Artificial potential biased probabilistic roadmap method
2004 (English)In: 2004 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS 1- 5, PROCEEDINGS, 2004, 461-466 p.Conference paper (Refereed)
Probabilistic roadmap methods (PRMs) 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.
Place, publisher, year, edition, pages
2004. 461-466 p.
, IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ISSN 1050-4729
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-44357DOI: 10.1109/ROBOT.2004.1307192ISI: 000221794800073ScopusID: 2-s2.0-3042621783ISBN: 0-7803-8232-3OAI: oai:DiVA.org:kth-44357DiVA: diva2:450899
IEEE International Conference on Robotics and Automation Location: New Orleans, LA Date: APR 26-MAY 01, 2004
QC 201110242011-10-242011-10-202012-01-24Bibliographically approved