Results 1 - 10
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220
Probabilistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces
- IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION
, 1996
"... A new motion planning method for robots in static workspaces is presented. This method proceeds in two phases: a learning phase and a query phase. In the learning phase, a probabilistic roadmap is constructed and stored as a graph whose nodes correspond to collision-free configurations and whose edg ..."
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Cited by 1277 (120 self)
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A new motion planning method for robots in static workspaces is presented. This method proceeds in two phases: a learning phase and a query phase. In the learning phase, a probabilistic roadmap is constructed and stored as a graph whose nodes correspond to collision-free configurations and whose edges correspond to feasible paths between these configurations. These paths are computed using a simple and fast local planner. In the query phase, any given start and goal configurations of the robot are connected to two nodes of the roadmap; the roadmap is then searched for a path joining these two nodes. The method is general and easy to implement. It can be applied to virtually any type of holonomic robot. It requires selecting certain parameters (e.g., the duration of the learning phase) whose values depend on the scene, that is the robot and its workspace. But these values turn out to be relatively easy to choose, Increased efficiency can also be achieved by tailoring some components of the method (e.g., the local planner) to the considered robots. In this paper the method is applied to planar articulated robots with many degrees of freedom. Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (=150 MIPS), after learning for relatively short periods of time (a few dozen seconds)
Coverage Control for Mobile Sensing Networks
, 2002
"... This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functio ..."
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Cited by 582 (49 self)
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This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.
Robot Motion Planning: A Distributed Representation Approach
, 1991
"... We propose a new approach to robot path planning that consists of building and searching a graph connecting the local minima of a potential function defined over the robot’s configuration space. A planner based on this approach has been implemented. This planner is considerably faster than previous ..."
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Cited by 402 (26 self)
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We propose a new approach to robot path planning that consists of building and searching a graph connecting the local minima of a potential function defined over the robot’s configuration space. A planner based on this approach has been implemented. This planner is considerably faster than previous path planners and solves problems for robots with many more degrees of freedom (DOFs). The power of the planner derives both from the "good " properties of the potential function and from the efficiency of the techniques used to escape the local minima of this function. The most powerful of these techniques is a Monte Carlo technique that escapes local minima by executing Brownian motions. The overall approach is made possible by the systematic use of distributed representations (bitmaps) for the robot’s work space and configuration space. We have experimented with the planner using several computer-simulated robots, including rigid objects with 3 DOFs (in 2D work space) and 6 DOFs (in 3D work space) and manipulator arms with 8, 10, and 31 DOFs (in 2D and 3D work spaces). Some of the most significant experiments are reported in this article.
Cooperative mobile robotics: Antecedents and directions
, 1995
"... There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting collective behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric pr ..."
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Cited by 385 (3 self)
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There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting collective behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of collective robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.
Motion Planning in Dynamic Environments using Velocity Obstacles
- International Journal of Robotics Research
, 1998
"... Abstract!llis paper presents a new approach for rot)ot]notion planning in dynamic environ-ments, based on the concept of Velocity Obstacle.,4 velocity obstacle defines the set of robot velocities that would result in a collision between tlie robot and an obstacle mov-ing at a given velocity. The avo ..."
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Cited by 206 (6 self)
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Abstract!llis paper presents a new approach for rot)ot]notion planning in dynamic environ-ments, based on the concept of Velocity Obstacle.,4 velocity obstacle defines the set of robot velocities that would result in a collision between tlie robot and an obstacle mov-ing at a given velocity. The avoidance maneuver a { a specific time is thus computed by selecting robot’s velocities out of that set. ~’lle set [If all avoid inp, velocities is redllced to the dynamica]]y fcasib]e maneuvers by considering the robot’s acceleration constraints. This computation is re])eatecl at regular time intro vals to account for genera] obstacle trajectories. The t rajtxtory from start to goal can be com])uted by searching a tree of feasible avoidance maneuvers C.olnputecl at discrete time ini ervals. An exhaustive search of the tree yields near-optima] trajectories that either minimize distance or motion time. A heuristic search of t}le tree yields trajectories that satisfy a l)rioritized list of objectives, such as reaching t}~e goal, maximizing speed, and achieving a desired trajectory structure. The heuristic approach is computational]y ctlicientl a])plic.al)le to on-line planning of industrial robots, performing assembly tasks cm lnoving conveyers, and to intelligent vehi-cles negotiating freeway traffic. The method is demonstrated for planning the trajectory of an automated vehicle in an Intelligent Vehicle Highway System scenario. 1.
Social Potential Fields: A Distributed Behavioral Control for Autonomous Robots
, 1999
"... A Very Large Scale Robotic (VLSR) system may consist of from hundreds to perhaps tens of thousands or more autonomous robots. The costs of robots are going down, and the robots are getting more compact, more capable, and more flexible. Hence, in the near future, we expect to see many industrial and ..."
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Cited by 183 (1 self)
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A Very Large Scale Robotic (VLSR) system may consist of from hundreds to perhaps tens of thousands or more autonomous robots. The costs of robots are going down, and the robots are getting more compact, more capable, and more flexible. Hence, in the near future, we expect to see many industrial and military applications of VLSR systems in tasks such as assembling, transporting, hazardous inspection, patrolling, guarding and attacking. In this paper, we propose a new approach for distributed autonomous control of VLSR systems. We define simple artificial force laws between pairs of robots or robot groups. The force laws are inverse-power force laws, incorporating both attraction and repulsion. The force laws can be distinct and to some degree they reflect the 'social relations' among robots. Therefore we call our method social potential fields. An individual robot's motion is controlled by the resultant artificial force imposed by other robots and other components of the system. The approach is distributed in that the force calculations and motion control can be done in an asynchronous and distributed manner. We also extend the social potential fields model to use spring laws as force laws. This paper presents the first and a preliminary study on applying potential fields to distributed autonomous multi-robot control. We describe the generic framework of our social potential fields method. We show with computer simulations that the method can yield interesting and useful behaviors among robots, and we give examples of possible industrial and military applications. We also identify theoretical problems for future studies. 1999 Published by Elsevier Science B.V. All rights reserved.
Interaction and Intelligent Behavior
, 1994
"... This thesis addresses situated, embodied agents interacting in complex domains. It focuses on two problems: 1) synthesis and analysis of intelligent group behavior, and 2) learning in complex group environments. Basic behaviors, control laws that cluster constraints to achieve particular goals and h ..."
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Cited by 174 (20 self)
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This thesis addresses situated, embodied agents interacting in complex domains. It focuses on two problems: 1) synthesis and analysis of intelligent group behavior, and 2) learning in complex group environments. Basic behaviors, control laws that cluster constraints to achieve particular goals and have the appropriate compositional properties, are proposed as effective primitives for control and learning. The thesis describes the process of selecting such basic behaviors, formally specifying them, algorithmically implementing them, and empirically evaluating them. All of the proposed ideas are validated with a group of up to 20 mobile robots using a basic behavior set consisting of: safe--wandering, following, aggregation, dispersion, and homing. The set of basic behaviors acts as a substrate for achieving more complex high--level goals and tasks. Two behavior combination operators are introduced, and verified by combining subsets of the above basic behavior set to implement collective flocking, foraging, and docking. A methodology is introduced for automatically constructing higher--level behaviors
Optimal Motion Planning for Multiple Robots Having Independent Goals
, 1998
"... This work makes two contributions to geometric motion planning for multiple robots: i) Motion plans are computed that simultaneously optimize an independent performance measure for each robot; ii) A general spectrum is defined between decoupled and centralized planning, in which we introduce coordin ..."
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Cited by 104 (6 self)
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This work makes two contributions to geometric motion planning for multiple robots: i) Motion plans are computed that simultaneously optimize an independent performance measure for each robot; ii) A general spectrum is defined between decoupled and centralized planning, in which we introduce coordination along independent roadmaps. By considering independent performance measures, we introduce a form of optimality that is consistent with concepts from multi-objective optimization and game theory literature. Previous multiple-robot motion planning approaches that consider optimality combine individual performance measures into a scalar criterion. As a result, these methods can fail to find many potentially useful motion plans. We present implemented, multiple-robot motion planning algorithms that are derived from the principle of optimality, for three problem classes along the spectrum between centralized and decoupled planning: i) coordination along fixed, independent paths; ii) coordination along independent roadmaps; iii) general, unconstrained motion planning. Computed examples are presented for all three problem classes that illustrate the concepts and algorithms.
Rapid Collision Detection by Dynamically Aligned DOP-Trees
- In Proc. of IEEE Virtual Reality Annual International Symposium; VRAIS ’98
, 1998
"... Based on a general hierarchical data structure, we present a fast algorithm for exact collision detection of arbitrary polygonal rigid objects. Objects consisting of hundreds of thousands of polygons can be checked for collision at interactive rates. ..."
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Cited by 76 (19 self)
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Based on a general hierarchical data structure, we present a fast algorithm for exact collision detection of arbitrary polygonal rigid objects. Objects consisting of hundreds of thousands of polygons can be checked for collision at interactive rates.