effector and the workpiece or other surface. The sensor performance was assessed in the laboratory with the sensor accuracies found to be better than 0:01 mm/s over a 70 mm/s velocity range. Finally an example of the sensors application to robotic manufacturing is presented where the sensor was applied to tool speed measurement for path planning in the wire and arc additive manufacturing process using a KUKA KR150 L110/2 industrial robot.

Artificial Potential Field Approach to Path Tracking for a Non-Holonomic Mobile Robot

DEFF Research Database (Denmark)

Sørensen, M.J.

2003-01-01

This paper introduces a novel path tracking controller for an over-actuated robotic vehicle moving in an agricultural field. The vehicle itself is a four wheel steered, four wheel driven vehicle subject to the two non-holonomic constraints of free rolling and non-slipping wheels. A dynamic model...

Self-repairing control for damaged robotic manipulators

International Nuclear Information System (INIS)

Eisler, G.R.; Robinett, R.D.; Dohrmann, C.R.; Driessen, B.J.

1997-03-01

Algorithms have been developed allowing operation of robotic systems under damaged conditions. Specific areas addressed were optimal sensor location, adaptive nonlinear control, fault-tolerant robot design, and dynamic path-planning. A seven-degree-of-freedom, hydraulic manipulator, with fault-tolerant joint design was also constructed and tested. This report completes this project which was funded under the Laboratory Directed Research and Development program

Static and Dynamic Path Planning Using Incremental Heuristic Search

OpenAIRE

Khattab, Asem

2018-01-01

Path planning is an important component in any highly automated vehicle system. In this report, the general problem of path planning is considered first in partially known static environments where only static obstacles are present but the layout of the environment is changing as the agent acquires new information. Attention is then given to the problem of path planning in dynamic environments where there are moving obstacles in addition to the static ones. Specifically, a 2D car-like agent t...

Intelligent mobile robots

International Nuclear Information System (INIS)

Ichikawa, Yoshiaki; Senoo, Makoto

1984-01-01

For the purpose of the application to remote working apparatuses in nuclear power plants and others, the software and moving mechanism of mobile robots that automatically accomplish the movement by only specifying the destination were manufactured for trial. The software has the function of searching a path to determine the quasi-shortest path and the function of controlling execution to control the action of the robots and guide to the destination. By taking heuristics into the method of searching a path and utilizing ultrasonic waves for the function of sight as they can easily detect distance though the information quantity is small, the execution was accelerated. By the simulation examination and the experiment using a mobile apparatus made for trial, it was confirmed that the route plan was able to be made almost in real time, and the appearance of an unknown obstacle was detected before collision and able to be reasonably avoided by the revision of the plan. An environment model, a route planner, the program for controlling execution, the makeup and control of moving function and the experiment on the movement are reported. The shortening of the processing time by dealing with unconfirmed echo and simplifying the writing in a map is a future problem. (Kako, I.)

A Review of Robotics Technologies for On-Orbit Services

Science.gov (United States)

2013-01-01

The SpaceX vehicle has successfully accomplished its first docking with the ISS in May 2012, delivered about 1,200 lbs of water, food , and other...algorithms, which can generate collision-free robot motion paths. Recently, Franch et al [101] have employed flatness theory to plan trajectories...3713–3719 (2005). [101] Franch J, Agrawal S, Fattah A, "Design of Differentially Flat Planar Space Robots: a Step Forward in Their Planning and

Robot Trajectories Comparison: A Statistical Approach

Directory of Open Access Journals (Sweden)

A. Ansuategui

2014-01-01

Full Text Available The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM2 and WaveFront, using different environments, robots, and local planners.

Robot Trajectories Comparison: A Statistical Approach

Science.gov (United States)

Ansuategui, A.; Arruti, A.; Susperregi, L.; Yurramendi, Y.; Jauregi, E.; Lazkano, E.; Sierra, B.

2014-01-01

The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM2 and WaveFront, using different environments, robots, and local planners. PMID:25525618

Development and human factors analysis of an augmented reality interface for multi-robot tele-operation and control

Science.gov (United States)

Lee, Sam; Lucas, Nathan P.; Ellis, R. Darin; Pandya, Abhilash

2012-06-01

This paper presents a seamlessly controlled human multi-robot system comprised of ground and aerial robots of semiautonomous nature for source localization tasks. The system combines augmented reality interfaces capabilities with human supervisor's ability to control multiple robots. The role of this human multi-robot interface is to allow an operator to control groups of heterogeneous robots in real time in a collaborative manner. It used advanced path planning algorithms to ensure obstacles are avoided and that the operators are free for higher-level tasks. Each robot knows the environment and obstacles and can automatically generate a collision-free path to any user-selected target. It displayed sensor information from each individual robot directly on the robot in the video view. In addition, a sensor data fused AR view is displayed which helped the users pin point source information or help the operator with the goals of the mission. The paper studies a preliminary Human Factors evaluation of this system in which several interface conditions are tested for source detection tasks. Results show that the novel Augmented Reality multi-robot control (Point-and-Go and Path Planning) reduced mission completion times compared to the traditional joystick control for target detection missions. Usability tests and operator workload analysis are also investigated.

Global and Local Path Planning Study in a ROS-Based Research Platform for Autonomous Vehicles

Directory of Open Access Journals (Sweden)

Pablo Marin-Plaza

2018-01-01

Full Text Available The aim of this work is to integrate and analyze the performance of a path planning method based on Time Elastic Bands (TEB in real research platform based on Ackermann model. Moreover, it will be proved that all modules related to the navigation can coexist and work together to achieve the goal point without any collision. The study is done by analyzing the trajectory generated from global and local planners. The software prototyping tool is Robot Operating System (ROS from Open Source Robotics Foundation and the research platform is the iCab (Intelligent Campus Automobile from University Carlos III. This work has been validated from a test inside the campus where the iCab has performed the navigation between the starting point and the goal point without any collision. During the experiment, we proved the low sensitivity of the TEB method to variations of the vehicle model configuration and constraints.

Trajectory planning of tokamak flexible in-vessel inspection robot

Energy Technology Data Exchange (ETDEWEB)

Wang, Hesheng [Department of Automation, Shanghai Jiao Tong University, 200240 Shanghai (China); Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240 Shanghai (China); Chen, Weidong, E-mail: wdchen@sjtu.edu.cn [Department of Automation, Shanghai Jiao Tong University, 200240 Shanghai (China); Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240 Shanghai (China); Lai, Yinping; He, Tao [Department of Automation, Shanghai Jiao Tong University, 200240 Shanghai (China); Key Laboratory of System Control and Information Processing, Ministry of Education of China, 200240 Shanghai (China)

2015-10-15

Highlights: • A tokamak flexible in-vessel inspection robot is designed. • Two trajectory planning methods are used to ensure the full coverage of the first wall scanning. • The method is tested on a simulated platform of EAST with the flexible in-vessel inspection robot. • Experimental results show the effectiveness of the proposed algorithm. - Abstract: Tokamak flexible in-vessel inspection robot is mainly designed to carry a camera for close observation of the first wall of the vacuum vessel, which is essential for the maintenance of the future tokamak reactor without breaking the working condition of the vacuum vessel. A tokamak flexible in-vessel inspection robot is designed. In order to improve efficiency of the remote maintenance, it is necessary to design a corresponding trajectory planning algorithm to complete the automatic full coverage scanning of the complex tokamak cavity. Two different trajectory planning methods, RS (rough scanning) and FS (fine scanning), according to different demands of the task, are used to ensure the full coverage of the first wall scanning. To quickly locate the damage position, the first trajectory planning method is targeted for quick and wide-ranging scan of the tokamak D-shaped section, and the second one is for careful observation. Furthermore, both of the two different trajectory planning methods can ensure the full coverage of the first wall scanning with an optimal end posture. The method is tested on a simulated platform of EAST (Experimental Advanced Superconducting Tokamak) with the flexible in-vessel inspection robot, and the results show the effectiveness of the proposed algorithm.

Trajectory planning of tokamak flexible in-vessel inspection robot

International Nuclear Information System (INIS)

Wang, Hesheng; Chen, Weidong; Lai, Yinping; He, Tao

2015-01-01

Highlights: • A tokamak flexible in-vessel inspection robot is designed. • Two trajectory planning methods are used to ensure the full coverage of the first wall scanning. • The method is tested on a simulated platform of EAST with the flexible in-vessel inspection robot. • Experimental results show the effectiveness of the proposed algorithm. - Abstract: Tokamak flexible in-vessel inspection robot is mainly designed to carry a camera for close observation of the first wall of the vacuum vessel, which is essential for the maintenance of the future tokamak reactor without breaking the working condition of the vacuum vessel. A tokamak flexible in-vessel inspection robot is designed. In order to improve efficiency of the remote maintenance, it is necessary to design a corresponding trajectory planning algorithm to complete the automatic full coverage scanning of the complex tokamak cavity. Two different trajectory planning methods, RS (rough scanning) and FS (fine scanning), according to different demands of the task, are used to ensure the full coverage of the first wall scanning. To quickly locate the damage position, the first trajectory planning method is targeted for quick and wide-ranging scan of the tokamak D-shaped section, and the second one is for careful observation. Furthermore, both of the two different trajectory planning methods can ensure the full coverage of the first wall scanning with an optimal end posture. The method is tested on a simulated platform of EAST (Experimental Advanced Superconducting Tokamak) with the flexible in-vessel inspection robot, and the results show the effectiveness of the proposed algorithm.

Multi-Robot Motion Planning: A Timed Automata Approach

OpenAIRE

Quottrup, Michael Melholt; Bak, Thomas; Izadi-Zamanabadi, Roozbeh

2004-01-01

This paper describes how a network of interacting timed automata can be used to model, analyze, and verify motion planning problems in a scenario with multiple robotic vehicles. The method presupposes an infra-structure of robots with feed-back controllers obeying simple restriction on a planar grid. The automata formalism merely presents a high-level model of environment, robots and control, but allows composition and formal symbolic reasoning about coordinated solutions. Composition is achi...

A bat algorithm with mutation for UCAV path planning.

Science.gov (United States)

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.

Creating spatial awareness in unmanned ground robots using SLAM

Indian Academy of Sciences (India)

sensor data to get information of the environment, to formulate its plan to achieve the given goals, to plan a path for movement to a designated location, to allow the robot to update itself con- tinuously to incorporate observed changes in its plans, etc. Among these activities, autonomous movement is very important for mobile ...

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.

Path Planning Algorithms for Autonomous Border Patrol Vehicles

Science.gov (United States)

Lau, George Tin Lam

This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.

Multi-AGV path planning with double-path constraints by using an improved genetic algorithm.

Directory of Open Access Journals (Sweden)

Zengliang Han

Full Text Available This paper investigates an improved genetic algorithm on multiple automated guided vehicle (multi-AGV path planning. The innovations embody in two aspects. First, three-exchange crossover heuristic operators are used to produce more optimal offsprings for getting more information than with the traditional two-exchange crossover heuristic operators in the improved genetic algorithm. Second, double-path constraints of both minimizing the total path distance of all AGVs and minimizing single path distances of each AGV are exerted, gaining the optimal shortest total path distance. The simulation results show that the total path distance of all AGVs and the longest single AGV path distance are shortened by using the improved genetic algorithm.

Plataforma autónoma inteligente para fútbol robot

Directory of Open Access Journals (Sweden)

Cesar Hernán Rodríguez Garavito

2008-01-01

Full Text Available This article presents the design, implementation, virtual simulation and test results for a hardware-software platform for robot soccer. The platform consists of a soccer field, a software-controlled mobile agent (AMC, a user-controlled mobile agent (MCU, a golf ball, an image sensor system and a path-planning controller. The problem for agent AMC is to sense the environment and move to a kicking position to score while avoiding opponents in its way. The soccer field is a bounded area of 1.5m x 2m in which mobile agents move following differential robot kinematics at 25.7cm/s speed; each robot has a kicking system which can speed up a golf ball at 1.43m/s velocity. A position sensor was implemented and optimised in three stages: capturing the soccer field image, converting to HSI format and applying digital filters and calculating the Cartesian components from colour patterns for identifying the mobile robots and the golf ball. Image sensor system processing speed is 30 frames per second. Robot path planning is controlled by a hybrid strategy based on two linearly combined fuzzy logic controllers; one takes agent AMC to the goal position and the other avoids obstacles while it moves to the goal position.

Environmental restoration and waste management: Robotics technology development program: Robotics 5-year program plan

International Nuclear Information System (INIS)

1991-01-01

In FY 1990 Robotics Technology Development Program (RTDP) planning teams visited five DOE sites. These sites were selected by the Office of Technology Development to provide a needs basis for developing a 5-Year Plan. Visits to five DOE sites provided identification of needs for robotics technology development to support Environmental Restoration and Waste Management (ER ampersand WM) projects at those sites. Additional site visits will be conducted in the future to expand the planning basis. This volume summarizes both the results of the site visits and the needs and requirements of the priority ER ampersand WM activities at the sites, including potential needs for robotics and remote systems technology. It also discusses hazards associated with the site activities and any problems or technical uncertainties associated with dealing with the hazards in the performance of the ER ampersand WM work. Robotic or remote systems currently under development for remediation projects or waste operations are also discussed. The information in this document is organized principally by site, activity, and priority. Section 2.0, Site Needs, is based on information from the site visit reports and provides a summary which focuses on the site needs and requirements for each priority activity. Section 2.0 also records evaluations and discussions by the RTDP team following the site visit. Section 3.0, Commonality Assessment, documents similar site needs where common, or cross-cutting, robotics technology might be applied to several activities. Section 4.0 contains a summary of the site needs and requirements in tabular form. 1 tab

Trajectory generation for car-like robots

International Nuclear Information System (INIS)

Vasseur, H.A.; Pin, F.G.

1990-01-01

Autonomous robots or remotely operated vehicles have raised high hopes in the military and industrial communities because of the potential safety improvement and gain of productivity they may provide. Waste management on nuclear sites, pallet manipulation in factories, interventions on battlefields, etc., are actively studied. A lot of these applications require powerful four-wheel vehicles, the kinematics of which is similar to that of a car. Such vehicles have three degrees of freedom: the (x,y) positions in a plane and the orientation of the vehicle. Path planning is often understood as only changing the position of the vehicle, whereas the tasks performed by this kind of robot require a perfect orientation of the vehicle: forklifting a pallet or docking at a loading or unloading station requires accuracy in the orientation of the vehicle. It is this requirement and the kinematic constraints of the motion mode that have led to the path-planning algorithm presented in this paper

A Sensor Based Navigation Algorithm for a Mobile Robot using the DVFF Approach

Directory of Open Access Journals (Sweden)

A. OUALID DJEKOUNE

2009-06-01

Full Text Available Often autonomous mobile robots operate in environment for which prior maps are incomplete or inaccurate. They require the safe execution for a collision free motion to a goal position. This paper addresses a complete navigation method for a mobile robot that moves in unknown environment. Thus, a novel method called DVFF combining the Virtual Force Field (VFF obstacle avoidance approach and global path planning based on D* algorithm is proposed. While D* generates global path information towards a goal position, the VFF local controller generates the admissible trajectories that ensure safe robot motion. Results and analysis from a battery of experiments with this new method implemented on a ATRV2 mobile robot are shown.

MR-based real time path planning for cardiac operations with transapical access.

Science.gov (United States)

Yeniaras, Erol; Navkar, Nikhil V; Sonmez, Ahmet E; Shah, Dipan J; Deng, Zhigang; Tsekos, Nikolaos V

2011-01-01

Minimally invasive surgeries (MIS) have been perpetually evolving due to their potential high impact on improving patient management and overall cost effectiveness. Currently, MIS are further strengthened by the incorporation of magnetic resonance imaging (MRI) for amended visualization and high precision. Motivated by the fact that real-time MRI is emerging as a feasible modality especially for guiding interventions and surgeries in the beating heart; in this paper we introduce a real-time path planning algorithm for intracardiac procedures. Our approach creates a volumetric safety zone inside a beating heart and updates it on-the-fly using real-time MRI during the deployment of a robotic device. In order to prove the concept and assess the feasibility of the introduced method, a realistic operational scenario of transapical aortic valve replacement in a beating heart is chosen as the virtual case study.

Active Path Planning for Drones in Object Search

OpenAIRE

Wang, Zeyangyi

2017-01-01

Object searching is one of the most popular applications of unmanned aerial vehicles. Low cost small drones are particularly suited for surveying tasks in difficult conditions. With their limited on-board processing power and battery life, there is a need for more efficient search algorithm. The proposed path planning algorithm utilizes AZ-net, a deep learning network to process images captured on drones for adaptive flight path planning. Search simulation based on videos and actual experimen...

Knowledge assistant for robotic environmental characterization

International Nuclear Information System (INIS)

Feddema, J.; Rivera, J.; Tucker, S.; Matek, J.

1996-08-01

A prototype sensor fusion framework called the open-quotes Knowledge Assistantclose quotes has been developed and tested on a gantry robot at Sandia National Laboratories. This Knowledge Assistant guides the robot operator during the planning, execution, and post analysis stages of the characterization process. During the planning stage, the Knowledge Assistant suggests robot paths and speeds based on knowledge of sensors available and their physical characteristics. During execution, the Knowledge Assistant coordinates the collection of data through a data acquisition open-quotes specialist.close quotes During execution and postanalysis, the Knowledge Assistant sends raw data to other open-quotes specialists,close quotes which include statistical pattern recognition software, a neural network, and model-based search software. After the specialists return their results, the Knowledge Assistant consolidates the information and returns a report to the robot control system where the sensed objects and their attributes (e.g., estimated dimensions, weight, material composition, etc.) are displayed in the world model. This report highlights the major components of this system

ReACT!: An Interactive Educational Tool for AI Planning for Robotics

Science.gov (United States)

Dogmus, Zeynep; Erdem, Esra; Patogulu, Volkan

2015-01-01

This paper presents ReAct!, an interactive educational tool for artificial intelligence (AI) planning for robotics. ReAct! enables students to describe robots' actions and change in dynamic domains without first having to know about the syntactic and semantic details of the underlying formalism, and to solve planning problems using…

Project ROBOTICS 2008

DEFF Research Database (Denmark)

Conrad, Finn

Mathematical modelling of Alto Robot, direct- and inverse kinematic transformation,simulation and path control applying MATLAB/SIMULINK.......Mathematical modelling of Alto Robot, direct- and inverse kinematic transformation,simulation and path control applying MATLAB/SIMULINK....

A design of toxic gas detecting security robot car based on wireless path-patrol

Directory of Open Access Journals (Sweden)

Cheng Ho-Chih

2017-01-01

Full Text Available Because a toxic gas detecting/monitoring system in a chemical plant is not movable, a gas detecting/monitoring system will be passive and the detecting range will also be constrained. This invention is an active multi-functional wireless patrol car that can substitute for humans that inspect a plant's security. In addition, to widen the monitoring vision within the environment, two motors used to rotate a wireless IPCAM with two axes are presented. Also, to control the robot car's movement, two axis motors used to drive the wheel of the robot car are also installed. Additionally, a toxic gas detector is linked to the microcontroller of the patrol car. The detected concentration of the gas will be fed back to the server pc. To enhance the robot car's patrolling duration, a movable electrical power unit in conjunction with a wireless module is also used. Consequently, this paper introduces a wireless path-patrol and toxic gas detecting security robot car that can assure a plant's security and protect workers when toxic gases are emitted.

An adaptive dual-optimal path-planning technique for unmanned air vehicles

Directory of Open Access Journals (Sweden)

Whitfield Clifford A.

2016-01-01

Full Text Available A multi-objective technique for unmanned air vehicle path-planning generation through task allocation has been developed. The dual-optimal path-planning technique generates real-time adaptive flight paths based on available flight windows and environmental influenced objectives. The environmentally-influenced flight condition determines the aircraft optimal orientation within a downstream virtual window of possible vehicle destinations that is based on the vehicle’s kinematics. The intermittent results are then pursued by a dynamic optimization technique to determine the flight path. This path-planning technique is a multi-objective optimization procedure consisting of two goals that do not require additional information to combine the conflicting objectives into a single-objective. The technique was applied to solar-regenerative high altitude long endurance flight which can benefit significantly from an adaptive real-time path-planning technique. The objectives were to determine the minimum power required flight paths while maintaining maximum solar power for continual surveillance over an area of interest (AOI. The simulated path generation technique prolonged the flight duration over a sustained turn loiter flight path by approximately 2 months for a year of flight. The potential for prolonged solar powered flight was consistent for all latitude locations, including 2 months of available flight at 60° latitude, where sustained turn flight was no longer capable.

Optimized path planning for soft tissue resection via laser vaporization

Science.gov (United States)

Ross, Weston; Cornwell, Neil; Tucker, Matthew; Mann, Brian; Codd, Patrick

2018-02-01

Robotic and robotic-assisted surgeries are becoming more prevalent with the promise of improving surgical outcomes through increased precision, reduced operating times, and minimally invasive procedures. The handheld laser scalpel in neurosurgery has been shown to provide a more gentle approach to tissue manipulation on or near critical structures over classical tooling, though difficulties of control have prevented large scale adoption of the tool. This paper presents a novel approach to generating a cutting path for the volumetric resection of tissue using a computer-guided laser scalpel. A soft tissue ablation simulator is developed and used in conjunction with an optimization routine to select parameters which maximize the total resection of target tissue while minimizing the damage to surrounding tissue. The simulator predicts the ablative properties of tissue from an interrogation cut for tuning and simulates the removal of a tumorous tissue embedded on the surface of healthy tissue using a laser scalpel. We demonstrate the ability to control depth and smoothness of cut using genetic algorithms to optimize the ablation parameters and cutting path. The laser power level, cutting rate and spacing between cuts are optimized over multiple surface cuts to achieve the desired resection volumes.

Feasibility of four-dimensional conformal planning for robotic radiosurgery

International Nuclear Information System (INIS)

Schlaefer, A.; Fisseler, J.; Dieterich, S.; Shiomi, H.; Cleary, K.; Schweikard, A.

2005-01-01

Organ motion can have a severe impact on the dose delivered by radiation therapy, and different procedures have been developed to address its effects. Conventional techniques include breath hold methods and gating. A different approach is the compensation for target motion by moving the treatment beams synchronously. Practical results have been reported for robot based radiosurgery, where a linear accelerator mounted on a robotic arm delivers the dose. However, not all organs move in the same way, which results in a relative motion of the beams with respect to the body and the tissues in the proximity of the tumor. This relative motion can severely effect the dose delivered to critical structures. We propose a method to incorporate motion in the treatment planning for robotic radiosurgery to avoid potential overdosing of organs surrounding the target. The method takes into account the motion of all considered volumes, which is discretized for dose calculations. Similarly, the beam motion is taken into account and the aggregated dose coefficient over all discrete steps is used for planning. We simulated the treatment of a moving target with three different planning methods. First, we computed beam weights based on a 3D planning situation and simulated treatment with organ motion and the beams moving synchronously to the target. Second, beam weights were computed by the 4D planning method incorporating the organ and beam motion and treatment was simulated for beams moving synchronously to the target. Third, the beam weights were determined by the 4D planning method with the beams fixed during planning and simulation. For comparison we also give results for the 3D treatment plan if there was no organ motion and when the plan is delivered by fixed beams in the presence of organ motion. The results indicate that the new 4D method is preferable and can further improve the overall conformality of motion compensated robotic radiosurgery

Development of the first force-controlled robot for otoneurosurgery.

Science.gov (United States)

Federspil, Philipp A; Geisthoff, Urban W; Henrich, Dominik; Plinkert, Peter K

2003-03-01

In some surgical specialties (eg, orthopedics), robots are already used in the operating room for bony milling work. Otological surgery and otoneurosurgery may also greatly benefit from the enhanced precision of robotics. Experimental study on robotic milling of oak wood and human temporal bone specimen. A standard industrial robot with a six-degrees-of-freedom serial kinematics was used, with force feedback to proportionally control the robot speed. Different milling modes and characteristic path parameters were evaluated to generate milling paths based on computer-aided design (CAD) geometry data of a cochlear implant and an implantable hearing system. The best-suited strategy proved to be the spiral horizontal milling mode with the burr held perpendicular to the temporal bone surface. To reduce groove height, the distance between paths should equal half the radius of the cutting burr head. Because of the vibration of the robot's own motors, a high oscillation of the SD of forces was encountered. This oscillation dropped drastically to nearly 0 Newton (N) when the burr head made contact with the dura mater, because of its damping characteristics. The cutting burr could be kept in contact with the dura mater for an extended period without damaging it, because of the burr's blunt head form. The robot moved the burr smoothly according to the encountered resistances. The study reports the first development of a functional robotic milling procedure for otoneurosurgery with force-based speed control. Future plans include implementation of ultrasound-based local navigation and performance of robotic mastoidectomy.

Robust online belief space planning in changing environments: Application to physical mobile robots

KAUST Repository

Agha-mohammadi, Ali-akbar

2014-05-01

© 2014 IEEE. Motion planning in belief space (under motion and sensing uncertainty) is a challenging problem due to the computational intractability of its exact solution. The Feedback-based Information RoadMap (FIRM) framework made an important theoretical step toward enabling roadmap-based planning in belief space and provided a computationally tractable version of belief space planning. However, there are still challenges in applying belief space planners to physical systems, such as the discrepancy between computational models and real physical models. In this paper, we propose a dynamic replanning scheme in belief space to address such challenges. Moreover, we present techniques to cope with changes in the environment (e.g., changes in the obstacle map), as well as unforeseen large deviations in the robot\\'s location (e.g., the kidnapped robot problem). We then utilize these techniques to implement the first online replanning scheme in belief space on a physical mobile robot that is robust to changes in the environment and large disturbances. This method demonstrates that belief space planning is a practical tool for robot motion planning.

Sampling Based Trajectory Planning for Robots in Dynamic Human Environments

DEFF Research Database (Denmark)

Svenstrup, Mikael

2010-01-01

Open-ended human environments, such as pedestrian streets, hospital corridors, train stations etc., are places where robots start to emerge. Hence, being able to plan safe and natural trajectories in these dynamic environments is an important skill for future generations of robots. In this work...... the problem is formulated as planning a minimal cost trajectory through a potential field, defined from the perceived position and motion of persons in the environment. A modified Rapidlyexploring Random Tree (RRT) algorithm is proposed as a solution to the planning problem. The algorithm implements a new...... for the uncertainty in the dynamic environment. The planning algorithm is demonstrated in a simulated pedestrian street environment....

Mobile-robot navigation with complete coverage of unstructured environments

OpenAIRE

García Armada, Elena; González de Santos, Pablo

2004-01-01

There are some mobile-robot applications that require the complete coverage of an unstructured environment. Examples are humanitarian de-mining and floor-cleaning tasks. A complete-coverage algorithm is then used, a path-planning technique that allows the robot to pass over all points in the environment, avoiding unknown obstacles. Different coverage algorithms exist, but they fail working in unstructured environments. This paper details a complete-coverage algorithm for unstructured environm...

MOVEMENT SIMULATION OF THREE ARMED ROBOT BY BEING USED AutoLISP

Directory of Open Access Journals (Sweden)

Mustafa BOZDEMİR

2000-01-01

Full Text Available Development of a suitable robot for desired aim and duty is very important for design enginers. On the other hand, designed robots may be unsuccesful in functioning inspite of many efforts. For this reason, before the production of considered robot systems, having prepared a simulation program, investigation of work field, getting done path plan and mistakes could be eliminated before robot production. In this study, movement simulation of a three armed robot has been realized by using AutoLIPS programing language which is supplied with AutoCAD. Analytical and matrix solution methods have been used in simulation equations.

Cloud-Enhanced Robotic System for Smart City Crowd Control

Directory of Open Access Journals (Sweden)

Akhlaqur Rahman

2016-12-01

Full Text Available Cloud robotics in smart cities is an emerging paradigm that enables autonomous robotic agents to communicate and collaborate with a cloud computing infrastructure. It complements the Internet of Things (IoT by creating an expanded network where robots offload data-intensive computation to the ubiquitous cloud to ensure quality of service (QoS. However, offloading for robots is significantly complex due to their unique characteristics of mobility, skill-learning, data collection, and decision-making capabilities. In this paper, a generic cloud robotics framework is proposed to realize smart city vision while taking into consideration its various complexities. Specifically, we present an integrated framework for a crowd control system where cloud-enhanced robots are deployed to perform necessary tasks. The task offloading is formulated as a constrained optimization problem capable of handling any task flow that can be characterized by a Direct Acyclic Graph (DAG. We consider two scenarios of minimizing energy and time, respectively, and develop a genetic algorithm (GA-based approach to identify the optimal task offloading decisions. The performance comparison with two benchmarks shows that our GA scheme achieves desired energy and time performance. We also show the adaptability of our algorithm by varying the values for bandwidth and movement. The results suggest their impact on offloading. Finally, we present a multi-task flow optimal path sequence problem that highlights how the robot can plan its task completion via movements that expend the minimum energy. This integrates path planning with offloading for robotics. To the best of our knowledge, this is the first attempt to evaluate cloud-based task offloading for a smart city crowd control system.

Practical indoor mobile robot navigation using hybrid maps

DEFF Research Database (Denmark)

Özkil, Ali Gürcan; Fan, Zhun; Xiao, Jizhong

2011-01-01

This paper presents a practical navigation scheme for indoor mobile robots using hybrid maps. The method makes use of metric maps for local navigation and a topological map for global path planning. Metric maps are generated as 2D occupancy grids by a range sensor to represent local information...... about partial areas. The global topological map is used to indicate the connectivity of the 'places-of-interests' in the environment and the interconnectivity of the local maps. Visual tags on the ceiling to be detected by the robot provide valuable information and contribute to reliable localization...... robot and evaluated in a hospital environment....

Locomotion Gait Planning of Climber Snake-Like Robot

Directory of Open Access Journals (Sweden)

Mohammad Nezaminia

2013-04-01

Full Text Available In this article a novel breed of snake-like climber robots has been introduced. Structure and operation of the first generation of snake-like climber robot "Marak I" has been discussed. The gait planning for two dimensional locomotion of a novel snake-like climber robot "Marak I" is presented. The types of locomotion investigated were rectilinear and wheeling gaits. The gaits of locomotion were experimented and their suitability for various applications has been mentioned. Some encountered practical problems plus solutions were addressed. Finally we found out that: the vertical motion was producing more fault than horizontal locomotion, and notably the fastest gait of locomotion was the wheeling gait

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

Institute of Scientific and Technical Information of China (English)

李伟; 陈祖舜; 等

1996-01-01

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

Path Planning Algorithms for the Adaptive Sensor Fleet

Science.gov (United States)

Stoneking, Eric; Hosler, Jeff

2005-01-01

The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.

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

Introduction of a computer-based method for automated planning of reduction paths under consideration of simulated muscular forces.

Science.gov (United States)

Buschbaum, Jan; Fremd, Rainer; Pohlemann, Tim; Kristen, Alexander

2017-08-01

Reduction is a crucial step in the surgical treatment of bone fractures. Finding an optimal path for restoring anatomical alignment is considered technically demanding because collisions as well as high forces caused by surrounding soft tissues can avoid desired reduction movements. The repetition of reduction movements leads to a trial-and-error process which causes a prolonged duration of surgery. By planning an appropriate reduction path-an optimal sequence of target-directed movements-these problems should be overcome. For this purpose, a computer-based method has been developed. Using the example of simple femoral shaft fractures, 3D models are generated out of CT images. A reposition algorithm aligns both fragments by reconstructing their broken edges. According to the criteria of a deduced planning strategy, a modified A*-algorithm searches collision-free route of minimal force from the dislocated into the computed target position. Muscular forces are considered using a musculoskeletal reduction model (OpenSim model), and bone collisions are detected by an appropriate method. Five femoral SYNBONE models were broken into different fracture classification types and were automatically reduced from ten randomly selected displaced positions. Highest mean translational and rotational error for achieving target alignment is [Formula: see text] and [Formula: see text]. Mean value and standard deviation of occurring forces are [Formula: see text] for M. tensor fasciae latae and [Formula: see text] for M. semitendinosus over all trials. These pathways are precise, collision-free, required forces are minimized, and thus regarded as optimal paths. A novel method for planning reduction paths under consideration of collisions and muscular forces is introduced. The results deliver additional knowledge for an appropriate tactical reduction procedure and can provide a basis for further navigated or robotic-assisted developments.

The research of autonomous obstacle avoidance of mobile robot based on multi-sensor integration

Science.gov (United States)

Zhao, Ming; Han, Baoling

2016-11-01

The object of this study is the bionic quadruped mobile robot. The study has proposed a system design plan for mobile robot obstacle avoidance with the binocular stereo visual sensor and the self-control 3D Lidar integrated with modified ant colony optimization path planning to realize the reconstruction of the environmental map. Because the working condition of a mobile robot is complex, the result of the 3D reconstruction with a single binocular sensor is undesirable when feature points are few and the light condition is poor. Therefore, this system integrates the stereo vision sensor blumblebee2 and the Lidar sensor together to detect the cloud information of 3D points of environmental obstacles. This paper proposes the sensor information fusion technology to rebuild the environment map. Firstly, according to the Lidar data and visual data on obstacle detection respectively, and then consider two methods respectively to detect the distribution of obstacles. Finally fusing the data to get the more complete, more accurate distribution of obstacles in the scene. Then the thesis introduces ant colony algorithm. It has analyzed advantages and disadvantages of the ant colony optimization and its formation cause deeply, and then improved the system with the help of the ant colony optimization to increase the rate of convergence and precision of the algorithm in robot path planning. Such improvements and integrations overcome the shortcomings of the ant colony optimization like involving into the local optimal solution easily, slow search speed and poor search results. This experiment deals with images and programs the motor drive under the compiling environment of Matlab and Visual Studio and establishes the visual 2.5D grid map. Finally it plans a global path for the mobile robot according to the ant colony algorithm. The feasibility and effectiveness of the system are confirmed by ROS and simulation platform of Linux.

Robust Path Planning and Feedback Design Under Stochastic Uncertainty

Science.gov (United States)

Blackmore, Lars

2008-01-01

Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.

Autonomous Navigation, Dynamic Path and Work Flow Planning in Multi-Agent Robotic Swarms

Data.gov (United States)

National Aeronautics and Space Administration — 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,...

Whole-Body Motion Planning for Humanoid Robots by Specifying Via-Points

Directory of Open Access Journals (Sweden)

ChangHyun Sung

2013-07-01

Full Text Available We design a framework about the planning of whole body motion for humanoid robots. Motion planning with various constraints is essential to success the task. In this research, we propose a motion planning method corresponding to various conditions for achieving the task. We specify some via-points to deal with the conditions for target achievement depending on various constraints. Together with certain constraints including task accomplishment, the via-point representation plays a crucial role in the optimization process of our method. Furthermore, the via-points as the optimization parameters are related to some physical conditions. We applied this method to generate the kicking motion of a humanoid robot HOAP-3. We have confirmed that the robot was able to complete the task of kicking a ball over an obstacle into a goal in addition to changing conditions of the location of a ball. These results show that the proposed motion planning method using via-point representation can increase articulation of the motion.

Elastic Stability of Concentric Tube Robots: A Stability Measure and Design Test.

Science.gov (United States)

Gilbert, Hunter B; Hendrick, Richard J; Webster, Robert J

2016-02-01

Concentric tube robots are needle-sized manipulators which have been investigated for use in minimally invasive surgeries. It was noted early in the development of these devices that elastic energy storage can lead to rapid snapping motion for designs with moderate to high tube curvatures. Substantial progress has recently been made in the concentric tube robot community in designing snap-free robots, planning stable paths, and characterizing conditions that result in snapping for specific classes of concentric tube robots. However, a general measure for how stable a given robot configuration is has yet to be proposed. In this paper, we use bifurcation and elastic stability theory to provide such a measure, as well as to produce a test for determining whether a given design is snap-free (i.e. whether snapping can occur anywhere in the unloaded robot's workspace). These results are useful in designing, planning motions for, and controlling concentric tube robots with high curvatures.

Space station automation: the role of robotics and artificial intelligence (Invited Paper)

Science.gov (United States)

Park, W. T.; Firschein, O.

1985-12-01

Automation of the space station is necessary to make more effective use of the crew, to carry out repairs that are impractical or dangerous, and to monitor and control the many space station subsystems. Intelligent robotics and expert systems play a strong role in automation, and both disciplines are highly dependent on a common artificial intelligence (Al) technology base. The AI technology base provides the reasoning and planning capabilities needed in robotic tasks, such as perception of the environment and planning a path to a goal, and in expert systems tasks, such as control of subsystems and maintenance of equipment. This paper describes automation concepts for the space station, the specific robotic and expert systems required to attain this automation, and the research and development required. It also presents an evolutionary development plan that leads to fully automatic mobile robots for servicing satellites. Finally, we indicate the sequence of demonstrations and the research and development needed to confirm the automation capabilities. We emphasize that advanced robotics requires AI, and that to advance, AI needs the "real-world" problems provided by robotics.

Energy-Aware Path Planning for UAS Persistent Sampling and Surveillance

Science.gov (United States)

Shaw-Cortez, Wenceslao

The focus of this work is to develop an energy-aware path planning algorithm that maximizes UAS endurance, while performing sampling and surveillance missions in a known, stationary wind environment. The energy-aware aspect is specifically tailored to extract energy from the wind to reduce thrust use, thereby increasing aircraft endurance. Wind energy extraction is performed by static soaring and dynamic soaring. Static soaring involves using upward wind currents to increase altitude and potential energy. Dynamic soaring involves taking advantage of wind gradients to exchange potential and kinetic energy. The path planning algorithm developed in this work uses optimization to combine these soaring trajectories with the overarching sampling and surveillance mission. The path planning algorithm uses a simplified aircraft model to tractably optimize soaring trajectories. This aircraft model is presented and along with the derivation of the equations of motion. A nonlinear program is used to create the soaring trajectories based on a given optimization problem. This optimization problem is defined using a heuristic decision tree, which defines appropriate problems given a sampling and surveillance mission and a wind model. Simulations are performed to assess the path planning algorithm. The results are used to identify properties of soaring trajectories as well as to determine what wind conditions support minimal thrust soaring. Additional results show how the path planning algorithm can be tuned between maximizing aircraft endurance and performing the sampling and surveillance mission. A means of trajectory stitching is demonstrated to show how the periodic soaring segments can be combined together to provide a full solution to an infinite/long horizon problem.

Robot Learning from Demonstration: A Task-level Planning Approach

Directory of Open Access Journals (Sweden)

Staffan Ekvall

2008-09-01

Full Text Available In this paper, we deal with the problem of learning by demonstration, task level learning and planning for robotic applications that involve object manipulation. Preprogramming robots for execution of complex domestic tasks such as setting a dinner table is of little use, since the same order of subtasks may not be conceivable in the run time due to the changed state of the world. In our approach, we aim to learn the goal of the task and use a task planner to reach the goal given different initial states of the world. For some tasks, there are underlying constraints that must be fulfille, and knowing just the final goal is not sufficient. We propose two techniques for constraint identification. In the first case, the teacher can directly instruct the system about the underlying constraints. In the second case, the constraints are identified by the robot itself based on multiple observations. The constraints are then considered in the planning phase, allowing the task to be executed without violating any of them. We evaluate our work on a real robot performing pick-and-place tasks.

Gait Planning Research for an Electrically Driven Large-Load-Ratio Six-Legged Robot

Directory of Open Access Journals (Sweden)

Hong-Chao Zhuang

2017-03-01

Full Text Available Gait planning is an important basis for the walking of a legged robot. To improve the walking stability of multi-legged robots and to reduce the impact force between the foot and the ground, gait planning strategies are presented for an electrically driven large-load-ratio six-legged robot. First, the configuration and walking gait of the electrically driven large-load-ratio six-legged robot are designed. The higher-stable swing sequences of legs and typical walking modes are respectively obtained. Based on the Denavit–Hartenberg (D–H method, the analyses of the forward and inverse kinematics are implemented. The mathematical models of the articulated rotation angles are respectively established. In view of the buffer device installed at the end of shin to decrease the impact force between the foot and the ground, an initial lift height of the leg is brought into gait planning when the support phase changes into the transfer phase. The mathematical models of foot trajectories are established. Finally, a prototype of the electrically driven large-load-ratio six-legged robot is developed. The experiments of the prototype are carried out regarding the aspects of the walking speed and surmounting obstacle. Then, the reasonableness of gait planning is verified based on the experimental results. The proposed strategies of gait planning lay the foundation for effectively reducing the foot–ground impact force and can provide a reference for other large-load-ratio multi-legged robots.

Applications of artificial intelligence to space station and automated software techniques: High level robot command language

Science.gov (United States)

Mckee, James W.

1989-01-01

The objective is to develop a system that will allow a person not necessarily skilled in the art of programming robots to quickly and naturally create the necessary data and commands to enable a robot to perform a desired task. The system will use a menu driven graphical user interface. This interface will allow the user to input data to select objects to be moved. There will be an imbedded expert system to process the knowledge about objects and the robot to determine how they are to be moved. There will be automatic path planning to avoid obstacles in the work space and to create a near optimum path. The system will contain the software to generate the required robot instructions.

Vision-based mapping with cooperative robots

Science.gov (United States)

Little, James J.; Jennings, Cullen; Murray, Don

1998-10-01

Two stereo-vision-based mobile robots navigate and autonomously explore their environment safely while building occupancy grid maps of the environment. The robots maintain position estimates within a global coordinate frame using landmark recognition. This allows them to build a common map by sharing position information and stereo data. Stereo vision processing and map updates are done at 3 Hz and the robots move at speeds of 200 cm/s. Cooperative mapping is achieved through autonomous exploration of unstructured and dynamic environments. The map is constructed conservatively, so as to be useful for collision-free path planning. Each robot maintains a separate copy of a shared map, and then posts updates to the common map when it returns to observe a landmark at home base. Issues include synchronization, mutual localization, navigation, exploration, registration of maps, merging repeated views (fusion), centralized vs decentralized maps.

Prediction of Path Deviation in Robot Based Incremental Sheet Metal Forming by Means of a New Solid-Shell Finite Element Technology and a Finite Elastoplastic Model with Combined Hardening

Science.gov (United States)

Kiliclar, Yalin; Laurischkat, Roman; Vladimirov, Ivaylo N.; Reese, Stefanie

2011-08-01

The presented project deals with a robot based incremental sheet metal forming process, which is called roboforming and has been developed at the Chair of Production Systems. It is characterized by flexible shaping using a freely programmable path-synchronous movement of two industrial robots. The final shape is produced by the incremental infeed of the forming tool in depth direction and its movement along the part contour in lateral direction. However, the resulting geometries formed in roboforming deviate several millimeters from the reference geometry. This results from the compliance of the involved machine structures and the springback effects of the workpiece. The project aims to predict these deviations caused by resiliences and to carry out a compensative path planning based on this prediction. Therefore a planning tool is implemented which compensates the robots's compliance and the springback effects of the sheet metal. The forming process is simulated by means of a finite element analysis using a material model developed at the Institute of Applied Mechanics (IFAM). It is based on the multiplicative split of the deformation gradient in the context of hyperelasticity and combines nonlinear kinematic and isotropic hardening. Low-order finite elements used to simulate thin sheet structures, such as used for the experiments, have the major problem of locking, a nonphysical stiffening effect. For an efficient finite element analysis a special solid-shell finite element formulation based on reduced integration with hourglass stabilization has been developed. To circumvent different locking effects, the enhanced assumed strain (EAS) and the assumed natural strain (ANS) concepts are included in this formulation. Having such powerful tools available we obtain more accurate geometries.

A Reactive Robot Architecture With Planning on Demand

National Research Council Canada - National Science Library

Ranganathan, Ananth; Koenig, Sven

2003-01-01

In this paper, we describe a reactive robot architecture that uses fast re-planning methods to avoid the shortcomings of reactive navigation, such as getting stuck in box canyons or in front of small openings...

On the reproducibility of expert-operated and robotic ultrasound acquisitions.

Science.gov (United States)

Kojcev, Risto; Khakzar, Ashkan; Fuerst, Bernhard; Zettinig, Oliver; Fahkry, Carole; DeJong, Robert; Richmon, Jeremy; Taylor, Russell; Sinibaldi, Edoardo; Navab, Nassir

2017-06-01

We present the evaluation of the reproducibility of measurements performed using robotic ultrasound imaging in comparison with expert-operated sonography. Robotic imaging for interventional procedures may be a valuable contribution, but requires reproducibility for its acceptance in clinical routine. We study this by comparing repeated measurements based on robotic and expert-operated ultrasound imaging. Robotic ultrasound acquisition is performed in three steps under user guidance: First, the patient is observed using a 3D camera on the robot end effector, and the user selects the region of interest. This allows for automatic planning of the robot trajectory. Next, the robot executes a sweeping motion following the planned trajectory, during which the ultrasound images and tracking data are recorded. As the robot is compliant, deviations from the path are possible, for instance due to patient motion. Finally, the ultrasound slices are compounded to create a volume. Repeated acquisitions can be performed automatically by comparing the previous and current patient surface. After repeated image acquisitions, the measurements based on acquisitions performed by the robotic system and expert are compared. Within our case series, the expert measured the anterior-posterior, longitudinal, transversal lengths of both of the left and right thyroid lobes on each of the 4 healthy volunteers 3 times, providing 72 measurements. Subsequently, the same procedure was performed using the robotic system resulting in a cumulative total of 144 clinically relevant measurements. Our results clearly indicated that robotic ultrasound enables more repeatable measurements. A robotic ultrasound platform leads to more reproducible data, which is of crucial importance for planning and executing interventions.

Aircraft path planning for optimal imaging using dynamic cost functions

Science.gov (United States)

Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

2015-05-01

Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

Space station automation and robotics study. Operator-systems interface

Science.gov (United States)

1984-01-01

This is the final report of a Space Station Automation and Robotics Planning Study, which was a joint project of the Boeing Aerospace Company, Boeing Commercial Airplane Company, and Boeing Computer Services Company. The study is in support of the Advanced Technology Advisory Committee established by NASA in accordance with a mandate by the U.S. Congress. Boeing support complements that provided to the NASA Contractor study team by four aerospace contractors, the Stanford Research Institute (SRI), and the California Space Institute. This study identifies automation and robotics (A&R) technologies that can be advanced by requirements levied by the Space Station Program. The methodology used in the study is to establish functional requirements for the operator system interface (OSI), establish the technologies needed to meet these requirements, and to forecast the availability of these technologies. The OSI would perform path planning, tracking and control, object recognition, fault detection and correction, and plan modifications in connection with extravehicular (EV) robot operations.

An Approximation Approach for Solving the Subpath Planning Problem

OpenAIRE

Safilian, Masoud; Tashakkori, S. Mehdi; Eghbali, Sepehr; Safilian, Aliakbar

2016-01-01

The subpath planning problem is a branch of the path planning problem, which has widespread applications in automated manufacturing process as well as vehicle and robot navigation. This problem is to find the shortest path or tour subject for travelling a set of given subpaths. The current approaches for dealing with the subpath planning problem are all based on meta-heuristic approaches. It is well-known that meta-heuristic based approaches have several deficiencies. To address them, we prop...

Real-Time Motion Planning and Safe Navigation in Dynamic Multi-Robot Environments

National Research Council Canada - National Science Library

Bruce, James R

2006-01-01

.... While motion planning has been used for high level robot navigation, or limited to semi-static or single-robot domains, it has often been dismissed for the real-time low-level control of agents due...

Artificial intelligence planning applications for space exploration and space robotics

Science.gov (United States)

Rokey, Mark; Grenander, Sven

1986-01-01

Mission sequencing involves the plan for actuation of the experiments to be conducted aboard a spacecraft; automation is under study by NASA as a means to reduce time and manpower costs in mission planning and in robotic implementation. The development of a mission sequence is conditioned by the limited duration of advantageous spacecraft encounters with objects of study, more research requests than can be satisfied, and requested changes in objectives. Autonomous robot development is hampered by the absence of task-level programming languages, the existence of anomalies in real-world interactions, and a lack of required capabilities in current sensor technology.

Shore-based Path Planning for Marine Vehicles Using a Model of Ocean Currents

Data.gov (United States)

National Aeronautics and Space Administration — Develop path planning methods that incorporate an approximate model of ocean currents in path planning for a range of autonomous marine vehicles such as surface...

A Hybrid 3D Path Planning Method for UAVs

DEFF Research Database (Denmark)

Ortiz-Arroyo, Daniel

2015-01-01

This paper presents a hybrid method for path planning in 3D spaces. We propose an improvement to a near-optimal 2D off-line algorithm and a flexible normalized on-line fuzzy controller to find shortest paths. Our method, targeted to low altitude domains, is simple and efficient. Our preliminary resu...

Multi-agent System for Off-line Coordinated Motion Planning of Multiple Industrial Robots

Directory of Open Access Journals (Sweden)

Shital S. Chiddarwar

2011-03-01

Full Text Available This article presents an agent based framework for coordinated motion planning of multiple robots. The emerging paradigm of agent based systems is implemented to address various issues related to safe and fast task execution when multiple robots share a common workspace. In the proposed agent based framework, each issue vital for coordinated motion planning of multiple robots and every robot participating in coordinated task is considered as an agent. The identified agents are interfaced with each other in order to incorporate the desired flexibility in the developed framework. This framework gives a complete strategy for determination of optimal trajectories of robots working in coordination with due consideration to their kinematic, dynamic and payload constraint. The complete architecture of the proposed framework and the detailed discussion on various modules are covered in this paper.

Cooperative path planning for multi-USV based on improved artificial bee colony algorithm

Science.gov (United States)

Cao, Lu; Chen, Qiwei

2018-03-01

Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.

Automatic control of a robotic vehicle

Science.gov (United States)

Mcreynolds, S. R.

1976-01-01

Over the last several years Jet Propulsion Laboratory has been engaged in a project to develop some of the technology required to build a robotic vehicle for exploring planetary surfaces. An overview of hardware and software being developed for this project is given. Particular emphasis is placed on the description of the current design for the Vehicle System required for locomotion and the path planning algorithm.

A hybrid metaheuristic DE/CS algorithm for UCAV three-dimension path planning.

Science.gov (United States)

Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen

2012-01-01

Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.

“Robots in Space” Multiagent Problem: Complexity, Information and Cryptographic Aspects

Directory of Open Access Journals (Sweden)

A. Yu. Bernstein

2013-01-01

Full Text Available We study a multiagent algorithmic problem that we call Robot in Space (RinS: There are n ≥ 2 autonomous robots, that need to agree without outside interference on distribution of shelters, so that straight pathes to the shelters will not intersect. The problem is closely related to the assignment problem in Graph Theory, to the convex hull problem in Combinatorial Geometry, or to the path-planning problem in Artificial Intelligence. Our algorithm grew up from a local search solution of the problem suggested by E.W. Dijkstra. We present a multiagent anonymous and scalable algorithm (protocol solving the problem, give an upper bound for the algorithm, prove (manually its correctness, and examine two communication aspects of the RinS problem — the informational and cryptographic. We proved that (1 there is no protocol that solves the RinS, which transfers a bounded number of bits, and (2 suggested the protocol that allows robots to check whether their paths intersect, without revealing additional information about their relative positions (with respect to shelters. The present paper continues the research presented in Mars Robot Puzzle (a Multiagent Approach to the Dijkstra Problem (by E.V. Bodin, N.O. Garanina, and N.V. Shilov, published in Modeling and analysis of information systems, 18(2, 2011.

Characterization Of Robot Work Cell

Science.gov (United States)

Anderson, Ronald R.; Paternoster, Vincent Y.; Guthmiller, Wayne A.

1990-01-01

Iterative process of measurement and computation used to characterize work cell of robot, increasing accuracy of mathematical model of work cell. Characterization needed because model used in off-line programming (OLP) to compute paths to control motion of robot. Increases accuracies of model and paths.

A neural network-based exploratory learning and motor planning system for co-robots

Directory of Open Access Journals (Sweden)

Byron V Galbraith

2015-07-01

Full Text Available Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or learning by doing, an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

A neural network-based exploratory learning and motor planning system for co-robots.

Science.gov (United States)

Galbraith, Byron V; Guenther, Frank H; Versace, Massimiliano

2015-01-01

Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or "learning by doing," an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

Research on Navigation Path Planning for An Underground Load Haul Dump

Directory of Open Access Journals (Sweden)

Qi Yulong

2015-11-01

Full Text Available The improved A * algorithm is a method of navigation path planning for articulated underground scrapers. Firstly, an environment model based on a mining Geographic Information System (GIS map is established, and then combined with improved A * algorithm, the underground global path planning problem of the intelligent Load Haul Dump (LHD is solved. In this paper, for the articulated structure, the method of expanding nodes by articulation angle is adopted to make expanded nodes meet the trajectory characteristics. In addition, collision threat cost is introduced in the evaluation function to avoid collisions between the LHD and the tunnel walls. As peran analysis of the simulation test to verify the effectiveness of the improved A * algorithm and a comparison with the traditional A * algorithm, the improved A * algorithm can enhance search efficiency. Acontrast of multiple sets of test parameters suggests that when the price weighted coefficient of collision is 0.2, the shortest path can be derived to avoid impact. Finally, tracking results indicate that the proposed algorithm for navigation path planning can maintain the tracking error to within 0.2 m in line with the structural characteristics of the scraper in the laboratory environment to realize the path planning of unmanned scrapers and trajectory tracking. Moreover, the algorithm can enhance the safety of scrapers and prevent roadway collisions. The feasibility and practicality of the proposed method is verified in this work.

Three-Dimensional Path Planning Software-Assisted Transjugular Intrahepatic Portosystemic Shunt: A Technical Modification

Energy Technology Data Exchange (ETDEWEB)

Tsauo, Jiaywei, E-mail: 80732059@qq.com; Luo, Xuefeng, E-mail: luobo-913@126.com [West China Hospital of Sichuan University, Institute of Interventional Radiology (China); Ye, Linchao, E-mail: linchao.ye@siemens.com [Siemens Ltd, Healthcare Sector (China); Li, Xiao, E-mail: simonlixiao@gmail.com [West China Hospital of Sichuan University, Institute of Interventional Radiology (China)

2015-06-15

PurposeThis study was designed to report our results with a modified technique of three-dimensional (3D) path planning software assisted transjugular intrahepatic portosystemic shunt (TIPS).Methods3D path planning software was recently developed to facilitate TIPS creation by using two carbon dioxide portograms acquired at least 20° apart to generate a 3D path for overlay needle guidance. However, one shortcoming is that puncturing along the overlay would be technically impossible if the angle of the liver access set and the angle of the 3D path are not the same. To solve this problem, a prototype 3D path planning software was fitted with a utility to calculate the angle of the 3D path. Using this, we modified the angle of the liver access set accordingly during the procedure in ten patients.ResultsFailure for technical reasons occurred in three patients (unsuccessful wedged hepatic venography in two cases, software technical failure in one case). The procedure was successful in the remaining seven patients, and only one needle pass was required to obtain portal vein access in each case. The course of puncture was comparable to the 3D path in all patients. No procedure-related complication occurred following the procedures.ConclusionsAdjusting the angle of the liver access set to match the angle of the 3D path determined by the software appears to be a favorable modification to the technique of 3D path planning software assisted TIPS.

Evolutionistic or revolutionary paths? A PACS maturity model for strategic situational planning.

Science.gov (United States)

van de Wetering, Rogier; Batenburg, Ronald; Lederman, Reeva

2010-07-01

While many hospitals are re-evaluating their current Picture Archiving and Communication System (PACS), few have a mature strategy for PACS deployment. Furthermore, strategies for implementation, strategic and situational planning methods for the evolution of PACS maturity are scarce in the scientific literature. Consequently, in this paper we propose a strategic planning method for PACS deployment. This method builds upon a PACS maturity model (PMM), based on the elaboration of the strategic alignment concept and the maturity growth path concept previously developed in the PACS domain. First, we review the literature on strategic planning for information systems and information technology and PACS maturity. Secondly, the PMM is extended by applying four different strategic perspectives of the Strategic Alignment Framework whereupon two types of growth paths (evolutionistic and revolutionary) are applied that focus on a roadmap for PMM. This roadmap builds a path to get from one level of maturity and evolve to the next. An extended method for PACS strategic planning is developed. This method defines eight distinctive strategies for PACS strategic situational planning that allow decision-makers in hospitals to decide which approach best suits their hospitals' current situation and future ambition and what in principle is needed to evolve through the different maturity levels. The proposed method allows hospitals to strategically plan for PACS maturation. It is situational in that the required investments and activities depend on the alignment between the hospital strategy and the selected growth path. The inclusion of both strategic alignment and maturity growth path concepts make the planning method rigorous, and provide a framework for further empirical research and clinical practice.

Image-based path planning for automated virtual colonoscopy navigation

Science.gov (United States)

Hong, Wei

2008-03-01

Virtual colonoscopy (VC) is a noninvasive method for colonic polyp screening, by reconstructing three-dimensional models of the colon using computerized tomography (CT). In virtual colonoscopy fly-through navigation, it is crucial to generate an optimal camera path for efficient clinical examination. In conventional methods, the centerline of the colon lumen is usually used as the camera path. In order to extract colon centerline, some time consuming pre-processing algorithms must be performed before the fly-through navigation, such as colon segmentation, distance transformation, or topological thinning. In this paper, we present an efficient image-based path planning algorithm for automated virtual colonoscopy fly-through navigation without the requirement of any pre-processing. Our algorithm only needs the physician to provide a seed point as the starting camera position using 2D axial CT images. A wide angle fisheye camera model is used to generate a depth image from the current camera position. Two types of navigational landmarks, safe regions and target regions are extracted from the depth images. Camera position and its corresponding view direction are then determined using these landmarks. The experimental results show that the generated paths are accurate and increase the user comfort during the fly-through navigation. Moreover, because of the efficiency of our path planning algorithm and rendering algorithm, our VC fly-through navigation system can still guarantee 30 FPS.

Global optimal path planning of an autonomous vehicle for overtaking a moving obstacle

Directory of Open Access Journals (Sweden)

B. Mashadi

Full Text Available In this paper, the global optimal path planning of an autonomous vehicle for overtaking a moving obstacle is proposed. In this study, the autonomous vehicle overtakes a moving vehicle by performing a double lane-change maneuver after detecting it in a proper distance ahead. The optimal path of vehicle for performing the lane-change maneuver is generated by a path planning program in which the sum of lateral deviation of the vehicle from a reference path and the rate of steering angle become minimum while the lateral acceleration of vehicle does not exceed a safe limit value. A nonlinear optimal control theory with the lateral vehicle dynamics equations and inequality constraint of lateral acceleration are used to generate the path. The indirect approach for solving the optimal control problem is used by applying the calculus of variation and the Pontryagin's Minimum Principle to obtain first-order necessary conditions for optimality. The optimal path is generated as a global optimal solution and can be used as the benchmark of the path generated by the local motion planning of autonomous vehicles. A full nonlinear vehicle model in CarSim software is used for path following simulation by importing path data from the MATLAB code. The simulation results show that the generated path for the autonomous vehicle satisfies all vehicle dynamics constraints and hence is a suitable overtaking path for the following vehicle.

PAIR'14 / PAIR'15 STUDENT CONFERENCES ON PLANNING IN ARTIFICIAL INTELLIGENCE AND ROBOTICS

Directory of Open Access Journals (Sweden)

Editorial Foreword

2015-12-01

Full Text Available Dear Readerthe original idea of the student conference on “Planning in Artificial Intelligence and Robotics” (PAIR is to join young researchers from particular laboratories in Czech Republic, where planning problems are investigated from artificial intelligence (AI or robotics points of view. The first year of PAIR has been organized at the Dept. of Computer Science, Faculty Electrical Engineering, Czech Technical University in 2014.At PAIR 2014, laboratories from Prague and Brno were presented. In particular, students and researchers from Charles University, Czech Technical University in Prague, Brno University of Technology, and Central European Institute of Technology participated at the event. Beside an introduction of the particular research groups and their topics, students presented contributions on their current research results. Ten papers were presented on topics ranging from domain–independent planning, trajectory planning to applications for unmanned aerial and legged robots. This first event provides us an initial experience with the community of young researchers in Czech Republic that are working planning in robotic or AI. Based on the success of PAIR 2014, we decided to continue with our effort to establish a suitable fora for students that are geographically very close, but usually do not meet, because of participation on different Robotics and AI events.The second student conference on Planning in Artificial Intelligence and Robotics (PAIR 2015 successfully continues the tradition of the first year of the conference organized in Prague. This year, the conference was collocated with 10th anniversary of RoboTour contest in Písek. This format enable us to extend the impact of the PAIR conference and improve the visibility of the growing student community. The conference reached a good amount of interesting papers focused on image processing for mobile robots, swarm control, driving simulation, robot control, or domain�

Analysis of construction dynamic plan using fuzzy critical path method

Directory of Open Access Journals (Sweden)

Kurij Kazimir V.

2014-01-01

Full Text Available Critical Path Method (CPM technique has become widely recognized as valuable tool for the planning and scheduling large construction projects. The aim of this paper is to present an analytical method for finding the Critical Path in the precedence network diagram where the duration of each activity is represented by a trapezoidal fuzzy number. This Fuzzy Critical Path Method (FCPM uses a defuzzification formula for trapezoidal fuzzy number and applies it on the total float (slack time for each activity in the fuzzy precedence network to find the critical path. The method presented in this paper is very effective in determining the critical activities and finding the critical paths.

PLANNING IN ARTIFICIAL INTELLIGENCE AND ROBOTICS (PAIR

Directory of Open Access Journals (Sweden)

Editorial, Foreword

2016-11-01

Full Text Available September 18th, 2016Deggendorf, Germanyhttp://robotics.fel.cvut.cz/pair16/Organized by: Artificial Intelligence Center Department of Computer Science Faculty of Electrical Engineering Czech Technical University in PragueTechnicka 2, Prague 6, 166 27, Czech RepublicGuest editors:Jan Faigl (Artificial Intelligence Center, Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University in PragueJiří Vokřínek (Artificial Intelligence Center, Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University in PragueScientific comittee:D. Belter (Poznań University of Technology, PolandW. Dorner (Technische Hochschule Deggendorf, GermanyJ. Faigl (Czech Technical University in PragueT. Krajník (University of Lincoln, United KingdomA. Komenda (Czech Technical University in PragueG. Kupris (Technische Hochschule Deggendorf, GermanyM. Rollo (Czech Technical University in PragueM. Saska (Czech Technical University in PragueJ. Vokřínek (Czech Technical University in PragueV. Vonásek (Czech Technical University in PragueK. Walas (Poznań University of Technology, Poland Foreword:The third year of the student conference on “Planning in Artificial Intelligence and Robotics” (PAIR continues in joining young researchers and students interested in robotics and artificial intelligence. In 2016, we follow the schema of the last year as a joint event with the RoboTour competition in Deggendorf, Germany. Thanks to the great collaboration with Gerald Kupris and Wolfgang Donner from Technische Hochschule Deggendorf and support from Czech Technical University under project No. SVK 26/16/F3 and Bayerisches Staatsministerium der Finanzen, für Landesentwicklung und Heimat, we have been able to provide accommodations and travel support to participants and an invited speaker. Fourteen papers have accepted and listed in the conference program. The papers have been authored by students from Central Europe

Path Planning Method for UUV Homing and Docking in Movement Disorders Environment

Directory of Open Access Journals (Sweden)

Zheping Yan

2014-01-01

Full Text Available Path planning method for unmanned underwater vehicles (UUV homing and docking in movement disorders environment is proposed in this paper. Firstly, cost function is proposed for path planning. Then, a novel particle swarm optimization (NPSO is proposed and applied to find the waypoint with minimum value of cost function. Then, a strategy for UUV enters into the mother vessel with a fixed angle being proposed. Finally, the test function is introduced to analyze the performance of NPSO and compare with basic particle swarm optimization (BPSO, inertia weight particle swarm optimization (LWPSO, EPSO, and time-varying acceleration coefficient (TVAC. It has turned out that, for unimodal functions, NPSO performed better searching accuracy and stability than other algorithms, and, for multimodal functions, the performance of NPSO is similar to TVAC. Then, the simulation of UUV path planning is presented, and it showed that, with the strategy proposed in this paper, UUV can dodge obstacles and threats, and search for the efficiency path.

Trajectory planning and optimal tracking for an industrial mobile robot

Science.gov (United States)

Hu, Huosheng; Brady, J. Michael; Probert, Penelope J.

1994-02-01

This paper introduces a unified approach to trajectory planning and tracking for an industrial mobile robot subject to non-holonomic constraints. We show (1) how a smooth trajectory is generated that takes into account the constraints from the dynamic environment and the robot kinematics; and (2) how a general predictive controller works to provide optimal tracking capability for nonlinear systems. The tracking performance of the proposed guidance system is analyzed by simulation.

Robotics virtual rail system and method

Science.gov (United States)

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

2011-07-05

A virtual track or rail system and method is described for execution by a robot. A user, through a user interface, generates a desired path comprised of at least one segment representative of the virtual track for the robot. Start and end points are assigned to the desired path and velocities are also associated with each of the at least one segment of the desired path. A waypoint file is generated including positions along the virtual track representing the desired path with the positions beginning from the start point to the end point including the velocities of each of the at least one segment. The waypoint file is sent to the robot for traversing along the virtual track.

Calibration and control for range imaging in mobile robot navigation

Energy Technology Data Exchange (ETDEWEB)

Dorum, O.H. [Norges Tekniske Hoegskole, Trondheim (Norway). Div. of Computer Systems and Telematics; Hoover, A. [University of South Florida, Tampa, FL (United States). Dept. of Computer Science and Engineering; Jones, J.P. [Oak Ridge National Lab., TN (United States)

1994-06-01

This paper addresses some issues in the development of sensor-based systems for mobile robot navigation which use range imaging sensors as the primary source for geometric information about the environment. In particular, we describe a model of scanning laser range cameras which takes into account the properties of the mechanical system responsible for image formation and a calibration procedure which yields improved accuracy over previous models. In addition, we describe an algorithm which takes the limitations of these sensors into account in path planning and path execution. In particular, range imaging sensors are characterized by a limited field of view and a standoff distance -- a minimum distance nearer than which surfaces cannot be sensed. These limitations can be addressed by enriching the concept of configuration space to include information about what can be sensed from a given configuration, and using this information to guide path planning and path following.

Robotic and artificial intelligence for keyhole neurosurgery: the ROBOCAST project, a multi-modal autonomous path planner.

Science.gov (United States)

De Momi, E; Ferrigno, G

2010-01-01

The robot and sensors integration for computer-assisted surgery and therapy (ROBOCAST) project (FP7-ICT-2007-215190) is co-funded by the European Union within the Seventh Framework Programme in the field of information and communication technologies. The ROBOCAST project focuses on robot- and artificial-intelligence-assisted keyhole neurosurgery (tumour biopsy and local drug delivery along straight or turning paths). The goal of this project is to assist surgeons with a robotic system controlled by an intelligent high-level controller (HLC) able to gather and integrate information from the surgeon, from diagnostic images, and from an array of on-field sensors. The HLC integrates pre-operative and intra-operative diagnostics data and measurements, intelligence augmentation, multiple-robot dexterity, and multiple sensory inputs in a closed-loop cooperating scheme including a smart interface for improved haptic immersion and integration. This paper, after the overall architecture description, focuses on the intelligent trajectory planner based on risk estimation and human criticism. The current status of development is reported, and first tests on the planner are shown by using a real image stack and risk descriptor phantom. The advantages of using a fuzzy risk description are given by the possibility of upgrading the knowledge on-field without the intervention of a knowledge engineer.

System Design and Implementation of Intelligent Fire Engine Path Planning based on SAT Algorithm

Institute of Scientific and Technical Information of China (English)

CAI Li-sha[1; ZENG Wei-peng[1; HAN Bao-ru[1

2016-01-01

In this paper, in order to make intelligent fi re car complete autonomy path planning in simulation map. Proposed system design of intelligent fi re car path planning based on SAT. The system includes a planning module, a communication module, a control module. Control module via the communication module upload the initial state and the goal state to planning module. Planning module solve this planning solution,and then download planning solution to control module, control the movement of the car fi re. Experiments show this the system is tracking short time, higher planning effi ciency.

An ultrasonic sensor controller for mapping and servo control in robotic systems

International Nuclear Information System (INIS)

Drotning, W.D.; Garcia, P. Jr.

1993-03-01

An ultrasonic sensor controller has been developed and applied in a variety of robotic systems for operation in hazardous environments. The controller consists of hardware and software that control multiple ultrasonic range sensors and provide workspace information to robot controllers for rapid, safe, and reliable operation in hazardous and remote environments. The hardware consists of a programmable multichannel controller that resides on a VMEbus for high speed communication to a multiprocessor architecture. The sensor controller has been used in a number of applications, which include providing high precision range information for proximity servo control of robots, and performing surface and obstacle mapping functions for safe path planning of robots in unstructured environments

Multi Robot Path Planning for Budgeted Active Perception with Self-Organising Maps

Science.gov (United States)

2016-10-04

5], [6], [7], but the formulations have been limited to restricted cases, such as a single object or a constrained action space. Little attention has...solution paths. Object parts are shown in the coloured point clouds. Viewpoint regions are coloured black (low reward), orange (medium) and yellow (high

Autonomous mobile robot for radiologic surveys

International Nuclear Information System (INIS)

Dudar, A.M.; Wagner, D.G.; Teese, G.D.

1994-01-01

An apparatus is described for conducting radiologic surveys. The apparatus comprises in the main a robot capable of following a preprogrammed path through an area, a radiation monitor adapted to receive input from a radiation detector assembly, ultrasonic transducers for navigation and collision avoidance, and an on-board computer system including an integrator for interfacing the radiation monitor and the robot. Front and rear bumpers are attached to the robot by bumper mounts. The robot may be equipped with memory boards for the collection and storage of radiation survey information. The on-board computer system is connected to a remote host computer via a UHF radio link. The apparatus is powered by a rechargeable 24-volt DC battery, and is stored at a docking station when not in use and/or for recharging. A remote host computer contains a stored database defining paths between points in the area where the robot is to operate, including but not limited to the locations of walls, doors, stationary furniture and equipment, and sonic markers if used. When a program consisting of a series of paths is downloaded to the on-board computer system, the robot conducts a floor survey autonomously at any preselected rate. When the radiation monitor detects contamination, the robot resurveys the area at reduced speed and resumes its preprogrammed path if the contamination is not confirmed. If the contamination is confirmed, the robot stops and sounds an alarm. 5 figures

Research and development at ORNL/CESAR towards cooperating robotic systems for hazardous environments

International Nuclear Information System (INIS)

Mann, R.C.; Fujimura, K.; Unseren, M.A.

1991-01-01

One of the frontiers in intelligent machine research is the understanding of how constructive cooperation among multiple autonomous agents can be effected. The effort at the Center for Engineering Systems Advanced Research (CESAR)at the Oak Ridge National Laboratory (ORNL) focuses on two problem areas: (1) cooperation by multiple mobile robots in dynamic, incompletely known environments; and (2) cooperating robotic manipulators. Particular emphasis is placed on experimental evaluation of research and developments using the CESAR robot system testbeds, including three mobile robots, and a seven-axis, kinematically redundant mobile manipulator. This paper summarizes initial results of research addressing the decoupling of position and force control for two manipulators holding a common object, and the path planning for multiple robots in a common workspace. 15 refs., 3 figs

Research and application of genetic algorithm in path planning of logistics distribution vehicle

Science.gov (United States)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.

Robotics Potential Fields

Directory of Open Access Journals (Sweden)

Jordi Lucero

2009-01-01

Full Text Available This problem was to calculate the path a robot would take to navigate an obstacle field and get to its goal. Three obstacles were given as negative potential fields which the robot avoided, and a goal was given a positive potential field that attracted the robot. The robot decided each step based on its distance, angle, and influence from every object. After each step, the robot recalculated and determined its next step until it reached its goal. The robot's calculations and steps were simulated with Microsoft Excel.

Trajectory Optimization of Spray Painting Robot for Complex Curved Surface Based on Exponential Mean Bézier Method

Directory of Open Access Journals (Sweden)

Wei Chen

2017-01-01

Full Text Available Automated tool trajectory planning for spray painting robots is still a challenging problem, especially for a large complex curved surface. This paper presents a new method of trajectory optimization for spray painting robot based on exponential mean Bézier method. The definition and the three theorems of exponential mean Bézier curves are discussed. Then a spatial painting path generation method based on exponential mean Bézier curves is developed. A new simple algorithm for trajectory optimization on complex curved surfaces is introduced. A golden section method is adopted to calculate the values. The experimental results illustrate that the exponential mean Bézier curves enhanced flexibility of the path planning, and the trajectory optimization algorithm achieved satisfactory performance. This method can also be extended to other applications.

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

Science.gov (United States)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

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...

Performance comparison of novel WNN approach with RBFNN in navigation of autonomous mobile robotic agent

Directory of Open Access Journals (Sweden)

Ghosh Saradindu

2016-01-01

Full Text Available This paper addresses the performance comparison of Radial Basis Function Neural Network (RBFNN with novel Wavelet Neural Network (WNN of designing intelligent controllers for path planning of mobile robot in an unknown environment. In the proposed WNN, different types of activation functions such as Mexican Hat, Gaussian and Morlet wavelet functions are used in the hidden nodes. The neural networks are trained by an intelligent supervised learning technique so that the robot makes a collision-free path in the unknown environment during navigation from different starting points to targets/goals. The efficiency of two algorithms is compared using some MATLAB simulations and experimental setup with Arduino Mega 2560 microcontroller in terms of path length and time taken to reach the target as an indicator for the accuracy of the network models.

Efficient Symbolic Task Planning for Multiple Mobile Robots

Science.gov (United States)

2016-12-13

shows a map of the testing environment. S1 and S2 ( green rectangles) are the initial positions of two robots, and G1 and G2 (red ellipses) show their...intelligence, pages 1594–1597. AAAI Press, 2008. [25] Mausam and D. S. Weld . Planning with durative actions in stochastic domains. J. Artif. Intell. Res...JAIR), 31:33–82, 2008. [26] D. McDermott, M. Ghallab, A. Howe, C. Knoblock, A. Ram, M. Veloso, D. Weld , and D. Wilkins. Pddl-the planning domain

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot.

Science.gov (United States)

Bengochea-Guevara, José M; Conesa-Muñoz, Jesus; Andújar, Dionisio; Ribeiro, Angela

2016-02-24

The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal cost. In this study, a small autonomous field inspection vehicle was developed to minimise the impact of the scouting on the crop and soil compaction. The proposed approach integrates a camera with a GPS receiver to obtain a set of basic behaviours required of an autonomous mobile robot to inspect a crop field with full coverage. A path planner considered the field contour and the crop type to determine the best inspection route. An image-processing method capable of extracting the central crop row under uncontrolled lighting conditions in real time from images acquired with a reflex camera positioned on the front of the robot was developed. Two fuzzy controllers were also designed and developed to achieve vision-guided navigation. A method for detecting the end of a crop row using camera-acquired images was developed. In addition, manoeuvres necessary for the robot to change rows were established. These manoeuvres enabled the robot to autonomously cover the entire crop by following a previously established plan and without stepping on the crop row, which is an essential behaviour for covering crops such as maize without damaging them.

Kinematic simulation and analysis of robot based on MATLAB

Science.gov (United States)

Liao, Shuhua; Li, Jiong

2018-03-01

The history of industrial automation is characterized by quick update technology, however, without a doubt, the industrial robot is a kind of special equipment. With the help of MATLAB matrix and drawing capacity in the MATLAB environment each link coordinate system set up by using the d-h parameters method and equation of motion of the structure. Robotics, Toolbox programming Toolbox and GUIDE to the joint application is the analysis of inverse kinematics and path planning and simulation, preliminary solve the problem of college students the car mechanical arm positioning theory, so as to achieve the aim of reservation.

Improved robotic stereotactic body radiation therapy plan quality and planning efficacy for organ-confined prostate cancer utilizing overlap-volume histogram-driven planning methodology

International Nuclear Information System (INIS)

Wu, Binbin; Pang, Dalong; Lei, Siyuan; Gatti, John; Tong, Michael; McNutt, Todd; Kole, Thomas; Dritschilo, Anatoly; Collins, Sean

2014-01-01

Background and purpose: This study is to determine if the overlap-volume histogram (OVH)-driven planning methodology can be adapted to robotic SBRT (CyberKnife Robotic Radiosurgery System) to further minimize the bladder and rectal doses achieved in plans manually-created by clinical planners. Methods and materials: A database containing clinically-delivered, robotic SBRT plans (7.25 Gy/fraction in 36.25 Gy) of 425 patients with localized prostate cancer was used as a cohort to establish an organ’s distance-to-dose model. The OVH-driven planning methodology was refined by adding the PTV volume factor to counter the target’s dose fall-off effect and incorporated into Multiplan to automate SBRT planning. For validation, automated plans (APs) for 12 new patients were generated, and their achieved dose/volume values were compared to the corresponding manually-created, clinically-delivered plans (CPs). A two-sided, Wilcoxon rank-sum test was used for statistical comparison with a significance level of p < 0.05. Results: PTV’s V(36.25 Gy) was comparable: 95.6% in CPs comparing to 95.1% in APs (p = 0.2). On average, the refined approach lowered V(18.12 Gy) to the bladder and rectum by 8.2% (p < 0.05) and 6.4% (p = 0.14). A physician confirmed APs were clinically acceptable. Conclusions: The improvements in APs could further reduce toxicities observed in SBRT for organ-confined prostate cancer

Towards Autonomous Operations of the Robonaut 2 Humanoid Robotic Testbed

Science.gov (United States)

Badger, Julia; Nguyen, Vienny; Mehling, Joshua; Hambuchen, Kimberly; Diftler, Myron; Luna, Ryan; Baker, William; Joyce, Charles

2016-01-01

The Robonaut project has been conducting research in robotics technology on board the International Space Station (ISS) since 2012. Recently, the original upper body humanoid robot was upgraded by the addition of two climbing manipulators ("legs"), more capable processors, and new sensors, as shown in Figure 1. While Robonaut 2 (R2) has been working through checkout exercises on orbit following the upgrade, technology development on the ground has continued to advance. Through the Active Reduced Gravity Offload System (ARGOS), the Robonaut team has been able to develop technologies that will enable full operation of the robotic testbed on orbit using similar robots located at the Johnson Space Center. Once these technologies have been vetted in this way, they will be implemented and tested on the R2 unit on board the ISS. The goal of this work is to create a fully-featured robotics research platform on board the ISS to increase the technology readiness level of technologies that will aid in future exploration missions. Technology development has thus far followed two main paths, autonomous climbing and efficient tool manipulation. Central to both technologies has been the incorporation of a human robotic interaction paradigm that involves the visualization of sensory and pre-planned command data with models of the robot and its environment. Figure 2 shows screenshots of these interactive tools, built in rviz, that are used to develop and implement these technologies on R2. Robonaut 2 is designed to move along the handrails and seat track around the US lab inside the ISS. This is difficult for many reasons, namely the environment is cluttered and constrained, the robot has many degrees of freedom (DOF) it can utilize for climbing, and remote commanding for precision tasks such as grasping handrails is time-consuming and difficult. Because of this, it is important to develop the technologies needed to allow the robot to reach operator-specified positions as

A study on optimal motion for a robot manipulator amid obstacles

International Nuclear Information System (INIS)

Park, Jong Keun

1997-01-01

Optimal motion for a robot manipulator is obtained by nonlinear programming. The objective of optimal motion is minimizing energy consumption of manipulator arm with fixed traveling time in the presence of obstacles. The geometric path is not predetermined. The total trajectory is described in terms of cubic B-spline polynomials and the coefficients of them are obtained to minimize a specific performance index. Obstacle avoidance is performed by the method that the square sum of penetration growth distances between every obstacles and robot links is included in the performance index with appropriate weighting coefficient. In all examples tested here, the solutions were converged to unique optimal trajectories from different initial ones. The optimal geometric path obtained in this research can be used in minimum time trajectory planning. (author)

Safe Maritime Autonomous Path Planning in a High Sea State

Science.gov (United States)

Ono, Masahiro; Quadrelli, Marco; Huntsberger, Terrance L.

2014-01-01

This paper presents a path planning method for sea surface vehicles that prevents capsizing and bow-diving in a high sea-state. A key idea is to use response amplitude operators (RAOs) or, in control terminology, the transfer functions from a sea state to a vessel's motion, in order to find a set of speeds and headings that results in excessive pitch and roll oscillations. This information is translated to arithmetic constraints on the ship's velocity, which are passed to a model predictive control (MPC)-based path planner to find a safe and optimal path that achieves specified goals. An obstacle avoidance capability is also added to the path planner. The proposed method is demonstrated by simulations.

Neurobiologically inspired mobile robot navigation and planning

Directory of Open Access Journals (Sweden)

Mathias Quoy

2007-11-01

Full Text Available After a short review of biologically inspired navigation architectures, mainly relying on modeling the hippocampal anatomy, or at least some of its functions, we present a navigation and planning model for mobile robots. This architecture is based on a model of the hippocampal and prefrontal interactions. In particular, the system relies on the definition of a new cell type “transition cells” that encompasses traditional “place cells”.

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

Control of Multiple Robotic Sentry Vehicles

Energy Technology Data Exchange (ETDEWEB)

Feddema, J.; Klarer, P.; Lewis, C.

1999-04-01

As part of a project for the Defense Advanced Research Projects Agency, Sandia National Laboratories is developing and testing the feasibility of using of a cooperative team of robotic sentry vehicles to guard a perimeter and to perform surround and diversion tasks. This paper describes on-going activities in the development of these robotic sentry vehicles. To date, we have developed a robotic perimeter detection system which consists of eight ''Roving All Terrain Lunar Explorer Rover'' (RATLER{trademark}) vehicles, a laptop-based base-station, and several Miniature Intrusion Detection Sensors (MIDS). A radio frequency receiver on each of the RATLER vehicles alerts the sentry vehicles of alarms from the hidden MIDS. When an alarm is received, each vehicle decides whether it should investigate the alarm based on the proximity of itself and the other vehicles to the alarm. As one vehicle attends an alarm, the other vehicles adjust their position around the perimeter to better prepare for another alarm. We have also demonstrated the ability to drive multiple vehicles in formation via tele-operation or by waypoint GPS navigation. This is currently being extended to include mission planning capabilities. At the base-station, the operator can draw on an aerial map the goal regions to be surrounded and the repulsive regions to be avoided. A potential field path planner automatically generates a path from the vehicles' current position to the goal regions while avoiding the repulsive regions and the other vehicles. This path is previewed to the operator before the regions are downloaded to the vehicles. The same potential field path planner resides on the vehicle, except additional repulsive forces from on-board proximity sensors guide the vehicle away from unplanned obstacles.

Coordinated trajectory planning of dual-arm space robot using constrained particle swarm optimization

Science.gov (United States)

Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich

2018-05-01

Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

Development and Field Testing of the FootFall Planning System for the ATHLETE Robots

Science.gov (United States)

SunSpiral, Vytas; Wheeler, D. W.; Chavez-Clementa, Daniel; Mittman, David

2011-01-01

The FootFall Planning System is a ground-based planning and decision support system designed to facilitate the control of walking activities for the ATHLETE (All-Terrain Hex-Limbed Extra-Terrestrial Explorer) family of robots. ATHLETE was developed at NASA's Jet Propulsion Laboratory (JPL) and is a large six-legged robot designed to serve multiple roles during manned and unmanned missions to the Moon; its roles include transportation, construction and exploration. Over the four years from 2006 through 2010 the FootFall Planning System was developed and adapted to two generations of the ATHLETE robots and tested at two analog field sites (the Human Robotic Systems Project's Integrated Field Test at Moses Lake, Washington, June 2008, and the Desert Research and Technology Studies (D-RATS), held at Black Point Lava Flow in Arizona, September 2010). Having 42 degrees of kinematic freedom, standing to a maximum height of just over 4 meters, and having a payload capacity of 450 kg in Earth gravity, the current version of the ATHLETE robot is a uniquely complex system. A central challenge to this work was the compliance of the high-DOF (Degree Of Freedom) robot, especially the compliance of the wheels, which affected many aspects of statically-stable walking. This paper will review the history of the development of the FootFall system, sharing design decisions, field test experiences, and the lessons learned concerning compliance and self-awareness.

Robots testing robots: ALAN-Arm, a humanoid arm for the testing of robotic rehabilitation systems.

Science.gov (United States)

Brookes, Jack; Kuznecovs, Maksims; Kanakis, Menelaos; Grigals, Arturs; Narvidas, Mazvydas; Gallagher, Justin; Levesley, Martin

2017-07-01

Robotics is increasing in popularity as a method of providing rich, personalized and cost-effective physiotherapy to individuals with some degree of upper limb paralysis, such as those who have suffered a stroke. These robotic rehabilitation systems are often high powered, and exoskeletal systems can attach to the person in a restrictive manner. Therefore, ensuring the mechanical safety of these devices before they come in contact with individuals is a priority. Additionally, rehabilitation systems may use novel sensor systems to measure current arm position. Used to capture and assess patient movements, these first need to be verified for accuracy by an external system. We present the ALAN-Arm, a humanoid robotic arm designed to be used for both accuracy benchmarking and safety testing of robotic rehabilitation systems. The system can be attached to a rehabilitation device and then replay generated or human movement trajectories, as well as autonomously play rehabilitation games or activities. Tests of the ALAN-Arm indicated it could recreate the path of a generated slow movement path with a maximum error of 14.2mm (mean = 5.8mm) and perform cyclic movements up to 0.6Hz with low gain (<1.5dB). Replaying human data trajectories showed the ability to largely preserve human movement characteristics with slightly higher path length and lower normalised jerk.

Mobile Robot for Life Science Automation

Directory of Open Access Journals (Sweden)

Hui Liu

2013-07-01

Full Text Available The paper presents a control system for mobile robots in distributed life science laboratories. The system covers all technical aspects of laboratory mobile robotics. In this system: (a to get an accurate and low-cost robot localization, a method using a StarGazer module with a number of ceiling landmarks is utilized; (b to have an expansible communication network, a standard IEEE 802.11g wireless network is adopted and a XML-based command protocol is designed for the communication between the remote side and the robot board side; (c to realize a function of dynamic obstacle measurement and collision avoidance, an artificial potential field method based on a Microsoft Kinect sensor is used; and (d to determine the shortest paths for transportation tasks, a hybrid planning strategy based on a Floyd algorithm and a Genetic Algorithm (GA is proposed. Additionally, to make the traditional GA method suitable for the laboratory robot's routing, a series of optimized works are also provided in detail. Two experiments show that the proposed system and its control strategy are effective for a complex life science laboratory.

Navigation control of a multi-functional eye robot

International Nuclear Information System (INIS)

Ali, F.A.M.; Hashmi, B.; Younas, A.; Abid, B.

2016-01-01

The advancement in robotic field is enhanced rigorously in the past Few decades. Robots are being used in different fields of science as well as warfare. The research shows that in the near future, robots would be able to serve in fighting wars. Different countries and their armies have already deployed several military robots. However, there exist some drawbacks of robots like their inefficiency and inability to work under abnormal conditions. Ascent of artificial intelligence may resolve this issue in the coming future. The main focus of this paper is to provide a low cost and long range most efficient mechanical as well as software design of an Eye Robot. Using a blend of robotics and image processing with an addition of artificial intelligence path navigation techniques, this project is designed and implemented by controlling the robot (including robotic arm and camera) through a 2.4 GHz RF module manually. Autonomous function of the robot includes navigation based on the path assigned to the robot. The path is drawn on a VB based application and then transferred to the robot wirelessly or through serial port. A Wi-Fi based Optical Character Recognition (OCR) implemented video streaming can also be observed at remote devices like laptops. (author)

Local Path Planning of Driverless Car Navigation Based on Jump Point Search Method Under Urban Environment

Directory of Open Access Journals (Sweden)

Kaijun Zhou

2017-09-01

Full Text Available The Jump Point Search (JPS algorithm is adopted for local path planning of the driverless car under urban environment, and it is a fast search method applied in path planning. Firstly, a vector Geographic Information System (GIS map, including Global Positioning System (GPS position, direction, and lane information, is built for global path planning. Secondly, the GIS map database is utilized in global path planning for the driverless car. Then, the JPS algorithm is adopted to avoid the front obstacle, and to find an optimal local path for the driverless car in the urban environment. Finally, 125 different simulation experiments in the urban environment demonstrate that JPS can search out the optimal and safety path successfully, and meanwhile, it has a lower time complexity compared with the Vector Field Histogram (VFH, the Rapidly Exploring Random Tree (RRT, A*, and the Probabilistic Roadmaps (PRM algorithms. Furthermore, JPS is validated usefully in the structured urban environment.

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.

Autonomous Path Planning for Road Vehicles in Narrow Environments: An Efficient Continuous Curvature Approach

Directory of Open Access Journals (Sweden)

Domokos Kiss

2017-01-01

Full Text Available In this paper we introduce a novel method for obtaining good quality paths for autonomous road vehicles (e.g., cars or buses in narrow environments. There are many traffic situations in urban scenarios where nontrivial maneuvering in narrow places is necessary. Navigating in cluttered parking lots or having to avoid obstacles blocking the way and finding a detour even in narrow streets are challenging, especially if the vehicle has large dimensions like a bus. We present a combined approximation-based approach to solve the path planning problem in such situations. Our approach consists of a global planner which generates a preliminary path consisting of straight and turning-in-place primitives and a local planner which is used to make the preliminary path feasible to car-like vehicles. The approximation methodology is well known in the literature; however, both components proposed in this paper differ from existing similar planning methods. The approximation process with the proposed local planner is proven to be convergent for any preliminary global paths. The resulting path has continuous curvature which renders our method well suited for application on real vehicles. Simulation experiments show that the proposed method outperforms similar approaches in terms of path quality in complicated planning tasks.

Design and Programming for Cable-Driven Parallel Robots in the German Pavilion at the EXPO 2015

Directory of Open Access Journals (Sweden)

Philipp Tempel

2015-08-01

Full Text Available In the German Pavilion at the EXPO 2015, two large cable-driven parallel robots are flying over the heads of the visitors representing two bees flying over Germany and displaying everyday life in Germany. Each robot consists of a mobile platform and eight cables suspended by winches and follows a desired trajectory, which needs to be computed in advance taking technical limitations, safety considerations and visual aspects into account. In this paper, a path planning software is presented, which includes the design process from developing a robot design and workspace estimation via planning complex trajectories considering technical limitations through to exporting a complete show. For a test trajectory, simulation results are given, which display the relevant trajectories and cable force distributions.

Robot-assisted radiofrequency ablation of primary and secondary liver tumours: early experience

International Nuclear Information System (INIS)

Abdullah, Basri Johan Jeet; Yeong, Chai Hong; Goh, Khean Lee; Yoong, Boon Koon; Ho, Gwo Fuang; Yim, Carolyn Chue Wai; Kulkarni, Anjali

2014-01-01

Computed tomography (CT)-compatible robots, both commercial and research-based, have been developed with the intention of increasing the accuracy of needle placement and potentially improving the outcomes of therapies in addition to reducing clinical staff and patient exposure to radiation during CT fluoroscopy. In the case of highly inaccessible lesions that require multiple plane angulations, robotically assisted needles may improve biopsy access and targeted drug delivery therapy by avoidance of the straight line path of normal linear needles. We report our preliminary experience of performing radiofrequency ablation of the liver using a robotic-assisted CT guidance system on 11 patients (17 lesions). Robotic-assisted planning and needle placement appears to have high accuracy, is technically easier than the non-robotic-assisted procedure, and involves a significantly lower radiation dose to both patient and support staff. (orig.)

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.

Robot-assisted radiofrequency ablation of primary and secondary liver tumours: early experience

Energy Technology Data Exchange (ETDEWEB)

Abdullah, Basri Johan Jeet [University of Malaya, Department of Biomedical Imaging, Faculty of Medicine, Kuala Lumpur (Malaysia); Yeong, Chai Hong [University of Malaya, University of Malaya Research Imaging Centre, Faculty of Medicine, Kuala Lumpur (Malaysia); Goh, Khean Lee [University of Malaya, Department of Internal Medicine, Faculty of Medicine, Kuala Lumpur (Malaysia); Yoong, Boon Koon [University of Malaya, Department of Surgery, Faculty of Medicine, Kuala Lumpur (Malaysia); Ho, Gwo Fuang [University of Malaya, Department of Oncology, Faculty of Medicine, Kuala Lumpur (Malaysia); Yim, Carolyn Chue Wai [University of Malaya, Department of Anesthesia, Faculty of Medicine, Kuala Lumpur (Malaysia); Kulkarni, Anjali [Perfint Healthcare Corporation, Florence, OR (United States)

2014-01-15

Computed tomography (CT)-compatible robots, both commercial and research-based, have been developed with the intention of increasing the accuracy of needle placement and potentially improving the outcomes of therapies in addition to reducing clinical staff and patient exposure to radiation during CT fluoroscopy. In the case of highly inaccessible lesions that require multiple plane angulations, robotically assisted needles may improve biopsy access and targeted drug delivery therapy by avoidance of the straight line path of normal linear needles. We report our preliminary experience of performing radiofrequency ablation of the liver using a robotic-assisted CT guidance system on 11 patients (17 lesions). Robotic-assisted planning and needle placement appears to have high accuracy, is technically easier than the non-robotic-assisted procedure, and involves a significantly lower radiation dose to both patient and support staff. (orig.)

Representation and Integration: Combining Robot Control, High-Level Planning, and Action Learning

DEFF Research Database (Denmark)

Petrick, Ronald; Kraft, Dirk; Mourao, Kira

We describe an approach to integrated robot control, high-level planning, and action effect learning that attempts to overcome the representational difficulties that exist between these diverse areas. Our approach combines ideas from robot vision, knowledgelevel planning, and connectionist machine......-level action specifications, suitable for planning, from a robot’s interactions with the world. We present a detailed overview of our approach and show how it supports the learning of certain aspects of a high-level lepresentation from low-level world state information....... learning, and focuses on the representational needs of these components.We also make use of a simple representational unit called an instantiated state transition fragment (ISTF) and a related structure called an object-action complex (OAC). The goal of this work is a general approach for inducing high...

A Model Based Approach to Increase the Part Accuracy in Robot Based Incremental Sheet Metal Forming

International Nuclear Information System (INIS)

Meier, Horst; Laurischkat, Roman; Zhu Junhong

2011-01-01

One main influence on the dimensional accuracy in robot based incremental sheet metal forming results from the compliance of the involved robot structures. Compared to conventional machine tools the low stiffness of the robot's kinematic results in a significant deviation of the planned tool path and therefore in a shape of insufficient quality. To predict and compensate these deviations offline, a model based approach, consisting of a finite element approach, to simulate the sheet forming, and a multi body system, modeling the compliant robot structure, has been developed. This paper describes the implementation and experimental verification of the multi body system model and its included compensation method.

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

Science.gov (United States)

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-01-01

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

Science.gov (United States)

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-02-11

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm

Directory of Open Access Journals (Sweden)

Anish Pandey

2017-02-01

Full Text Available This article introduces a singleton type-1 fuzzy logic system (T1-SFLS controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. The WDO (Wind Driven Optimization algorithm is used to optimize and tune the input/output membership function parameters of the fuzzy controller. The WDO algorithm is working based on the atmospheric motion of infinitesimal small air parcels navigates over an N-dimensional search domain. The performance of this proposed technique has compared through many computer simulations and real-time experiments by using Khepera-III mobile robot. As compared to the T1-SFLS controller the Fuzzy-WDO algorithm is found good agreement for mobile robot navigation.

Autonomous mobile robotic system for supporting counterterrorist and surveillance operations

Science.gov (United States)

Adamczyk, Marek; Bulandra, Kazimierz; Moczulski, Wojciech

2017-10-01

Contemporary research on mobile robots concerns applications to counterterrorist and surveillance operations. The goal is to develop systems that are capable of supporting the police and special forces by carrying out such operations. The paper deals with a dedicated robotic system for surveillance of large objects such as airports, factories, military bases, and many others. The goal is to trace unauthorised persons who try to enter to the guarded area, document the intrusion and report it to the surveillance centre, and then warn the intruder by sound messages and eventually subdue him/her by stunning through acoustic effect of great power. The system consists of several parts. An armoured four-wheeled robot assures required mobility of the system. The robot is equipped with a set of sensors including 3D mapping system, IR and video cameras, and microphones. It communicates with the central control station (CCS) by means of a wideband wireless encrypted system. A control system of the robot can operate autonomously, and under remote control. In the autonomous mode the robot follows the path planned by the CCS. Once an intruder has been detected, the robot can adopt its plan to allow tracking him/her. Furthermore, special procedures of treatment of the intruder are applied including warning about the breach of the border of the protected area, and incapacitation of an appropriately selected very loud sound until a patrol of guards arrives. Once getting stuck the robot can contact the operator who can remotely solve the problem the robot is faced with.

A New Approach of Multi-robot Cooperative Pursuit Based on Association Rule Data Mining

Directory of Open Access Journals (Sweden)

Jun Li

2010-02-01

Full Text Available An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuit process into forming the pursuit teams and capturing the targets. The data sets of attribute relationship is built by consulting all of factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuit teams. Through doping out the positions of targets, the pursuit game can be transformed into multi-robot path planning. Reinforcement learning is used to find the best path. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove the feasibility and validity of the given algorithm under a dynamic environment.

A New Approach of Multi-Robot Cooperative Pursuit Based on Association Rule Data Mining

Directory of Open Access Journals (Sweden)

Jun Li

2009-12-01

Full Text Available An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuit process into forming the pursuit teams and capturing the targets. The data sets of attribute relationship is built by consulting all of factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuit teams. Through doping out the positions of targets, the pursuit game can be transformed into multi-robot path planning. Reinforcement learning is used to find the best path. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove the feasibility and validity of the given algorithm under a dynamic environment.

Current-Sensitive Path Planning for an Underactuated Free-Floating Ocean Sensorweb

Science.gov (United States)

Dahl, Kristen P.; Thompson, David R.; McLaren, David; Chao, Yi; Chien, Steve

2011-01-01

This work investigates multi-agent path planning in strong, dynamic currents using thousands of highly under-actuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.

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

International Nuclear Information System (INIS)

Pin, Francois G.

2003-01-01

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

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

International Nuclear Information System (INIS)

Pin, Grancois G.

2004-01-01

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

Design and implementation of motion planning of inspection and maintenance robot for ITER-like vessel

Energy Technology Data Exchange (ETDEWEB)

Wang, Hesheng; Lai, Yinping [Department of Automation, Shanghai Jiao Tong University, Shanghai 200240 (China); Key Laboratory of System Control and Information Processing, Ministry of Education of China (China); Chen, Weidong, E-mail: wdchen@sjtu.edu.cn [Department of Automation, Shanghai Jiao Tong University, Shanghai 200240 (China); Key Laboratory of System Control and Information Processing, Ministry of Education of China (China); Cao, Qixin [Institute of Robotics, Shanghai Jiao Tong University, Shanghai 200240 (China)

2015-12-15

Robot motion planning is a fundamental problem to ensure the robot executing the task without clashes, fast and accurately in a special environment. In this paper, a motion planning of a 12 DOFs remote handling robot used for inspecting the working state of the ITER-like vessel and maintaining key device components is proposed and implemented. Firstly, the forward and inverse kinematics are given by analytic method. The work space and posture space of this manipulator are both considered. Then the motion planning is divided into three stages: coming out of the cassette mover, moving along the in-vessel center line, and inspecting the D-shape section. Lastly, the result of experiments verified the performance of the motion design method. In addition, the task of unscrewing/screwing the screw demonstrated the feasibility of system in function.

Based on Short Motion Paths and Artificial Intelligence Method for Chinese Chess Game

Directory of Open Access Journals (Sweden)

Chien-Ming Hung

2017-08-01

Full Text Available The article develops the decision rules to win each set of the Chinese chess game using evaluation algorithm and artificial intelligence method, and uses the mobile robot to be instead of the chess, and presents the movement scenarios using the shortest motion paths for mobile robots. Player can play the Chinese chess game according to the game rules with the supervised computer. The supervised computer decides the optimal motion path to win the set using artificial intelligence method, and controls mobile robots according to the programmed motion paths of the assigned chesses moving on the platform via wireless RF interface. We uses enhance A* searching algorithm to solve the shortest path problem of the assigned chess, and solve the collision problems of the motion paths for two mobile robots moving on the platform simultaneously. We implement a famous set to be called lwild horses run in farmr using the proposed method. First we use simulation method to display the motion paths of the assigned chesses for the player and the supervised computer. Then the supervised computer implements the simulation results on the chessboard platform using mobile robots. Mobile robots move on the chessboard platform according to the programmed motion paths and is guided to move on the centre line of the corridor, and avoid the obstacles (chesses, and detect the cross point of the platform using three reflective IR modules.

Hierarchical path planning and control of a small fixed-wing UAV: Theory and experimental validation

Science.gov (United States)

Jung, Dongwon

2007-12-01

Recently there has been a tremendous growth of research emphasizing control of unmanned aerial vehicles (UAVs) either in isolation or in teams. As a matter of fact, UAVs increasingly find their way into military and law enforcement applications (e.g., reconnaissance, remote delivery of urgent equipment/material, resource assessment, environmental monitoring, battlefield monitoring, ordnance delivery, etc.). This trend will continue in the future, as UAVs are poised to replace the human-in-the-loop during dangerous missions. Civilian applications of UAVs are also envisioned such as crop dusting, geological surveying, search and rescue operations, etc. In this thesis we propose a new online multiresolution path planning algorithm for a small UAV with limited on-board computational resources. The proposed approach assumes that the UAV has detailed information of the environment and the obstacles only in its vicinity. Information about far-away obstacles is also available, albeit less accurately. The proposed algorithm uses the fast lifting wavelet transform (FLWT) to get a multiresolution cell decomposition of the environment, whose dimension is commensurate to the on-board computational resources. A topological graph representation of the multiresolution cell decomposition is constructed efficiently, directly from the approximation and detail wavelet coefficients. Dynamic path planning is sequentially executed for an optimal path using the A* algorithm over the resulting graph. The proposed path planning algorithm is implemented on-line on a small autopilot. Comparisons with the standard D*-lite algorithm are also presented. We also investigate the problem of generating a smooth, planar reference path from a discrete optimal path. Upon the optimal path being represented as a sequence of cells in square geometry, we derive a smooth B-spline path that is constrained inside a channel that is induced by the geometry of the cells. To this end, a constrained optimization

A Robot Trajectory Optimization Approach for Thermal Barrier Coatings Used for Free-Form Components

Science.gov (United States)

Cai, Zhenhua; Qi, Beichun; Tao, Chongyuan; Luo, Jie; Chen, Yuepeng; Xie, Changjun

2017-10-01

This paper is concerned with a robot trajectory optimization approach for thermal barrier coatings. As the requirements of high reproducibility of complex workpieces increase, an optimal thermal spraying trajectory should not only guarantee an accurate control of spray parameters defined by users (e.g., scanning speed, spray distance, scanning step, etc.) to achieve coating thickness homogeneity but also help to homogenize the heat transfer distribution on the coating surface. A mesh-based trajectory generation approach is introduced in this work to generate path curves on a free-form component. Then, two types of meander trajectories are generated by performing a different connection method. Additionally, this paper presents a research approach for introducing the heat transfer analysis into the trajectory planning process. Combining heat transfer analysis with trajectory planning overcomes the defects of traditional trajectory planning methods (e.g., local over-heating), which helps form the uniform temperature field by optimizing the time sequence of path curves. The influence of two different robot trajectories on the process of heat transfer is estimated by coupled FEM models which demonstrates the effectiveness of the presented optimization approach.

ROBOT TASK SCENE ANALYZER

International Nuclear Information System (INIS)

Hamel, William R.; Everett, Steven

2000-01-01

Environmental restoration and waste management (ER and WM) challenges in the United States Department of Energy (DOE), and around the world, involve radiation or other hazards which will necessitate the use of remote operations to protect human workers from dangerous exposures. Remote operations carry the implication of greater costs since remote work systems are inherently less productive than contact human work due to the inefficiencies/complexities of teleoperation. To reduce costs and improve quality, much attention has been focused on methods to improve the productivity of combined human operator/remote equipment systems; the achievements to date are modest at best. The most promising avenue in the near term is to supplement conventional remote work systems with robotic planning and control techniques borrowed from manufacturing and other domains where robotic automation has been used. Practical combinations of teleoperation and robotic control will yield telerobotic work systems that outperform currently available remote equipment. It is believed that practical telerobotic systems may increase remote work efficiencies significantly. Increases of 30% to 50% have been conservatively estimated for typical remote operations. It is important to recognize that the basic hardware and software features of most modern remote manipulation systems can readily accommodate the functionality required for telerobotics. Further, several of the additional system ingredients necessary to implement telerobotic control--machine vision, 3D object and workspace modeling, automatic tool path generation and collision-free trajectory planning--are existent

ROBOT TASK SCENE ANALYZER

Energy Technology Data Exchange (ETDEWEB)

William R. Hamel; Steven Everett

2000-08-01

Environmental restoration and waste management (ER and WM) challenges in the United States Department of Energy (DOE), and around the world, involve radiation or other hazards which will necessitate the use of remote operations to protect human workers from dangerous exposures. Remote operations carry the implication of greater costs since remote work systems are inherently less productive than contact human work due to the inefficiencies/complexities of teleoperation. To reduce costs and improve quality, much attention has been focused on methods to improve the productivity of combined human operator/remote equipment systems; the achievements to date are modest at best. The most promising avenue in the near term is to supplement conventional remote work systems with robotic planning and control techniques borrowed from manufacturing and other domains where robotic automation has been used. Practical combinations of teleoperation and robotic control will yield telerobotic work systems that outperform currently available remote equipment. It is believed that practical telerobotic systems may increase remote work efficiencies significantly. Increases of 30% to 50% have been conservatively estimated for typical remote operations. It is important to recognize that the basic hardware and software features of most modern remote manipulation systems can readily accommodate the functionality required for telerobotics. Further, several of the additional system ingredients necessary to implement telerobotic control--machine vision, 3D object and workspace modeling, automatic tool path generation and collision-free trajectory planning--are existent.

Patient-specific surgical simulator for the pre-operative planning of single-incision laparoscopic surgery with bimanual robots.

Science.gov (United States)

Turini, Giuseppe; Moglia, Andrea; Ferrari, Vincenzo; Ferrari, Mauro; Mosca, Franco

2012-01-01

The trend of surgical robotics is to follow the evolution of laparoscopy, which is now moving towards single-incision laparoscopic surgery. The main drawback of this approach is the limited maneuverability of the surgical tools. Promising solutions to improve the surgeon's dexterity are based on bimanual robots. However, since both robot arms are completely inserted into the patient's body, issues related to possible unwanted collisions with structures adjacent to the target organ may arise. This paper presents a simulator based on patient-specific data for the positioning and workspace evaluation of bimanual surgical robots in the pre-operative planning of single-incision laparoscopic surgery. The simulator, designed for the pre-operative planning of robotic laparoscopic interventions, was tested by five expert surgeons who evaluated its main functionalities and provided an overall rating for the system. The proposed system demonstrated good performance and usability, and was designed to integrate both present and future bimanual surgical robots.

Automatic Multiple-Needle Surgical Planning of Robotic-Assisted Microwave Coagulation in Large Liver Tumor Therapy.

Directory of Open Access Journals (Sweden)

Shaoli Liu

Full Text Available The "robotic-assisted liver tumor coagulation therapy" (RALTCT system is a promising candidate for large liver tumor treatment in terms of accuracy and speed. A prerequisite for effective therapy is accurate surgical planning. However, it is difficult for the surgeon to perform surgical planning manually due to the difficulties associated with robot-assisted large liver tumor therapy. These main difficulties include the following aspects: (1 multiple needles are needed to destroy the entire tumor, (2 the insertion trajectories of the needles should avoid the ribs, blood vessels, and other tissues and organs in the abdominal cavity, (3 the placement of multiple needles should avoid interference with each other, (4 an inserted needle will cause some deformation of liver, which will result in changes in subsequently inserted needles' operating environment, and (5 the multiple needle-insertion trajectories should be consistent with the needle-driven robot's movement characteristics. Thus, an effective multiple-needle surgical planning procedure is needed. To overcome these problems, we present an automatic multiple-needle surgical planning of optimal insertion trajectories to the targets, based on a mathematical description of all relevant structure surfaces. The method determines the analytical expression of boundaries of every needle "collision-free reachable workspace" (CFRW, which are the feasible insertion zones based on several constraints. Then, the optimal needle insertion trajectory within the optimization criteria will be chosen in the needle CFRW automatically. Also, the results can be visualized with our navigation system. In the simulation experiment, three needle-insertion trajectories were obtained successfully. In the in vitro experiment, the robot successfully achieved insertion of multiple needles. The proposed automatic multiple-needle surgical planning can improve the efficiency and safety of robot-assisted large liver tumor

Automatic Multiple-Needle Surgical Planning of Robotic-Assisted Microwave Coagulation in Large Liver Tumor Therapy.

Science.gov (United States)

Liu, Shaoli; Xia, Zeyang; Liu, Jianhua; Xu, Jing; Ren, He; Lu, Tong; Yang, Xiangdong

2016-01-01

The "robotic-assisted liver tumor coagulation therapy" (RALTCT) system is a promising candidate for large liver tumor treatment in terms of accuracy and speed. A prerequisite for effective therapy is accurate surgical planning. However, it is difficult for the surgeon to perform surgical planning manually due to the difficulties associated with robot-assisted large liver tumor therapy. These main difficulties include the following aspects: (1) multiple needles are needed to destroy the entire tumor, (2) the insertion trajectories of the needles should avoid the ribs, blood vessels, and other tissues and organs in the abdominal cavity, (3) the placement of multiple needles should avoid interference with each other, (4) an inserted needle will cause some deformation of liver, which will result in changes in subsequently inserted needles' operating environment, and (5) the multiple needle-insertion trajectories should be consistent with the needle-driven robot's movement characteristics. Thus, an effective multiple-needle surgical planning procedure is needed. To overcome these problems, we present an automatic multiple-needle surgical planning of optimal insertion trajectories to the targets, based on a mathematical description of all relevant structure surfaces. The method determines the analytical expression of boundaries of every needle "collision-free reachable workspace" (CFRW), which are the feasible insertion zones based on several constraints. Then, the optimal needle insertion trajectory within the optimization criteria will be chosen in the needle CFRW automatically. Also, the results can be visualized with our navigation system. In the simulation experiment, three needle-insertion trajectories were obtained successfully. In the in vitro experiment, the robot successfully achieved insertion of multiple needles. The proposed automatic multiple-needle surgical planning can improve the efficiency and safety of robot-assisted large liver tumor therapy

Empirical evaluation of a practical indoor mobile robot navigation method using hybrid maps

DEFF Research Database (Denmark)

Özkil, Ali Gürcan; Fan, Zhun; Xiao, Jizhong

2010-01-01

This video presents a practical navigation scheme for indoor mobile robots using hybrid maps. The method makes use of metric maps for local navigation and a topological map for global path planning. Metric maps are generated as occupancy grids by a laser range finder to represent local information...... about partial areas. The global topological map is used to indicate the connectivity of the ‘places-of-interests’ in the environment and the interconnectivity of the local maps. Visual tags on the ceiling to be detected by the robot provide valuable information and contribute to reliable localization...... that the method is implemented successfully on physical robot in a hospital environment, which provides a practical solution for indoor navigation....

Heading Estimation of Robot Combine Harvesters during Turning Maneuveres.

Science.gov (United States)

Rahman, Md Mostafizar; Ishii, Kazunobu

2018-05-01

Absolute heading is an important parameter for a robot combine harvester or a robot tracked combine harvester, especially while it is turning, but due to the rapid turning of robot combine harvesters, its inertial measurement unit gives a gyro measurement bias that causes heading drift. Our research goal is to estimate the absolute heading of robot combine harvesters by compensating this gyro measurement bias during non-linear turning maneuvers. A sensor fusion method like the extended Kalman filter combined with the tracked combine harvester dynamic model and sensor measurements was used to estimate the absolute heading of a robot combine harvester. Circular, sinusoidal and concave shapes were used to evaluate the estimated heading produced by the sensor fusion method. The results indicate that the estimated heading is better than measured heading which was calculated from the integration of yaw rate gyro measurements, and the root mean square errors (RMSEs) for estimated headings are smaller than the measured headings. In practics, the target of this paper is thus the estimation of a heading or absolute heading that is bias compensated, and can be further used to calculate the exact crop periphery for automatic path planning of robot combine harvesters.

Planning Robotic Manipulation Strategies for Sliding Objects

Science.gov (United States)

Peshkin, Michael A.

Automated planning of grasping or manipulation requires an understanding of both the physics and the geometry of manipulation, and a representation of that knowledge which facilitates the search for successful strategies. We consider manipulation on a level conveyor belt or tabletop, on which a part may slide when touched by a robot. Manipulation plans for a given part must succeed in the face of two types of uncertainty: that of the details of surfaces in contact, and that of the initial configuration of the part. In general the points of contact between the part and the surface it slides on will be unknown, so the motion of the part in response to a push cannot be predicted exactly. Using a simple variational principle (which is derived), we find the set of possible motions of a part for a given push, for all collections of points of contact. The answer emerges as a locus of centers of rotation (CORs). Manipulation plans made using this locus will succeed despite unknown details of contact. Results of experimental tests of the COR loci are presented. Uncertainty in the initial configuration of a part is usually also present. To plan in the presence of uncertainty, configuration maps are defined, which map all configurations of a part before an elementary operation to all possible outcomes, thus encapsulating the physics and geometry of the operation. The configuration map for an operation sequence is a product of configuration maps of elementary operations. Using COR loci we compute configuration maps for elementary sliding operations. Appropriate search techniques are applied to find operation sequences which succeed in the presence of uncertainty in the initial configuration and unknown details of contact. Such operation sequences may be used as parts feeder designs or as manipulation or grasping strategies for robots. As an example we demonstrate the automated design of a class of passive parts feeders consisting of multiple sequential fences across a conveyor

Optimal Orientation Planning and Control Deviation Estimation on FAST Cable-Driven Parallel Robot

Directory of Open Access Journals (Sweden)

Hui Li

2014-03-01

Full Text Available The paper is devoted theoretically to the optimal orientation planning and control deviation estimation of FAST cable-driven parallel robot. Regarding the robot characteristics, the solutions are obtained from two constrained optimizations, both of which are based on the equilibrium of the cabin and the attention on force allocation among 6 cable tensions. A kind of control algorithm is proposed based on the position and force feedbacks. The analysis proves that the orientation control depends on force feedback and the optimal tension solution corresponding to the planned orientation. Finally, the estimation of orientation deviation is given under the limit range of tension errors.

The Toggle Local Planner for sampling-based motion planning

KAUST Repository

Denny, Jory

2012-05-01

Sampling-based solutions to the motion planning problem, such as the probabilistic roadmap method (PRM), have become commonplace in robotics applications. These solutions are the norm as the dimensionality of the planning space grows, i.e., d > 5. An important primitive of these methods is the local planner, which is used for validation of simple paths between two configurations. The most common is the straight-line local planner which interpolates along the straight line between the two configurations. In this paper, we introduce a new local planner, Toggle Local Planner (Toggle LP), which extends local planning to a two-dimensional subspace of the overall planning space. If no path exists between the two configurations in the subspace, then Toggle LP is guaranteed to correctly return false. Intuitively, more connections could be found by Toggle LP than by the straight-line planner, resulting in better connected roadmaps. As shown in our results, this is the case, and additionally, the extra cost, in terms of time or storage, for Toggle LP is minimal. Additionally, our experimental analysis of the planner shows the benefit for a wide array of robots, with DOF as high as 70. © 2012 IEEE.

Intelligent control system for nuclear power plant mobile robot

International Nuclear Information System (INIS)

Koenig, A.; Lecoeur-Taibi, I.; Crochon, E.; Vacherand, F.

1991-01-01

In order to fully optimize the efficiency of the perception and navigation components available on a mobile robot, the upper level of a mobile robot control requires intelligence support to unload the work of the teleoperator. This knowledge-based system has to manage a priori data such as the map of the workspace, the mission, the characteristics of sensors and robot, but also, the current environment state and the running mission. It has to issue a plan to drive the sensors to focus on relevant objects or to scan the environment and to select the best algorithms depending on the current situation. The environment workspace is a nuclear power plant building. The teleoperated robot is a mobile wheeled or legged vehicle that moves inside the different floors of the building. There are three types of mission: radio-activity survey, inspection and intervention. To perform these goals the robot must avoid obstacles, pass through doors, possibly climb stairs and recognize valves and pipes. The perception control system has to provide the operator with a synthetic view of the surroundings. It manages background tasks such as obstacle detection and free space map building, and specific tasks such as beacon recognition for odometry relocalization and valve detection for maintenance. To do this, the system solves perception resources conflicts, taking into account the current states of the sensors and the current conditions such as lightness or darkness, cluttered scenes, sensor failure. A perception plan is issued from the mission goals, planned path, relocalization requirements and available perception resources. Basically, the knowledge-based system is implemented on a blackboard architecture which includes two parts: a top-down planning part and a bottom-up perception part. The results of the perception are continuously sent to the operator who can trigger new perception actions. (author)

Robot Tracer with Visual Camera

Science.gov (United States)

Jabbar Lubis, Abdul; Dwi Lestari, Yuyun; Dafitri, Haida; Azanuddin

2017-12-01

Robot is a versatile tool that can function replace human work function. The robot is a device that can be reprogrammed according to user needs. The use of wireless networks for remote monitoring needs can be utilized to build a robot that can be monitored movement and can be monitored using blueprints and he can track the path chosen robot. This process is sent using a wireless network. For visual robot using high resolution cameras to facilitate the operator to control the robot and see the surrounding circumstances.

Globally Optimal Path Planning with Anisotropic Running Costs

Science.gov (United States)

2013-03-01

Eikonal equation and has numerous applications, for exam- ple, in path planning, computational geometry, computer vision, and image enhancement...Sethian 1999b]. Numerical methods for solving the Eikonal equation include Tsitsiklis’ control-theoretic algorithm [Tsitsiklis 1995], Fast Marching Methods...methods for Eikonal equations on triangular meshes, SIAM J. Numer. Anal. 45(1), 83—107. Rowe, M. P., Sidhu, H. S. & Mercer, G. N. (2009) Military

Towards Informative Path Planning for Acoustic SLAM

OpenAIRE

Evers, C; Moore, A; Naylor, P

2016-01-01

Acoustic scene mapping is a challenging task as microphone arrays can often localize sound sources only in terms of their directions. Spatial diversity can be exploited constructively to infer source-sensor range when using microphone arrays installed on moving platforms, such as robots. As the absolute location of a moving robot is often unknown in practice, Acoustic Simultaneous Localization And Mapping (a-SLAM) is required in order to localize the moving robot?s positions and jointly map t...

A Robust Planning Algorithm for Groups of Entities in Discrete Spaces

Directory of Open Access Journals (Sweden)

Igor Wojnicki

2015-07-01

Full Text Available Automated planning is a well-established field of artificial intelligence (AI, with applications in route finding, robotics and operational research, among others. The task of developing a plan is often solved by finding a path in a graph representing the search domain; a robust plan consists of numerous paths that can be chosen if the execution of the best (optimal one fails. While robust planning for a single entity is rather simple, development of a robust plan for multiple entities in a common environment can lead to combinatorial explosion. This paper proposes a novel hybrid approach, joining heuristic search and the wavefront algorithm to provide a plan featuring robustness in areas where it is needed, while maintaining a low level of computational complexity.

Aircraft path planning with the use of smooth trajectories

Science.gov (United States)

Belokon', S. A.; Zolotukhin, Yu. N.; Nesterov, A. A.

2017-01-01

A simplified method of plane trajectory calculation is proposed for solving the problem of planning a path defined by a sequence of waypoints. The trajectory consists of oriented segments of straight lines joined by clothoids (Cornu spirals). The efficiency of the method is validated by means of numerical simulations in the MATLAB/Simulink environment.

Resection planning for robotic acoustic neuroma surgery

Science.gov (United States)

McBrayer, Kepra L.; Wanna, George B.; Dawant, Benoit M.; Balachandran, Ramya; Labadie, Robert F.; Noble, Jack H.

2016-03-01

Acoustic neuroma surgery is a procedure in which a benign mass is removed from the Internal Auditory Canal (IAC). Currently this surgical procedure requires manual drilling of the temporal bone followed by exposure and removal of the acoustic neuroma. This procedure is physically and mentally taxing to the surgeon. Our group is working to develop an Acoustic Neuroma Surgery Robot (ANSR) to perform the initial drilling procedure. Planning the ANSR's drilling region using pre-operative CT requires expertise and around 35 minutes' time. We propose an approach for automatically producing a resection plan for the ANSR that would avoid damage to sensitive ear structures and require minimal editing by the surgeon. We first compute an atlas-based segmentation of the mastoid section of the temporal bone, refine it based on the position of anatomical landmarks, and apply a safety margin to the result to produce the automatic resection plan. In experiments with CTs from 9 subjects, our automated process resulted in a resection plan that was verified to be safe in every case. Approximately 2 minutes were required in each case for the surgeon to verify and edit the plan to permit functional access to the IAC. We measured a mean Dice coefficient of 0.99 and surface error of 0.08 mm between the final and automatically proposed plans. These preliminary results indicate that our approach is a viable method for resection planning for the ANSR and drastically reduces the surgeon's planning effort.

A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems

KAUST Repository

Abdelkader, Mohamed

2017-10-19

We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which is an adversarial game played between two teams of autonomous agents called defenders and attackers. We start with the centralized formulation of the problem as a linear program because of its computational efficiency. Then we present an approximation framework in which each agent solves a local version of the centralized linear program by communicating with its neighbors only. The premise in this work is that for practical multi-agent systems, real time implementability of distributed algorithms is more crucial then global optimality. Thus, instead of verifying the proposed framework by performing offline simulations in MATLAB, we run extensive simulations in a robotic simulator V-REP, which includes a detailed dynamic model of quadrotors. Moreover, to create a realistic scenario, we allow a human operator to control the attacker quadrotor through a joystick in a single attacker setup. These simulations authenticate that the proposed framework is real time implementable and results in a performance that is comparable with the global optimal solution under the considered scenarios.

A novel approach for multiple mobile objects path planning: Parametrization method and conflict resolution strategy

International Nuclear Information System (INIS)

Ma, Yong; Wang, Hongwei; Zamirian, M.

2012-01-01

We present a new approach containing two steps to determine conflict-free paths for mobile objects in two and three dimensions with moving obstacles. Firstly, the shortest path of each object is set as goal function which is subject to collision-avoidance criterion, path smoothness, and velocity and acceleration constraints. This problem is formulated as calculus of variation problem (CVP). Using parametrization method, CVP is converted to time-varying nonlinear programming problems (TNLPP) and then resolved. Secondly, move sequence of object is assigned by priority scheme; conflicts are resolved by multilevel conflict resolution strategy. Approach efficiency is confirmed by numerical examples. -- Highlights: ► Approach with parametrization method and conflict resolution strategy is proposed. ► Approach fits for multi-object paths planning in two and three dimensions. ► Single object path planning and multi-object conflict resolution are orderly used. ► Path of each object obtained with parameterization method in the first phase. ► Conflict-free paths gained by multi-object conflict resolution in the second phase.

An Aerial-Ground Robotic System for Navigation and Obstacle Mapping in Large Outdoor Areas

Directory of Open Access Journals (Sweden)

David Zapata

2013-01-01

Full Text Available There are many outdoor robotic applications where a robot must reach a goal position or explore an area without previous knowledge of the environment around it. Additionally, other applications (like path planning require the use of known maps or previous information of the environment. This work presents a system composed by a terrestrial and an aerial robot that cooperate and share sensor information in order to address those requirements. The ground robot is able to navigate in an unknown large environment aided by visual feedback from a camera on board the aerial robot. At the same time, the obstacles are mapped in real-time by putting together the information from the camera and the positioning system of the ground robot. A set of experiments were carried out with the purpose of verifying the system applicability. The experiments were performed in a simulation environment and outdoor with a medium-sized ground robot and a mini quad-rotor. The proposed robotic system shows outstanding results in simultaneous navigation and mapping applications in large outdoor environments.

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

Science.gov (United States)

Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

Path planning in uncertain flow fields using ensemble method

KAUST Repository

Wang, Tong

2016-08-20

An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.

A Framework for Multi-Robot Motion Planning from Temporal Logic Specifications

DEFF Research Database (Denmark)

Koo, T. John; Li, Rongqing; Quottrup, Michael Melholt

2012-01-01

-time Temporal Logic, Computation Tree Logic, and -calculus can be preserved. Motion planning can then be performed at a discrete level by considering the parallel composition of discrete abstractions of the robots with a requirement specification given in a suitable temporal logic. The bisimilarity ensures...

A New Methodology for Solving Trajectory Planning and Dynamic Load-Carrying Capacity of a Robot Manipulator

Directory of Open Access Journals (Sweden)

Wanjin Guo

2016-01-01

Full Text Available A new methodology using a direct method for obtaining the best found trajectory planning and maximum dynamic load-carrying capacity (DLCC is presented for a 5-degree of freedom (DOF hybrid robot manipulator. A nonlinear constrained multiobjective optimization problem is formulated with four objective functions, namely, travel time, total energy involved in the motion, joint jerks, and joint acceleration. The vector of decision variables is defined by the sequence of the time-interval lengths associated with each two consecutive via-points on the desired trajectory of the 5-DOF robot generalized coordinates. Then this vector of decision variables is computed in order to minimize the cost function (which is the weighted sum of these four objective functions subject to constraints on joint positions, velocities, acceleration, jerks, forces/torques, and payload mass. Two separate approaches are proposed to deal with the trajectory planning problem and the maximum DLCC calculation for the 5-DOF robot manipulator using an evolutionary optimization technique. The adopted evolutionary algorithm is the elitist nondominated sorting genetic algorithm (NSGA-II. A numerical application is performed for obtaining best found solutions of trajectory planning and maximum DLCC calculation for the 5-DOF hybrid robot manipulator.

Environmental mobile robot based on artificial intelligence and visual perception for weed elimination

Directory of Open Access Journals (Sweden)

Nabeel Kadim Abid AL-SAHIB

2012-12-01

Full Text Available This research presents a new editing design for the pioneer p3-dx mobile robot by adding a mechanical gripper for eliminating the weed and a digital camera for capturing the image of the field. Also, a wireless kit that makes control on the motor's gripper is envisaged. This work consists of two parts. The theoretical part contains a program to read the image and discover the weed coordinates which will be sent to the path planning software to discover the locations of weed, green plant and sick plant. These positions are sent then to the mobile robot navigation software. Then the wireless signal is sent to the gripper. The experimental part is represented as a digital camera that takes an image of the agricultural field, and then sends it to the computer for processing. After that the weeds coordinates are sent to the mobile robots by mobile robot navigation software. Next, the wireless signal is sent to the wireless kit controlling the motor gripper by the computer interface program; the first trial on the agricultural field shows that the mobile robot can discriminate the green plant, from weed and sick plant and can take the right decision with respect to treatment or elimination. The experimental work shows that the environmental mobile robot can detect successfully the weed, sick plant and the hale plant. The mobile robot also travels from base to the target point represented by the weed and sick plants in the optimum path. The experimental work also shows that the environmental mobile robot can eliminate the weed and cure the sick plants in a correctly way.

Robust path planning for flexible needle insertion using Markov decision processes.

Science.gov (United States)

Tan, Xiaoyu; Yu, Pengqian; Lim, Kah-Bin; Chui, Chee-Kong

2018-05-11

Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue-needle interactions. This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue-needle interaction. Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue-needle interactions. Future work will involve experiment with biological tissue in vivo. The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.

Resampling: An optimization method for inverse planning in robotic radiosurgery

International Nuclear Information System (INIS)

Schweikard, Achim; Schlaefer, Alexander; Adler, John R. Jr.

2006-01-01

By design, the range of beam directions in conventional radiosurgery are constrained to an isocentric array. However, the recent introduction of robotic radiosurgery dramatically increases the flexibility of targeting, and as a consequence, beams need be neither coplanar nor isocentric. Such a nonisocentric design permits a large number of distinct beam directions to be used in one single treatment. These major technical differences provide an opportunity to improve upon the well-established principles for treatment planning used with GammaKnife or LINAC radiosurgery. With this objective in mind, our group has developed over the past decade an inverse planning tool for robotic radiosurgery. This system first computes a set of beam directions, and then during an optimization step, weights each individual beam. Optimization begins with a feasibility query, the answer to which is derived through linear programming. This approach offers the advantage of completeness and avoids local optima. Final beam selection is based on heuristics. In this report we present and evaluate a new strategy for utilizing the advantages of linear programming to improve beam selection. Starting from an initial solution, a heuristically determined set of beams is added to the optimization problem, while beams with zero weight are removed. This process is repeated to sample a set of beams much larger compared with typical optimization. Experimental results indicate that the planning approach efficiently finds acceptable plans and that resampling can further improve its efficiency

Robot engineering

Energy Technology Data Exchange (ETDEWEB)

Jung, Seul

2006-02-15

This book deals with robot engineering, giving descriptions of robot's history, current tendency of robot field, work and characteristic of industrial robot, essential merit and vector, application of matrix, analysis of basic vector, expression of Denavit-Hartenberg, robot kinematics such as forward kinematics, inverse kinematics, cases of MATLAB program, and motion kinematics, robot kinetics like moment of inertia, centrifugal force and coriolis power, and Euler-Lagrangian equation course plan, SIMULINK position control of robots.

Robot engineering

International Nuclear Information System (INIS)

Jung, Seul

2006-02-01

This book deals with robot engineering, giving descriptions of robot's history, current tendency of robot field, work and characteristic of industrial robot, essential merit and vector, application of matrix, analysis of basic vector, expression of Denavit-Hartenberg, robot kinematics such as forward kinematics, inverse kinematics, cases of MATLAB program, and motion kinematics, robot kinetics like moment of inertia, centrifugal force and coriolis power, and Euler-Lagrangian equation course plan, SIMULINK position control of robots.

Three-dimensional computed tomography reconstruction for operative planning in robotic segmentectomy: a pilot study.

Science.gov (United States)

Le Moal, Julien; Peillon, Christophe; Dacher, Jean-Nicolas; Baste, Jean-Marc

2018-01-01

The objective of our pilot study was to assess if three-dimensional (3D) reconstruction performed by Visible Patient™ could be helpful for the operative planning, efficiency and safety of robot-assisted segmentectomy. Between 2014 and 2015, 3D reconstructions were provided by the Visible Patient™ online service and used for the operative planning of robotic segmentectomy. To obtain 3D reconstruction, the surgeon uploaded the anonymized computed tomography (CT) image of the patient to the secured Visible Patient™ server and then downloaded the model after completion. Nine segmentectomies were performed between 2014 and 2015 using a pre-operative 3D model. All 3D reconstructions met our expectations: anatomical accuracy (bronchi, arteries, veins, tumor, and the thoracic wall with intercostal spaces), accurate delimitation of each segment in the lobe of interest, margin resection, free space rotation, portability (smartphone, tablet) and time saving technique. We have shown that operative planning by 3D CT using Visible Patient™ reconstruction is useful in our practice of robot-assisted segmentectomy. The main disadvantage is the high cost. Its impact on reducing complications and improving surgical efficiency is the object of an ongoing study.

The Motion Path Study of Measuring Robot Based on Variable Universe Fuzzy Control

Directory of Open Access Journals (Sweden)

Ma Guoqing

2017-01-01

Full Text Available For the problem of measuring robot requires a higher positioning, firstly learning about the error overview of the system, analysised the influence of attitude, speed and other factors on systematic errors. Then collected and analyzed the systematic error curve in the track to complete the planning process. The last adding fuzzy control in both cases, by comparing with the original system, can found that the method based on fuzzy control system can significantly reduce the error during the motion.

Preclinical evaluation of an MRI-compatible pneumatic robot for angulated needle placement in transperineal prostate interventions

Science.gov (United States)

Tokuda, Junichi; Song, Sang-Eun; Fischer, Gregory S.; Iordachita, Iulian; Seifabadi, Reza; Cho, Bong Joon; Tuncali, Kemal; Fichtinger, Gabor; Tempany, Clare M.; Hata, Nobuhiko

2013-01-01

Purpose To evaluate the targeting accuracy of a small profile MRI-compatible pneumatic robot for needle placement that can angulate a needle insertion path into a large accessible target volume. Methods We extended our MRI-compatible pneumatic robot for needle placement to utilize its four degrees-of-freedom (4-DOF) mechanism with two parallel triangular structures and support transperineal prostate biopsies in a closed-bore magnetic resonance imaging (MRI) scanner. The robot is designed to guide a needle towards a lesion so that a radiologist can manually insert it in the bore. The robot is integrated with navigation software that allows an operator to plan angulated needle insertion by selecting a target and an entry point. The targeting error was evaluated while the angle between the needle insertion path and the static magnetic field was between −5.7° and 5.7° horizontally and between −5.7° and 4.3° vertically in the MRI scanner after sterilizing and draping the device. Results The robot positioned the needle for angulated insertion as specified on the navigation software with overall targeting error of 0.8 ± 0.5 mm along the horizontal axis and 0.8 ± 0.8 mm along the vertical axis. The two-dimensional root-mean-square targeting error on the axial slices as containing the targets was 1.4 mm. Conclusions Our preclinical evaluation demonstrated that the MRI-compatible pneumatic robot for needle placement with the capability to angulate the needle insertion path provides targeting accuracy feasible for clinical MRI-guided prostate interventions. The clinical feasibility has to be established in a clinical study. PMID:22678723

Learning for intelligent mobile robots

Science.gov (United States)

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

2003-10-01

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

An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage

Directory of Open Access Journals (Sweden)

German Gramajo

2017-01-01

Full Text Available A path planning strategy for a search and coverage mission for a small UAV that maximizes the area covered based on stored energy and maneuverability constraints is presented. The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of flight. Comparisons of this formulation to a path planning algorithm based on those with time constraint show equivalent coverage performance but improvement in prediction of overall mission duration and accuracy of the terminal position of the vehicle.

Heading Estimation of Robot Combine Harvesters during Turning Maneuveres

Directory of Open Access Journals (Sweden)

Md Mostafizar Rahman

2018-05-01

Full Text Available Absolute heading is an important parameter for a robot combine harvester or a robot tracked combine harvester, especially while it is turning, but due to the rapid turning of robot combine harvesters, its inertial measurement unit gives a gyro measurement bias that causes heading drift. Our research goal is to estimate the absolute heading of robot combine harvesters by compensating this gyro measurement bias during non-linear turning maneuvers. A sensor fusion method like the extended Kalman filter combined with the tracked combine harvester dynamic model and sensor measurements was used to estimate the absolute heading of a robot combine harvester. Circular, sinusoidal and concave shapes were used to evaluate the estimated heading produced by the sensor fusion method. The results indicate that the estimated heading is better than measured heading which was calculated from the integration of yaw rate gyro measurements, and the root mean square errors (RMSEs for estimated headings are smaller than the measured headings. In practics, the target of this paper is thus the estimation of a heading or absolute heading that is bias compensated, and can be further used to calculate the exact crop periphery for automatic path planning of robot combine harvesters.

An advanced semiautonomous robotic system for hazardous response work for decontamination and decommissioning

International Nuclear Information System (INIS)

Crane, C.; Tulenko, J.F.

1990-01-01

The articulated transporter/manipulator system (ATMS) under development by the University of Florida (UF) with Odetics Corporation as lead subcontractor will be able to manipulate through obstructed areas. Since 1987, the Advanced Technology Division of the US Department of Energy has sponsored a university team composed of the UF, University of Michigan, University of Tennessee, and the University of Texas under the leadership of the Oak Ridge National Laboratory to pursue innovative robotics research leading to the development of advanced robotic systems. The UF has the task of developing the ATMS innovative transport system. As part of this task, UF has been focusing on developing horizontal and external navigation algorithms that carry out ongoing ATMS autonomous path planning. The flexibility of the ATMS is also being demonstrated as a surveillance/maintenance robot for the PRISM reactor. The ATMS has demonstrated that it can carry out autonomous planning responding both to obstacles and set operating levels. The ATMS also has demonstrated that it has sufficient flexibility to serve in a surveillance/maintenance mode. Work is progressing on developing the hardware to deliver the mechanical capabilities demonstrated by simulated robotic system

Time-optimal path planning in uncertain flow fields using ensemble method

KAUST Repository

Wang, Tong; Le Maitre, Olivier; Hoteit, Ibrahim; Knio, Omar

2016-01-01

the performance of sampling strategy, and develop insight into extensions dealing with regional or general circulation models. In particular, the ensemble method enables us to perform a statistical analysis of travel times, and consequently develop a path planning

Next-generation robotic surgery--from the aspect of surgical robots developed by industry.

Science.gov (United States)

Nakadate, Ryu; Arata, Jumpei; Hashizume, Makoto

2015-02-01

At present, much of the research conducted worldwide focuses on extending the ability of surgical robots. One approach is to extend robotic dexterity. For instance, accessibility and dexterity of the surgical instruments remains the largest issue for reduced port surgery such as single port surgery or natural orifice surgery. To solve this problem, a great deal of research is currently conducted in the field of robotics. Enhancing the surgeon's perception is an approach that uses advanced sensor technology. The real-time data acquired through the robotic system combined with the data stored in the robot (such as the robot's location) provide a major advantage. This paper aims at introducing state-of-the-art products and pre-market products in this technological advancement, namely the robotic challenge in extending dexterity and hopefully providing the path to robotic surgery in the near future.

A flexible 3D laser scanning system using a robotic arm

Science.gov (United States)

Fei, Zixuan; Zhou, Xiang; Gao, Xiaofei; Zhang, Guanliang

2017-06-01

In this paper, we present a flexible 3D scanning system based on a MEMS scanner mounted on an industrial arm with a turntable. This system has 7-degrees of freedom and is able to conduct a full field scan from any angle, suitable for scanning object with the complex shape. The existing non-contact 3D scanning system usually uses laser scanner that projects fixed stripe mounted on the Coordinate Measuring Machine (CMM) or industrial robot. These existing systems can't perform path planning without CAD models. The 3D scanning system presented in this paper can scan the object without CAD models, and we introduced this path planning method in the paper. We also propose a practical approach to calibrating the hand-in-eye system based on binocular stereo vision and analyzes the errors of the hand-eye calibration.

Mission Activity Planning for Humans and Robots on the Moon

Science.gov (United States)

Weisbin, C.; Shelton, K.; Lincoln, W.; Elfes, A.; Smith, J.H.; Mrozinski, J.; Hua, H.; Adumitroaie, V.; Silberg, R.

2008-01-01

A series of studies is conducted to develop a systematic approach to optimizing, both in terms of the distribution and scheduling of tasks, scenarios in which astronauts and robots accomplish a group of activities on the Moon, given an objective function (OF) and specific resources and constraints. An automated planning tool is developed as a key element of this optimization system.

Friendly network robotics; Friendly network robotics

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

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

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot

Directory of Open Access Journals (Sweden)

Xingguang Duan

2018-01-01

Full Text Available In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, “kinematics + optics” hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning.

Modelling and Experiment Based on a Navigation System for a Cranio-Maxillofacial Surgical Robot

Science.gov (United States)

Duan, Xingguang; Gao, Liang; Li, Jianxi; Li, Haoyuan; Guo, Yanjun

2018-01-01

In view of the characteristics of high risk and high accuracy in cranio-maxillofacial surgery, we present a novel surgical robot system that can be used in a variety of surgeries. The surgical robot system can assist surgeons in completing biopsy of skull base lesions, radiofrequency thermocoagulation of the trigeminal ganglion, and radioactive particle implantation of skull base malignant tumors. This paper focuses on modelling and experimental analyses of the robot system based on navigation technology. Firstly, the transformation relationship between the subsystems is realized based on the quaternion and the iterative closest point registration algorithm. The hand-eye coordination model based on optical navigation is established to control the end effector of the robot moving to the target position along the planning path. The closed-loop control method, “kinematics + optics” hybrid motion control method, is presented to improve the positioning accuracy of the system. Secondly, the accuracy of the system model was tested by model experiments. And the feasibility of the closed-loop control method was verified by comparing the positioning accuracy before and after the application of the method. Finally, the skull model experiments were performed to evaluate the function of the surgical robot system. The results validate its feasibility and are consistent with the preoperative surgical planning. PMID:29599948

Optimal Trajectory Tracking Control for a Wheeled Mobile Robot Using Fractional Order PID Controller

Directory of Open Access Journals (Sweden)

Ameer L. Saleh

2018-02-01

Full Text Available This paper present an optimal Fractional Order PID (FOPID controller based on Particle Swarm Optimization (PSO for controlling the trajectory tracking of Wheeled Mobile Robot(WMR.The issue of trajectory tracking with given a desired reference velocity is minimized to get the distance and deviation angle equal to zero, to realize the objective of trajectory tracking a two FOPID controllers are used for velocity control and azimuth control to implement the trajectory tracking control. A path planning and path tracking methodologies are used to give different desired tracking trajectories.  PSO algorithm is using to find the optimal parameters of FOPID controllers. The kinematic and dynamic models of wheeled mobile robot for desired trajectory tracking with PSO algorithm are simulated in Simulink-Matlab. Simulation results show that the optimal FOPID controllers are more effective and has better dynamic performance than the conventional methods.

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

Energy Technology Data Exchange (ETDEWEB)

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

2004-03-29

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

Image Based Solution to Occlusion Problem for Multiple Robots Navigation

Directory of Open Access Journals (Sweden)

Taj Mohammad Khan

2012-04-01

Full Text Available In machine vision, occlusions problem is always a challenging issue in image based mapping and navigation tasks. This paper presents a multiple view vision based algorithm for the development of occlusion-free map of the indoor environment. The map is assumed to be utilized by the mobile robots within the workspace. It has wide range of applications, including mobile robot path planning and navigation, access control in restricted areas, and surveillance systems. We used wall mounted fixed camera system. After intensity adjustment and background subtraction of the synchronously captured images, the image registration was performed. We applied our algorithm on the registered images to resolve the occlusion problem. This technique works well even in the existence of total occlusion for a longer period.

Design and Implementation of Fire Extinguisher Robot with Robotic Arm

Directory of Open Access Journals (Sweden)

Memon Abdul Waris

2018-01-01

Full Text Available Robot is a device, which performs human task or behave like a human-being. It needs expertise skills and complex programming to design. For designing a fire fighter robot, many sensors and motors were used. User firstly send robot to an affected area, to get live image of the field with the help of mobile camera via Wi-Fi using IP camera application to laptop. If any signs of fire shown in image, user direct robot in that particular direction for confirmation. Fire sensor and temperature sensor detects and measures the reading, after confirmation robot sprinkle water on affected field. During extinguish process if any obstacle comes in between the prototype and the affected area the ultrasonic sensor detects the obstacle, in response the robotic arm moves to pick and place that obstacle to another location for clearing the path. Meanwhile if any poisonous gas is present, the gas sensor detects and indicates by making alarm.

Evaluation of a New Backtrack Free Path Planning Algorithm for Manipulators

Science.gov (United States)

Islam, Md. Nazrul; Tamura, Shinsuke; Murata, Tomonari; Yanase, Tatsuro

This paper evaluates a newly proposed backtrack free path planning algorithm (BFA) for manipulators. BFA is an exact algorithm, i.e. it is resolution complete. Different from existing resolution complete algorithms, its computation time and memory space are proportional to the number of arms. Therefore paths can be calculated within practical and predetermined time even for manipulators with many arms, and it becomes possible to plan complicated motions of multi-arm manipulators in fully automated environments. The performance of BFA is evaluated for 2-dimensional environments while changing the number of arms and obstacle placements. Its performance under locus and attitude constraints is also evaluated. Evaluation results show that the computation volume of the algorithm is almost the same as the theoretical one, i.e. it increases linearly with the number of arms even in complicated environments. Moreover BFA achieves the constant performance independent of environments.

Planning of optimal work path for minimizing exposure dose during radiation work in radwaste storage

International Nuclear Information System (INIS)

Kim, Yoon Hyuk; Park, Won Man; Kim, Kyung Soo; Whang, Joo Ho

2005-01-01

Since the safety of nuclear power plant has been becoming a big social issue, the exposure dose of radiation for workers has been one of the important factors concerning the safety problem. The existing calculation methods of radiation dose used in the planning of radiation work assume that dose rate dose not depend on the location within a work space, thus the variation of exposure dose by different work path is not considered. In this study, a modified numerical method was presented to estimate the exposure dose during radiation work in radwaste storage considering the effects of the distance between a worker and sources. And a new numerical algorithm was suggested to search the optimal work path minimizing the exposure dose in pre-defined work space with given radiation sources. Finally, a virtual work simulation program was developed to visualize the exposure dose of radiation during radiation works in radwaste storage and provide the capability of simulation for work planning. As a numerical example, a test radiation work was simulated under given space and two radiation sources, and the suggested optimal work path was compared with three predefined work paths. The optimal work path obtained in the study could reduce the exposure dose for the given test work. Based on the results, the developed numerical method and simulation program could be useful tools in the planning of radiation work

Teaching Joint-Level Robot Programming with a New Robotics Software Tool

Directory of Open Access Journals (Sweden)

Fernando Gonzalez

2017-12-01

Full Text Available With the rising popularity of robotics in our modern world there is an increase in the number of engineering programs that offer the basic Introduction to Robotics course. This common introductory robotics course generally covers the fundamental theory of robotics including robot kinematics, dynamics, differential movements, trajectory planning and basic computer vision algorithms commonly used in the field of robotics. Joint programming, the task of writing a program that directly controls the robot’s joint motors, is an activity that involves robot kinematics, dynamics, and trajectory planning. In this paper, we introduce a new educational robotics tool developed for teaching joint programming. The tool allows the student to write a program in a modified C language that controls the movement of the arm by controlling the velocity of each joint motor. This is a very important activity in the robotics course and leads the student to gain knowledge of how to build a robotic arm controller. Sample assignments are presented for different levels of difficulty.

2D navigation and pilotage of an autonomous mobile robot

International Nuclear Information System (INIS)

Favre, Patrick

1989-01-01

The contribution of this thesis deals with the navigation and the piloting of an autonomous robot, in a known or weakly known environment of dimension two without constraints. This leads to generate an optimal path to a given goal and then to compute the commands to follow this path. Several constraints are taken into account (obstacles, geometry and kinematic of the robot, dynamic effects). The first part defines the problem and presents the state of the art. The three following parts present a set of complementary solutions according to the knowledge level of the environment and to the space constraints: - Case of a known environment: generation and following of a trajectory with respect to given path points. - Case of a weakly known environment: coupling of a command module interacting with the environment perception, and a path planner. This allows a fast motion of the robot. - Case of a constrained environment: planner enabling the taking into account of many constraints as the robot's shape, turning radius limitation, backward motion and orientation. (author) [fr

Roles and Self-Reconfigurable Robots

DEFF Research Database (Denmark)

Dvinge, Nicolai; Schultz, Ulrik Pagh; Christensen, David Johan

2007-01-01

A self-reconfigurable robot is a robotic device that can change its own shape. Self-reconfigurable robots are commonly built from multiple identical modules that can manipulate each other to change the shape of the robot. The robot can also perform tasks such as locomotion without changing shape......., significantly simplifying the task of programming self-reconfigurable robots. Our language fully supports programming the ATRON self-reconfigurable robot, and has been used to implement several controllers running both on the physical modules and in simulation.......A self-reconfigurable robot is a robotic device that can change its own shape. Self-reconfigurable robots are commonly built from multiple identical modules that can manipulate each other to change the shape of the robot. The robot can also perform tasks such as locomotion without changing shape....... Programming a modular, self-reconfigurable robot is however a complicated task: the robot is essentially a real-time, distributed embedded system, where control and communication paths often are tightly coupled to the current physical configuration of the robot. To facilitate the task of programming modular...

Presentation robot Advee

Czech Academy of Sciences Publication Activity Database

Krejsa, Jiří; Věchet, Stanislav; Hrbáček, J.; Ripel, T.; Ondroušek, V.; Hrbáček, R.; Schreiber, P.

2012-01-01

Roč. 18, 5/6 (2012), s. 307-322 ISSN 1802-1484 Institutional research plan: CEZ:AV0Z20760514 Keywords : mobile robot * human - robot interface * localization Subject RIV: JD - Computer Applications, Robot ics

Planetary rovers robotic exploration of the solar system

CERN Document Server

Ellery, Alex

2016-01-01

The increasing adoption of terrain mobility – planetary rovers – for the investigation of planetary surfaces emphasises their central importance in space exploration. This imposes a completely new set of technologies and methodologies to the design of such spacecraft – and planetary rovers are indeed, first and foremost, spacecraft. This introduces vehicle engineering, mechatronics, robotics, artificial intelligence and associated technologies to the spacecraft engineer’s repertoire of skills. Planetary Rovers is the only book that comprehensively covers these aspects of planetary rover engineering and more. The book: • discusses relevant planetary environments to rover missions, stressing the Moon and Mars; • includes a brief survey of previous rover missions; • covers rover mobility, traction and control systems; • stresses the importance of robotic vision in rovers for both navigation and science; • comprehensively covers autonomous navigation, path planning and multi-rover formations on ...

Study of Robust Position Recognition System of a Mobile Robot Using Multiple Cameras and Absolute Space Coordinates

Energy Technology Data Exchange (ETDEWEB)

Mo, Se Hyun [Amotech, Seoul (Korea, Republic of); Jeon, Young Pil [Samsung Electronics Co., Ltd. Suwon (Korea, Republic of); Park, Jong Ho [Seonam Univ., Namwon (Korea, Republic of); Chong, Kil To [Chon-buk Nat' 1 Univ., Junju (Korea, Republic of)

2017-07-15

With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.

Study of Robust Position Recognition System of a Mobile Robot Using Multiple Cameras and Absolute Space Coordinates

International Nuclear Information System (INIS)

Mo, Se Hyun; Jeon, Young Pil; Park, Jong Ho; Chong, Kil To

2017-01-01

With the development of ICT technology, the indoor utilization of robots is increasing. Research on transportation, cleaning, guidance robots, etc., that can be used now or increase the scope of future use will be advanced. To facilitate the use of mobile robots in indoor spaces, the problem of self-location recognition is an important research area to be addressed. If an unexpected collision occurs during the motion of a mobile robot, the position of the mobile robot deviates from the initially planned navigation path. In this case, the mobile robot needs a robust controller that enables the mobile robot to accurately navigate toward the goal. This research tries to address the issues related to self-location of the mobile robot. A robust position recognition system was implemented; the system estimates the position of the mobile robot using a combination of encoder information of the mobile robot and the absolute space coordinate transformation information obtained from external video sources such as a large number of CCTVs installed in the room. Furthermore, vector field histogram method of the pass traveling algorithm of the mobile robot system was applied, and the results of the research were confirmed after conducting experiments.

Interactive animated displayed of man-controlled and autonomous robots

International Nuclear Information System (INIS)

Crane, C.D. III; Duffy, J.

1986-01-01

An interactive computer graphics program has been developed which allows an operator to more readily control robot motions in two distinct modes; viz., man-controlled and autonomous. In man-controlled mode, the robot is guided by a joystick or similar device. As the robot moves, actual joint angle information is measured and supplied to a graphics system which accurately duplicates the robot motion. Obstacles are placed in the actual and animated workspace and the operator is warned of imminent collisions by sight and sound via the graphics system. Operation of the system in man-controlled mode is shown. In autonomous mode, a collision-free path between specified points is obtained by previewing robot motions on the graphics system. Once a satisfactory path is selected, the path characteristics are transmitted to the actual robot and the motion is executed. The telepresence system developed at the University of Florida has been successful in demonstrating that the concept of controlling a robot manipulator with the aid of an interactive computer graphics system is feasible and practical. The clarity of images coupled with real-time interaction and real-time determination of imminent collision with obstacles has resulted in improved operator performance. Furthermore, the ability for an operator to preview and supervise autonomous operations is a significant attribute when operating in a hazardous environment

Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles

Science.gov (United States)

Hu, Xuemin; Chen, Long; Tang, Bo; Cao, Dongpu; He, Haibo

2018-02-01

This paper presents a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles. The proposed path planning method determines not only an optimal path, but also the appropriate acceleration and speed for a vehicle. In this method, we first construct a center line from a set of predefined waypoints, which are usually obtained from a lane-level map. A series of path candidates are generated by the arc length and offset to the center line in the s - ρ coordinate system. Then, all of these candidates are converted into Cartesian coordinates. The optimal path is selected considering the total cost of static safety, comfortability, and dynamic safety; meanwhile, the appropriate acceleration and speed for the optimal path are also identified. Various types of roads, including single-lane roads and multi-lane roads with static and moving obstacles, are designed to test the proposed method. The simulation results demonstrate the effectiveness of the proposed method, and indicate its wide practical application to autonomous driving.

Investigation In Two Wheels Mobile Robot Movement: Stability and Motion Paths

Directory of Open Access Journals (Sweden)

Abdulrahman A.A. Emhemed

2013-01-01

Full Text Available This paper deals with the problem of dynamic modelling of inspection robot two wheels. Fuzzy controller based on robotics techniques for optimize of an inspection stability. The target is to enhancement of robot direction and avoids the obstacles. To find collision free area, distance-sensors such as ultra-sonic sensors and laser scanners or vision systems are usually employed. The distance-sensors offer only distance information between mobile robots and obstacles. Also the target are shown can be reached by different directions. The fuzzy logic controller is effect to avoid the abstacles and get ideal direction to “the target box”.

Robotics in rehabilitation: technology as destiny.

Science.gov (United States)

Stein, Joel

2012-11-01

Robotic aids for rehabilitation hold considerable promise but have not yet achieved widespread clinical adoption. Barriers to adoption include the limited data on efficacy, the single-purpose design of existing robots, financial considerations, and clinician lack of familiarity with this technology. Although the path forward to clinical adoption may be slow and have several false starts, the labor-saving aspect of robotic technology will ultimately ensure its adoption.

Heuristic methods for shared backup path protection planning

DEFF Research Database (Denmark)

Haahr, Jørgen Thorlund; Stidsen, Thomas Riis; Zachariasen, Martin

2012-01-01

schemes are employed. In contrast to manual intervention, automatic protection schemes such as Shared Backup Path Protection (SBPP) can recover from failure quickly and efficiently. SBPP is a simple but efficient protection scheme that can be implemented in backbone networks with technology available...... present heuristic algorithms and lower bound methods for the SBPP planning problem. Experimental results show that the heuristic algorithms are able to find good quality solutions in minutes. A solution gap of less than 3.5% was achieved for more than half of the benchmark instances (and a gap of less...

Dynamic whole-body robotic manipulation

Science.gov (United States)

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

2013-05-01

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

Towards Using a Generic Robot as Training Partner

DEFF Research Database (Denmark)

Sørensen, Anders Stengaard; Savarimuthu, Thiusius Rajeeth; Nielsen, Jacob

2014-01-01

In this paper, we demonstrate how a generic industrial robot can be used as a training partner, for upper limb training. The motion path and human/robot interaction of a non-generic upper-arm training robot is transferred to a generic industrial robot arm, and we demonstrate that the robot arm can...... implement the same type of interaction, but can expand the training regime to include both upper arm and shoulder training. We compare the generic robot to two affordable but custom-built training robots, and outline interesting directions for future work based on these training robots....

Bio-Inspired Genetic Algorithms with Formalized Crossover Operators for Robotic Applications.

Science.gov (United States)

Zhang, Jie; Kang, Man; Li, Xiaojuan; Liu, Geng-Yang

2017-01-01

Genetic algorithms are widely adopted to solve optimization problems in robotic applications. In such safety-critical systems, it is vitally important to formally prove the correctness when genetic algorithms are applied. This paper focuses on formal modeling of crossover operations that are one of most important operations in genetic algorithms. Specially, we for the first time formalize crossover operations with higher-order logic based on HOL4 that is easy to be deployed with its user-friendly programing environment. With correctness-guaranteed formalized crossover operations, we can safely apply them in robotic applications. We implement our technique to solve a path planning problem using a genetic algorithm with our formalized crossover operations, and the results show the effectiveness of our technique.

Tree Climbing Robot Design, Kinematics and Motion Planning

CERN Document Server

Lam, Tin Lun

2012-01-01

Climbing robot is a challenging research topic that has gained much attention from researchers. Most of the robots reported in the literature are designed to climb on manmade structures, but seldom robots are designed for climbing natural environment such as trees. Trees and manmade structures are very different in nature. It brings different aspects of technical challenges to the robot design. In this book, you can find a collection of the cutting edge technologies in the field of tree-climbing robot and the ways that animals climb. It provides a valuable reference for robot designers to select appropriate climbing methods in designing tree-climbing robots for specific purposes. Based on the study, a novel bio-inspired tree-climbing robot with several breakthrough performances has been developed and presents in this book. It is capable of performing various actions that is impossible in the state-of-the-art tree-climbing robots, such as moving between trunk and branches. This book also proposes several appro...

A PSO-Optimized Reciprocal Velocity Obstacles Algorithm for Navigation of Multiple Mobile Robots

Directory of Open Access Journals (Sweden)

Ziyad Allawi

2015-03-01

Full Text Available In this paper, a new optimization method for the Reciprocal Velocity Obstacles (RVO is proposed. It uses the well-known Particle Swarm Optimization (PSO for navigation control of multiple mobile robots with kinematic constraints. The RVO is used for collision avoidance between the robots, while PSO is used to choose the best path for the robot maneuver to avoid colliding with other robots and to get to its goal faster. This method was applied on 24 mobile robots facing each other. Simulation results have shown that this method outperforms the ordinary RVO when the path is heuristically chosen.

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Robot motion planning (RMP) develops a precise path between start and goal points for mobile robots in an unknown environment. RMP is a complex task when it needs to be planned for a group of robots in a coordinated environment with leader–follower relationship. The planned path might change depending upon ...

Time optimal paths for high speed maneuvering

Energy Technology Data Exchange (ETDEWEB)

Reister, D.B.; Lenhart, S.M.

1993-01-01

Recent theoretical results have completely solved the problem of determining the minimum length path for a vehicle with a minimum turning radius moving from an initial configuration to a final configuration. Time optimal paths for a constant speed vehicle are a subset of the minimum length paths. This paper uses the Pontryagin maximum principle to find time optimal paths for a constant speed vehicle. The time optimal paths consist of sequences of axes of circles and straight lines. The maximum principle introduces concepts (dual variables, bang-bang solutions, singular solutions, and transversality conditions) that provide important insight into the nature of the time optimal paths. We explore the properties of the optimal paths and present some experimental results for a mobile robot following an optimal path.

Time-optimal path planning in uncertain flow fields using ensemble method

KAUST Repository

Wang, Tong

2016-01-06

An ensemble-based approach is developed to conduct time-optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where a set deterministic predictions is used to model and quantify uncertainty in the predictions. In the operational setting, much about dynamics, topography and forcing of the ocean environment is uncertain, and as a result a single path produced by a model simulation has limited utility. To overcome this limitation, we rely on a finitesize ensemble of deterministic forecasts to quantify the impact of variability in the dynamics. The uncertainty of flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each the resulting realizations of the uncertain current field, we predict the optimal path by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of sampling strategy, and develop insight into extensions dealing with regional or general circulation models. In particular, the ensemble method enables us to perform a statistical analysis of travel times, and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.

Hybrid path planning for non-holonomic autonomous vehicles: An experimental evaluation

NARCIS (Netherlands)

Esposto, F.; Goos, J.; Teerhuis, A.; Alirezaei, M.

2017-01-01

Path planning of an autonomous vehicle as a non-holonomic system is an essential part for many automated driving applications. Parking a car into a parking lot and maneuvering it through a narrow corridor would be a common driving scenarios in an urban environment. In this study a hybrid approach

Head Pose Estimation Using Multilinear Subspace Analysis for Robot Human Awareness

Science.gov (United States)

Ivanov, Tonislav; Matthies, Larry; Vasilescu, M. Alex O.

2009-01-01

Mobile robots, operating in unconstrained indoor and outdoor environments, would benefit in many ways from perception of the human awareness around them. Knowledge of people's head pose and gaze directions would enable the robot to deduce which people are aware of the its presence, and to predict future motions of the people for better path planning. To make such inferences, requires estimating head pose on facial images that are combination of multiple varying factors, such as identity, appearance, head pose, and illumination. By applying multilinear algebra, the algebra of higher-order tensors, we can separate these factors and estimate head pose regardless of subject's identity or image conditions. Furthermore, we can automatically handle uncertainty in the size of the face and its location. We demonstrate a pipeline of on-the-move detection of pedestrians with a robot stereo vision system, segmentation of the head, and head pose estimation in cluttered urban street scenes.

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †.

Science.gov (United States)

Cai, Wenyu; Zhang, Meiyan; Zheng, Yahong Rosa

2017-07-11

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X - Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.

Optimal trajectory planning of free-floating space manipulator using differential evolution algorithm

Science.gov (United States)

Wang, Mingming; Luo, Jianjun; Fang, Jing; Yuan, Jianping

2018-03-01

The existence of the path dependent dynamic singularities limits the volume of available workspace of free-floating space robot and induces enormous joint velocities when such singularities are met. In order to overcome this demerit, this paper presents an optimal joint trajectory planning method using forward kinematics equations of free-floating space robot, while joint motion laws are delineated with application of the concept of reaction null-space. Bézier curve, in conjunction with the null-space column vectors, are applied to describe the joint trajectories. Considering the forward kinematics equations of the free-floating space robot, the trajectory planning issue is consequently transferred to an optimization issue while the control points to construct the Bézier curve are the design variables. A constrained differential evolution (DE) scheme with premature handling strategy is implemented to find the optimal solution of the design variables while specific objectives and imposed constraints are satisfied. Differ from traditional methods, we synthesize null-space and specialized curve to provide a novel viewpoint for trajectory planning of free-floating space robot. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) kinematically redundant manipulator mounted on a free-floating spacecraft and demonstrate the feasibility and effectiveness of the proposed method.

Optimizing a mobile robot control system using GPU acceleration

Science.gov (United States)

Tuck, Nat; McGuinness, Michael; Martin, Fred

2012-01-01

This paper describes our attempt to optimize a robot control program for the Intelligent Ground Vehicle Competition (IGVC) by running computationally intensive portions of the system on a commodity graphics processing unit (GPU). The IGVC Autonomous Challenge requires a control program that performs a number of different computationally intensive tasks ranging from computer vision to path planning. For the 2011 competition our Robot Operating System (ROS) based control system would not run comfortably on the multicore CPU on our custom robot platform. The process of profiling the ROS control program and selecting appropriate modules for porting to run on a GPU is described. A GPU-targeting compiler, Bacon, is used to speed up development and help optimize the ported modules. The impact of the ported modules on overall performance is discussed. We conclude that GPU optimization can free a significant amount of CPU resources with minimal effort for expensive user-written code, but that replacing heavily-optimized library functions is more difficult, and a much less efficient use of time.

Autonomous Robot Navigation In Public Nature Park

DEFF Research Database (Denmark)

Andersen, Jens Christian; Andersen, Nils Axel; Ravn, Ole

2005-01-01

This extended abstract describes a project to make a robot travel autonomously across a public nature park. The challenge is to detect and follow the right path across junctions and open squares avoiding people and obstacles. The robot is equipped with a laser scanner, a (low accuracy) GPS, wheel...

Lazy motion planning for robotic manipulators

NARCIS (Netherlands)

Andrien, A.R.P.; van de Molengraft, M.J.G.; Bruyninckx, H.P.J.

2017-01-01

Robotic manipulators are making a shift towards mobile bases in both industry and domestic environments, which puts high demands on efficient use of the robot’s limited energy resources. In this work, the problem of reducing energy usage of a robot manipulator during a task is investigated. We

Implementation of a Multi-Robot Coverage Algorithm on a Two-Dimensional, Grid-Based Environment

Science.gov (United States)

2017-06-01

different approaches is based on “ behavior -based” versus “system theory based” approaches to the problem. 1. Behavior –Based Approach Most behavior -based...otherwise, it performs the behavior of IG. This kind of algorithm could be classified as a system theory based approach since the change in the...systems, robot agents are likely to take over mine countermeasure (MCM) missions one day. The path planning coverage algorithm is an essential topic for

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †

Directory of Open Access Journals (Sweden)

Wenyu Cai

2017-07-01

Full Text Available This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP problem and the Genetic Algorithm (GA is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB or Tour Length Balance (TLB constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X − Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.

A Distributed Framework for Real Time Path Planning in Practical Multi-agent Systems

KAUST Repository

Abdelkader, Mohamed; Jaleel, Hassan; Shamma, Jeff S.

2017-01-01

We present a framework for distributed, energy efficient, and real time implementable algorithms for path planning in multi-agent systems. The proposed framework is presented in the context of a motivating example of capture the flag which

Development and Performance Evaluation of Image-Based Robotic Waxing System for Detailing Automobiles.

Science.gov (United States)

Lin, Chi-Ying; Hsu, Bing-Cheng

2018-05-14

Waxing is an important aspect of automobile detailing, aimed at protecting the finish of the car and preventing rust. At present, this delicate work is conducted manually due to the need for iterative adjustments to achieve acceptable quality. This paper presents a robotic waxing system in which surface images are used to evaluate the quality of the finish. An RGB-D camera is used to build a point cloud that details the sheet metal components to enable path planning for a robot manipulator. The robot is equipped with a multi-axis force sensor to measure and control the forces involved in the application and buffing of wax. Images of sheet metal components that were waxed by experienced car detailers were analyzed using image processing algorithms. A Gaussian distribution function and its parameterized values were obtained from the images for use as a performance criterion in evaluating the quality of surfaces prepared by the robotic waxing system. Waxing force and dwell time were optimized using a mathematical model based on the image-based criterion used to measure waxing performance. Experimental results demonstrate the feasibility of the proposed robotic waxing system and image-based performance evaluation scheme.

Sensor module design and forward and inverse kinematics analysis of 6-DOF sorting transferring robot

Science.gov (United States)

Zhou, Huiying; Lin, Jiajian; Liu, Lei; Tao, Meng

2017-09-01

To meet the demand of high strength express sorting, it is significant to design a robot with multiple degrees of freedom that can sort and transfer. This paper uses infrared sensor, color sensor and pressure sensor to receive external information, combine the plan of motion path in advance and the feedback information from the sensors, then write relevant program. In accordance with these, we can design a 6-DOF robot that can realize multi-angle seizing. In order to obtain characteristics of forward and inverse kinematics, this paper describes the coordinate directions and pose estimation by the D-H parameter method and closed solution. On the basis of the solution of forward and inverse kinematics, geometric parameters of links and link parameters are optimized in terms of application requirements. In this way, this robot can identify route, sort and transfer.

Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

Science.gov (United States)

Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao

2015-01-01

This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…

Complete coverage path planning of a random polygon - A FroboMind component

DEFF Research Database (Denmark)

Aslund, Sebastian; Jensen, Kjeld; Jørgensen, Rasmus Nyholm

solution where all the steps in the process is included: Segmentation of a data set, creation of a configuration space, decomposition of a polygon, global and local path planning. To achieve this, a series of known algorithms are used including some tweaks and improvements to create a solid foundation...

An industrial robot singular trajectories planning based on graphs and neural networks

Science.gov (United States)

Łęgowski, Adrian; Niezabitowski, Michał

2016-06-01

Singular trajectories are rarely used because of issues during realization. A method of planning trajectories for given set of points in task space with use of graphs and neural networks is presented. In every desired point the inverse kinematics problem is solved in order to derive all possible solutions. A graph of solutions is made. The shortest path is determined to define required nodes in joint space. Neural networks are used to define the path between these nodes.

A novel algorithm for solving optimal path planning problems based on parametrization method and fuzzy aggregation

International Nuclear Information System (INIS)

Zamirian, M.; Kamyad, A.V.; Farahi, M.H.

2009-01-01

In this Letter a new approach for solving optimal path planning problems for a single rigid and free moving object in a two and three dimensional space in the presence of stationary or moving obstacles is presented. In this approach the path planning problems have some incompatible objectives such as the length of path that must be minimized, the distance between the path and obstacles that must be maximized and etc., then a multi-objective dynamic optimization problem (MODOP) is achieved. Considering the imprecise nature of decision maker's (DM) judgment, these multiple objectives are viewed as fuzzy variables. By determining intervals for the values of these fuzzy variables, flexible monotonic decreasing or increasing membership functions are determined as the degrees of satisfaction of these fuzzy variables on their intervals. Then, the optimal path planning policy is searched by maximizing the aggregated fuzzy decision values, resulting in a fuzzy multi-objective dynamic optimization problem (FMODOP). Using a suitable t-norm, the FMODOP is converted into a non-linear dynamic optimization problem (NLDOP). By using parametrization method and some calculations, the NLDOP is converted into the sequence of conventional non-linear programming problems (NLPP). It is proved that the solution of this sequence of the NLPPs tends to a Pareto optimal solution which, among other Pareto optimal solutions, has the best satisfaction of DM for the MODOP. Finally, the above procedure as a novel algorithm integrating parametrization method and fuzzy aggregation to solve the MODOP is proposed. Efficiency of our approach is confirmed by some numerical examples.

Supervised Autonomy for Exploration and Mobile Manipulation in Rough Terrain with a Centaur-like Robot

Directory of Open Access Journals (Sweden)

Max Schwarz

2016-10-01

Full Text Available Planetary exploration scenarios illustrate the need for autonomous robots that are capable to operate in unknown environments without direct human interaction. At the DARPA Robotics Challenge, we demonstrated that our Centaur-like mobile manipulation robot Momaro can solve complex tasks when teleoperated. Motivated by the DLR SpaceBot Cup 2015, where robots should explore a Mars-like environment, find and transport objects, take a soil sample, and perform assembly tasks, we developed autonomous capabilities for Momaro. Our robot perceives and maps previously unknown, uneven terrain using a 3D laser scanner. Based on the generated height map, we assess drivability, plan navigation paths, and execute them using the omnidirectional drive. Using its four legs, the robot adapts to the slope of the terrain. Momaro perceives objects with cameras, estimates their pose, and manipulates them with its two arms autonomously. For specifying missions, monitoring mission progress, on-the-fly reconfiguration, and teleoperation, we developed a ground station with suitable operator interfaces. To handle network communication interruptions and latencies between robot and ground station, we implemented a robust network layer for the ROS middleware. With the developed system, our team NimbRo Explorer solved all tasks of the DLR SpaceBot Camp 2015. We also discuss the lessons learned from this demonstration.

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

Path Planning Software and Graphics Interface for an Autonomous Vehicle, Accounting for Terrain Features

National Research Council Canada - National Science Library

Hurezeanu, Vlad

2000-01-01

.... This vehicle performs tasks to include surveying fields, laying mines, and teleoperation. The capability of the vehicle will be increased if its supporting software plans paths that take into account the terrain features...

Accuracy and speed of robotic assisted needle interventions using a modern cone beam computed tomography intervention suite: a phantom study