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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Proceedings ArticleDOI
HPRM: a hierarchical PRM
TL;DR: A hierarchical variant of the probabilistic roadmap method for motion planning is introduced, by recursively refining an initially sparse sampling in neighborhoods of the obstacle boundary, that generates a smaller roadmap that is more likely to find narrow passages than uniform sampling.
Journal ArticleDOI
Perception‐aware autonomous mast motion planning for planetary exploration rovers
TL;DR: In this paper, the authors use the ability of the rover to actively steer the visual sensor to improve fault tolerance and maximize the perception performance, which is accomplished by an online assessment of possible trajectories using synthetic, future camera views created from previous observations.
Journal ArticleDOI
Efficient Penetration Depth Computation Between Rigid Models Using Contact Space Propagation Sampling
TL;DR: In this article, the authors proposed a novel method to compute the approximate global penetration depth (PD) between two nonconvex geometric models, which consists of two phases: offline precomputation and run-time queries.
Proceedings ArticleDOI
Structural improvement filtering strategy for PRM
TL;DR: This work introduces a filtering strategy for the Probabilistic Roadmap Methods (PRM) with the aim to improve roadmap construction performance by selecting only the samples that are likely to produce roadmap structure improvement.
Proceedings ArticleDOI
VIZMO++: a visualization, authoring, and educational tool for motion planning
TL;DR: An interactive tool for visualizing and editing motion planning environments, problem instances, and their solutions that is specialized for sampling-based randomized planners such as probabilistic roadmap (PRM) and rapidly-exploring random tree (RRT) methods is presented.
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.