Asymptotically-optimal Motion Planning using lower bounds on cost

Oren Salzman, Dan Halperin

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

Abstract

Many path-finding algorithms on graphs such as A∗ are sped up by using a heuristic function that gives lower bounds on the cost to reach the goal. Aiming to apply similar techniques to speed up sampling-based motion-planning algorithms, we use effective lower bounds on the cost between configurations to tightly estimate the cost-to-go. We then use these estimates in an anytime asymptotically-optimal algorithm which we call Motion Planning using Lower Bounds (MPLB). MPLB is based on the Fast Marching Trees (FMT∗) algorithm [1] recently presented by Janson and Pavone. An advantage of our approach is that in many cases (especially as the number of samples grows) the weight of collision detection in the computation is almost negligible compared to the weight of nearest-neighbor queries. We prove that MPLB performs no more collision-detection calls than an anytime version of FMT∗. Additionally, we demonstrate in simulations that for certain scenarios, the algorithmic tools presented here enable efficiently producing low-cost paths while spending only a small fraction of the running time on collision detection.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Robotics and Automation, ICRA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4167-4172
Number of pages6
EditionJune
ISBN (Electronic)9781479969234
DOIs
StatePublished - 29 Jun 2015
Event2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States
Duration: 26 May 201530 May 2015

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
NumberJune
Volume2015-June
ISSN (Print)1050-4729

Conference

Conference2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Country/TerritoryUnited States
CitySeattle
Period26/05/1530/05/15

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