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402
Randomized kinodynamic planning
- THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2001; 20; 378
, 2001
"... This paper presents the first randomized approach to kinodynamic planning (also known as trajectory planning or trajectory design). The task is to determine control inputs to drive a robot from an initial configuration and velocity to a goal configuration and velocity while obeying physically based ..."
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Cited by 626 (35 self)
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This paper presents the first randomized approach to kinodynamic planning (also known as trajectory planning or trajectory design). The task is to determine control inputs to drive a robot from an initial configuration and velocity to a goal configuration and velocity while obeying physically based dynamical models and avoiding obstacles in the robot’s environment. The authors consider generic systems that express the nonlinear dynamics of a robot in terms of the robot’s high-dimensional configuration space. Kinodynamic planning is treated as a motion-planning problem in a higher dimensional state space that has both first-order differential constraints and obstaclebased global constraints. The state space serves the same role as the configuration space for basic path planning; however, standard randomized path-planning techniques do not directly apply to planning trajectories in the state space. The authors have developed a randomized
Rapidly-Exploring Random Trees: A New Tool for Path Planning
, 1998
"... We introduce the concept of a Rapidly-exploring Random Tree (RRT) as a randomized data structure that is designed for a broad class of path planning problems. While they share many of the beneficial properties of existing randomized planning techniques, RRTs are specifically designed to handle nonho ..."
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Cited by 397 (19 self)
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We introduce the concept of a Rapidly-exploring Random Tree (RRT) as a randomized data structure that is designed for a broad class of path planning problems. While they share many of the beneficial properties of existing randomized planning techniques, RRTs are specifically designed to handle nonholonomic constraints (including dynamics) and high degrees of freedom. An RRT is iteratively expanded by applying control inputs that drive the system slightly toward randomly-selected points, as opposed to requiring point-to-point convergence, as in the probabilistic roadmap approach. Several desirable properties and a basic implementation of RRTs are discussed. To date, we have successfully applied RRTs to holonomic, nonholonomic, and kinodynamic planning problems of up to twelve degrees of freedom.
PATH PLANNING IN EXPANSIVE CONFIGURATION SPACES
, 1999
"... We introduce the notion of expansiveness to characterize a family of robot configuration spaces whose connectivity can be effectively captured by a roadmap of randomlysampled milestones. The analysis of expansive configuration spaces has inspired us to develop a new randomized planning algorithm. ..."
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Cited by 264 (30 self)
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We introduce the notion of expansiveness to characterize a family of robot configuration spaces whose connectivity can be effectively captured by a roadmap of randomlysampled milestones. The analysis of expansive configuration spaces has inspired us to develop a new randomized planning algorithm. This new algorithm tries to sample only the portion of the configuration space that is relevant to the current query, avoiding the cost of precomputing a roadmap for the entire configuration space. Thus, it is wellsuited for problems where only a single query is submitted for a given environment. The algorithm has been implemented and successfully applied to complex assembly maintainability problems from the automotive industry.
OBPRM: An Obstacle-Based PRM for 3D Workspaces
, 2001
"... Recently, a new class of randomized path planning ..."
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Cited by 249 (73 self)
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Recently, a new class of randomized path planning
Path Planning Using Lazy PRM
- In IEEE Int. Conf. Robot. & Autom
, 2000
"... This paper describes a new approach to probabilistic roadmap planners (PRMs). The overall theme of the algorithm, called Lazy PRM, is to minimize the number of collision checks performed during planning and hence minimize the running time of the planner. Our algorithm builds a roadmap in the configu ..."
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Cited by 243 (20 self)
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This paper describes a new approach to probabilistic roadmap planners (PRMs). The overall theme of the algorithm, called Lazy PRM, is to minimize the number of collision checks performed during planning and hence minimize the running time of the planner. Our algorithm builds a roadmap in the configuration space, whose nodes are the user-defined initial and goal configurations and a number of randomly generated nodes. Neighboring nodes are connected by edges representing paths between the nodes. In contrast with PRMs, our planner initially assumes that all nodes and edges in the roadmap are collision-free, and searches the roadmap at hand for a shortest path between the initial and the goal node. The nodes and edges along the path are then checked for collision. If a collision with the obstacles occurs, the corresponding nodes and edges are removed from the roadmap. Our planner either finds a new shortest path, or first updates the roadmap with new nodes and edges, and then searches for a shortest path. The above process is repeated until a collision-free path is returned.
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.
On Finding Narrow Passages with Probabilistic Roadmap Planners
, 1998
"... ... This paper provides foundations for understanding the effect of passages on the connectedness of probabilistic roadmaps. It also proposes a new random sampling scheme for finding such passages. An initial roadmap is built in a "dilated" free space allowing some penetration distance of ..."
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Cited by 181 (31 self)
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... This paper provides foundations for understanding the effect of passages on the connectedness of probabilistic roadmaps. It also proposes a new random sampling scheme for finding such passages. An initial roadmap is built in a "dilated" free space allowing some penetration distance of the robot into the obstacles. This roadmap is then modified by resampling around the links that do not lie in the true free space. Experiments show that this strategy allows relatively small roadmaps to reliably capture the free space connectivity
Planning Motions with Intentions
, 1994
"... We apply manipulation planning to computer animation. A new path planner is presented that automatically computes the collision-free trajectories for several cooperating arms to manipulate a movable object between two configurations. This implemented planner is capable of dealing with complicated ta ..."
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Cited by 150 (19 self)
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We apply manipulation planning to computer animation. A new path planner is presented that automatically computes the collision-free trajectories for several cooperating arms to manipulate a movable object between two configurations. This implemented planner is capable of dealing with complicated tasks where regrasping is involved. In addition, we present a new inverse kinematics algorithm for the human arms. This algorithm is utilized by the planner for the generation of realistic human arm motions as they manipulate objects. We view our system as a tool for facilitating the production of animation.
A randomized roadmap method for path and manipulation planning
- in Proc. IEEE Int. Conf. Robot. Autom. (ICRA
, 1996
"... This paper presents a new randomized roadmap method for motion planning for many dof robots that can be used to obtain high quality roadmaps even when C-space is crowded. The main novelty in our approach is that roadmap candidate points are chosen on C-obstacle sur-faces. As a consequence, the roadm ..."
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Cited by 140 (17 self)
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This paper presents a new randomized roadmap method for motion planning for many dof robots that can be used to obtain high quality roadmaps even when C-space is crowded. The main novelty in our approach is that roadmap candidate points are chosen on C-obstacle sur-faces. As a consequence, the roadmap is likely to con-tain difficult paths, such as those traversing long, narrow passages in C-space. The approach can be used for both collision-free path planning and for manipulationplanning of contact tasks. Experimental results with a planar artic-ulated 6 dof robot show that, after preprocessing, difficult path planning operations can often be carried out in less than a second. 1
