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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A Novel Algorithm for Autonomous Robot Navigation System Using Neural Network
Najmuddin Aamer,S. Ramachandran +1 more
TL;DR: This work proposed an efficient model for the robot navigation using neural networks and to overcome the path planning, kinematics based model is presented and it is able to achieve the stability condition of the robot.
Book ChapterDOI
Planning Collision-Free Paths Using Probabilistic Roadmaps
Seth Hutchinson,P. Leven +1 more
Journal ArticleDOI
An Efficient Sampling-Based Path Planning for the Lunar Rover with Autonomous Target Seeking
TL;DR: In this paper, an efficient path planning method for the lunar rover to improve the autonomy and exploration ability in the complex and unstructured lunar surface environment is presented, based on which a detecting point selection strategy is proposed to choose target positions that meet the rover's constraints.
Posted Content
Annotated-skeleton Biased Motion Planning for Faster Relevant Region Discovery.
TL;DR: This work presents a method that augments a skeleton representing the workspace topology with such information to guide a sampling-based motion planner to rapidly discover regions most relevant to the problem at hand and demonstrates the efficacy of this approach in both robotics problems and applications in drug design.
Dissertation
3D Motion Planning using Kinodynamically Feasible Motion Primitives in Unknown Environments
TL;DR: This thesis presents a new motion planner that is capable of finding collision-free paths through an unknown environment while satisfying the kinodynamic constraints of the vehicle using a two step process.
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.