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Toward Online Probabilistic Path Replanning in Dynamic Environments
LAAS-CNRS, Toulouse, France.ORCID iD: 0000-0003-3513-8854
Singleton Technology, Lausanne, Switzerland.
Autonomous Systems Lab, EPFL, Switzerland.
2006 (English)In: IROS 2006: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Piscataway, N.J.: IEEE Press, 2006, 2876-2881 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents work on sensor-based motion planning in initially unknown dynamic environments. Motion detection and modeling are combined with a smooth navigation function to perform on-line path planning in cluttered dynamic environments. The SLIP algorithm, an extension of Iterative Closest Point, combines motion detection from a mobile platform with position estimation. This information is used via probabilistic prediction to estimate a traversal risk function that unifies dynamic and static obstacles. The risk is fed to E* and leads to smooth paths that trade off collision risk versus detours. © 2006 IEEE.

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE Press, 2006. 2876-2881 p.
Keyword [en]
path planning, probabilistic reasoning, human-robot interaction
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:hh:diva-20117DOI: 10.1109/IROS.2006.282136ISI: 000245452403004Scopus ID: 2-s2.0-34250656472ISBN: 978-142440259-5 ISBN: 142440259X OAI: oai:DiVA.org:hh-20117DiVA: diva2:576979
Conference
2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006, Beijing, 9-15 October 2006, Category number CH37780
Available from: 2012-12-14 Created: 2012-12-14 Last updated: 2013-11-15Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Language
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Output format
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