Open AccessProceedings Article
OBPRM: an obstacle-based PRM for 3D workspaces
Nancy M. Amato,O. Burchan Bayazit,Lucia K. Dale,Christopher Jones,Daniel Vallejo +4 more
- pp 155-168
TLDR
This paper presents a new class of randomized path planning methods, known as Probabilistic Roadmap Methods (prms), which use randomization to construct a graph of representative paths in C-space whose vertices correspond to collision-free con gurations of the robot.Abstract:
Recently, a new class of randomized path planning methods, known as Probabilistic Roadmap Methods (prms) have shown great potential for solving complicated high-dimensional problems. prms use randomization (usually during preprocessing) to construct a graph of representative paths in C-space (a roadmap) whose vertices correspond to collision-free con gurations of the robot and in which two vertices are connected by an edge if a path between the two corresponding con gurations can be found by a local planning method.read more
Citations
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Journal ArticleDOI
Sparse roadmap spanners for asymptotically near-optimal motion planning
Andrew Dobson,Kostas E. Bekris +1 more
TL;DR: Simulations for rigid-body motion planning show that algorithms for constructing sparse roadmap spanners indeed provide small data structures and result in faster query resolution, and suggests that finite-size data structures with asymptotic near-optimality in continuous spaces may indeed exist.
Proceedings ArticleDOI
Decomposition-based motion planning: a framework for real-time motion planning in high-dimensional configuration spaces
Oliver Brock,Lydia E. Kavraki +1 more
TL;DR: A novel real-time motion planning framework, called decomposition-based motion planning, is proposed, which decomposes the original planning problem into simpler sub-problems, whose successive solution empirically results in a large reduction of the overall complexity.
Journal ArticleDOI
Measure theoretic analysis of probabilistic path planning
Andrew M. Ladd,Lydia E. Kavraki +1 more
TL;DR: This paper presents a novel analysis of the probabilistic roadmap method (PRM) for path planning, and gives a bound on the expected number iterations of PRM required to find a path, in terms of the number of intermediate points and the probability of choosing a point from a certain set.
Proceedings ArticleDOI
Toward Optimal Configuration Space Sampling
Brendan Burns,Oliver Brock +1 more
TL;DR: A new approach to multi-query samplingbased motion planning is proposed, which exploits information obtained from earlier exploration and its current state to guide exploration and significantly decreases the runtime required for motion planning.
Proceedings ArticleDOI
Non-gaited humanoid locomotion planning
TL;DR: A method of iterative constraint enforcement is presented that samples feasible configurations much more quickly and uses a probabilistic, sample-based approach to compute each step.
References
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Book
Robot Motion Planning
TL;DR: This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.
Journal ArticleDOI
Probabilistic roadmaps for path planning in high-dimensional configuration spaces
TL;DR: Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (/spl ap/150 MIPS), after learning for relatively short periods of time (a few dozen seconds).
Journal ArticleDOI
Robot motion planning: a distributed representation approach
TL;DR: 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 is proposed and a planner based on this approach has been implemented.
Journal ArticleDOI
Gross motion planning—a survey
Yong K. Hwang,Narendra Ahuja +1 more
TL;DR: This paper surveys the work on gross-motion planning, including motion planners for point robots, rigid robots, and manipulators in stationary, time-varying, constrained, and movable-object environments.
Proceedings Article
Complexity of the Mover's Problem and Generalizations Extended Abstract
TL;DR: This paper concerns the problem of moving a polyhedron through Euclidean space while avoiding polyhedral obstacles.