Optimal obstacle avoidance based on the Hamilton-Jacobi-Bellman equation

S. Sundar, Z. Shiller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

This paper presents a method for generating shortest paths in cluttered environments, based on the Hamilton-Jacobi-Bellman (HJB) equation. Formulating the shortest obstacle avoidance problem as a time optimal control problem, the shortest paths are generated by following the negative gradient of the return function, which satisfies the HJB equation. A method to generate near-optimal paths is also presented, based on a pseudo return function. Paths generated by this method are guaranteed to reach the goal, at which the pseudo return function is shown to have a unique minimum. The computation required to generate the nearoptimal paths is substantially lower than those of traditional potential field methods, making it applicable to on-line obstacle avoidance. Examples with circular obstacles demonstrate close correlation between the near-optimal and optimal paths, and the advantages of the proposed approach over traditional potential field methods.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
Editors Anon
PagesVar pagings
Editionpt 3
StatePublished - 1994
Externally publishedYes
EventProceedings of the 1994 IEEE International Conference on Robotics and Automation. Part 3 (of 4) - San Diego, CA, USA
Duration: 8 May 199413 May 1994

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Numberpt 3
ISSN (Print)1050-4729

Conference

ConferenceProceedings of the 1994 IEEE International Conference on Robotics and Automation. Part 3 (of 4)
CitySan Diego, CA, USA
Period8/05/9413/05/94

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