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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.
Rapidly-Exploring Random Trees: Progress and Prospects
- Algorithmic and Computational Robotics: New Directions
, 2000
"... this paper, which presents randomized, algorithmic techniques for path planning that are particular suited for problems that involve dierential constraints. ..."
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Cited by 333 (20 self)
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this paper, which presents randomized, algorithmic techniques for path planning that are particular suited for problems that involve dierential constraints.
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
Real-time motion planning for agile autonomous vehicles,
- AIAA Journal of Guidance and Control
, 2002
"... Planning the path of an autonomous,agile vehicle in a dynamicenvironment is a very complex problem, especially when the vehicle is required to use its full maneuvering capabilities. Recent efforts aimed at using randomized algorithms for planning the path of kinematic and dynamic vehicles have demo ..."
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Cited by 225 (16 self)
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Planning the path of an autonomous,agile vehicle in a dynamicenvironment is a very complex problem, especially when the vehicle is required to use its full maneuvering capabilities. Recent efforts aimed at using randomized algorithms for planning the path of kinematic and dynamic vehicles have demonstrated considerable potential for implementation on future autonomous platforms. This paper builds upon these efforts by proposing a randomized path planning architecture for dynamical systems in the presence of xed and moving obstacles. This architecture addresses the dynamic constraints on the vehicle's motion, and it provides at the same time a consistent decoupling between low-level control and motion planning. The path planning algorithm retains the convergence properties of its kinematic counterparts. System safety is also addressed in the face of nite computation times by analyzing the behavior of the algorithm when the available onboard computation resources are limited, and the planning must be performed in real time. The proposed algorithm can be applied to vehicles whose dynamics are described either by ordinary differential equations or by higher-level, hybrid representations. Simulation examples involving a ground robot and a small autonomous helicopter are presented and discussed.
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
MAPRM: A probabilistic roadmap planner with sampling on the medial axis of the free space
- In Proc. IEEE Int. Conf. Robot. Autom. (ICRA
, 1999
"... Probabilistic roadmap planning methods have been shown to perform well in a number of practical situations, but their performance degrades when paths are required to pass through narrow passages in the free space. We propose a new method of sampling the configuration space in which randomly generate ..."
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Cited by 174 (47 self)
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Probabilistic roadmap planning methods have been shown to perform well in a number of practical situations, but their performance degrades when paths are required to pass through narrow passages in the free space. We propose a new method of sampling the configuration space in which randomly generated configurations, free or not, are retracted onto the medial axis of the free space. We give algorithms that perform this retraction while avoiding explicit computation of the medial axis, and we show that sampling and retracting in this manner increases the number of nodes found in small volume corridors in a way that is independent of the volume of the corridor and depends only on the characteristics of the obstacles bounding it. Theoretical and experimental results are given to show that this improves performance on problems requiring traversal of narrow passages. 1
Controlling Formations of Multiple Mobile Robots
- in Proceedings of the IEEE International Conference on Robotics and Automation
, 1998
"... In this paper we investigate feedback laws used to control multiple robots moving together in a formation. We propose a method for controlling formations that uses only local sensor-based information, in a leader-follower motion. We use methods of feedback linearization to exponentially stabilize th ..."
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Cited by 158 (24 self)
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In this paper we investigate feedback laws used to control multiple robots moving together in a formation. We propose a method for controlling formations that uses only local sensor-based information, in a leader-follower motion. We use methods of feedback linearization to exponentially stabilize the relative distance and orientation of the follower, and show that the zero dynamics of the system are also (asymptotically) stable. We demonstrate in simulation the use of these algorithms to control six robots moving around an obstacle. These types of control laws can be used to control arbitrarily large numbers of robots moving in very general types of formations. Keywords: Nonholonomic motion planning, Control theory and Formations of robots. 1 Introduction This paper addresses issues of control and coordination for many robots moving in formation using decentralized controllers. The research on control and motion planning for mobile robots is both extensive and diverse. In the area o...
