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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Book ChapterDOI
Dynamic Region-biased Rapidly-exploring Random Trees
TL;DR: Current state-of-the-art motion planners rely on samplingbased planning to explore the problem space for a solution, but sampling valid configurations in narrow or cluttered workspaces remains a challenge.
Proceedings ArticleDOI
Generalizing the analysis of PRM
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 in terms of computing the transitive closure of a relation over a probability space and gives a bound interms of the number of intermediate points for some path and the probability of choosing a point from a certain set.
Journal ArticleDOI
Human Interaction with Motion Planning Algorithm
TL;DR: This paper proposes a modification of a classic motion planning method, the Rapidly-exploring Random Tree to build an Interactive-RRT, based on exchanging pseudo-forces between the algorithm and the user, and on data gathering from the virtual scene.
Book ChapterDOI
Capturing the connectivity of high-dimensional geometric spaces by parallelizable random sampling techniques
TL;DR: A basic probabilistic roadmap planner is described, which is easily parallelizable, and a formal analysis is provided that explains its empirical success when the space satisfies two geometric properties called e-goodness and expansiveness.
Book ChapterDOI
Path Deformation Roadmaps
Léonard Jaillet,Thierry Siméon +1 more
TL;DR: A method that extends the Visibility-PRM technique to constructing compact roadmaps that encode a richer and more suitable information than representative paths of the homotopy classes, that enables small roadmaps to reliably and efficiently capture the multiple connectedness of the space in various problems.
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.