Abstract:
Probabilistic roadmap methods (PRM) have been successfully used to solve difficult path planning problems but their efficiency is limited when the free space contains nar...Show MoreMetadata
Abstract:
Probabilistic roadmap methods (PRM) have been successfully used to solve difficult path planning problems but their efficiency is limited when the free space contains narrow passages through which the robot must pass. This paper presents a new sampling scheme that aims to increase the probability of finding paths through narrow passages. Here, a biased sampling scheme is used to increase the distribution of nodes in narrow regions of the free space. A partial computation of the artificial potential field is used to bias the distribution of nodes.
Published in: IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004
Date of Conference: 26 April 2004 - 01 May 2004
Date Added to IEEE Xplore: 06 July 2004
Print ISBN:0-7803-8232-3
Print ISSN: 1050-4729
Contents 