CCQ: Efficient local planning using connection collision query

Min Tang, Young J. Kim, Dinesh Manocha

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

13 Scopus citations

Abstract

We introduce a novel proximity query, called connection collision query (CCQ), and use it for efficient and exact local planning in sampling-based motion planners. Given two collision-free configurations, CCQ checks whether these configurations can be connected by a given continuous path that either lies completely in the free space or penetrates any obstacle by at most ε, a given threshold. Our approach is general, robust, and can handle different continuous path formulations. We have integrated the CCQ algorithm with sampling-based motion planners and can perform reliable local planning queries with little performance degradation, as compared to prior methods. Moreover, the CCQ-based exact local planner is about an order of magnitude faster than prior exact local planning algorithms.

Original languageEnglish
Title of host publicationAlgorithmic Foundations of Robotics IX - Selected Contributions of the Ninth International Workshop on the Algorithmic Foundations of Robotics
Pages229-247
Number of pages19
EditionSTAR
DOIs
StatePublished - 2010
Event9th International Workshop on the Algorithmic Foundations of Robotics, WAFR 2010 - Singapore, Singapore
Duration: 13 Dec 201015 Dec 2010

Publication series

NameSpringer Tracts in Advanced Robotics
NumberSTAR
Volume68
ISSN (Print)1610-7438
ISSN (Electronic)1610-742X

Conference

Conference9th International Workshop on the Algorithmic Foundations of Robotics, WAFR 2010
Country/TerritorySingapore
CitySingapore
Period13/12/1015/12/10

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