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Towards Real-Time Sensor-Based Path Planning in Highly Dynamic Environments
LAAS-CNRS, Toulouse, France.ORCID iD: 0000-0003-3513-8854
Singleton Technology, Lausanne, Switzerland.
Autonomous Systems Lab, EPFL, Switzerland.
2007 (English)In: Autonomous Navigation in Dynamic Environments / [ed] Christian Laugier and Raja Chatila, New York: Springer-Verlag New York, 2007, 135-148 p.Chapter in book (Refereed)
Abstract [en]

This paper presents work on sensor-based motion planning in initially unknown dynamic environments. Motion detection and probabilistic motion modeling are combined with a smooth navigation function to perform on-line path planning and replanning in cluttered dynamic environments such as public exhibitions. The SLIP algorithm, an extension of Iterative Closest Point, combines motion detection from a mobile platform with position estimation. This information is then processed using probabilistic motion prediction to yield a co-occurrence risk that unifies dynamic and static elements. The risk is translated into traversal costs for an E* path planner. It produces smooth paths that trade off collision risk versus detours. © Springer.

Place, publisher, year, edition, pages
New York: Springer-Verlag New York, 2007. 135-148 p.
Series
Springer Tracts in Advanced Robotics, ISSN 1610-7438 ; 35
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:hh:diva-20124DOI: 10.1007/978-3-540-73422-2_7ISBN: 978-3-540-73421-5 OAI: oai:DiVA.org:hh-20124DiVA: diva2:577000
Note

ScopusID: 2-s2.0-35348825549

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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