Steps toward derandomizing RRTs

Stephen R. Lindemann, Steven M. Lavalle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present two new motion planning algorithms, based on the Rapidly Exploring Random Tree (RRT) family of algorithms. These algorithms represent the first work in the direction of derandomizing RRTs; this is a very challenging problem due to the way randomization is used in RRTs. In RRTs, randomization is used to create Voronoi bias, which causes the search trees to rapidly explore the state space. Our algorithms take steps to increase the Voronoi bias and to retain this property without the use of randomization. Studying these and related algorithms will improve our understanding of how efficient exploration can be accomplished, and will hopefully lead to improved planners. We give experimental results that illustrate how the new algorithms explore the state space and how they compare with existing RRT algorithms.

Original languageEnglish (US)
Title of host publicationProceedings of the Fourth International Workshop on Robot Motion and Control, RoMoCo'04
PublisherWydawnictwo Politechniki Poznanskiej
Pages271-277
Number of pages7
ISBN (Print)8371432720, 9788371432729
DOIs
StatePublished - 2004
EventProceedings of the Fourth International Workshop on Robot Motion and Control, RoMoCo'04 - Puszczykowo, Poland
Duration: Jun 17 2004Jun 20 2004

Publication series

NameProceedings of the Fourth International Workshop on Robot Motion and Control, RoMoCo'04

Other

OtherProceedings of the Fourth International Workshop on Robot Motion and Control, RoMoCo'04
Country/TerritoryPoland
CityPuszczykowo
Period6/17/046/20/04

ASJC Scopus subject areas

  • Engineering(all)

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