Path planning for simple robots using soft subdivision search

Ching Hsiang Hsu, John Paul Ryan, Chee Yap

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

Abstract

The concept of ε-exact path planning is a theoretically sound alternative to the standard exact algorithms, and provides much stronger guarantees than probabilistic or sampling algorithms. It opens the way for the introduction of soft predicates in the context of subdivision algorithm. Taking a leaf from the great success of the Probabilistic Road Map (PRM) framework, we formulate an analogous framework for subdivision, called Soft Subdivision Search (SSS). In this video, we illustrate the SSS framework for a trio of simple planar robots: disc, triangle and 2-links. These robots have, respectively, 2, 3 and 4 degrees of freedom. Our 2-link robot can also avoid self-crossing. These algorithms operate in realtime and are relatively easy to implement.

Original languageEnglish (US)
Title of host publication32nd International Symposium on Computational Geometry, SoCG 2016
EditorsSandor Fekete, Anna Lubiw
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Pages68.1-68.5
ISBN (Electronic)9783959770095
DOIs
StatePublished - Jun 1 2016
Event32nd International Symposium on Computational Geometry, SoCG 2016 - Boston, United States
Duration: Jun 14 2016Jun 17 2016

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume51
ISSN (Print)1868-8969

Other

Other32nd International Symposium on Computational Geometry, SoCG 2016
CountryUnited States
CityBoston
Period6/14/166/17/16

Keywords

  • Configuration space
  • Path planning
  • Resolution exactness
  • Soft predicates
  • Subdivision search

ASJC Scopus subject areas

  • Software

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