Visual collision avoidance by segmentation

Ian Horswill*

*Corresponding author for this work

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

31 Scopus citations

Abstract

Visual collision avoidance involves two difficult subproblems: obstacle recognition and depth measurement. We present a class of algorithms that use particularly simple methods for each subproblem and derive a set of sufficient conditions for their proper functioning based on a set of idealizations. We then discuss and compare two different implementations of the approach and discuss their performance. Finally, we experimentally validate the idealizations.

Original languageEnglish (US)
Title of host publicationIEEE/RSJ/GI International Conference on Intelligent Robots and Systems
PublisherIEEE
Pages902-909
Number of pages8
Volume2
StatePublished - Dec 1 1994
EventProceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems. Part 3 (of 3) - Munich, Ger
Duration: Sep 12 1994Sep 16 1994

Other

OtherProceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems. Part 3 (of 3)
CityMunich, Ger
Period9/12/949/16/94

ASJC Scopus subject areas

  • Engineering(all)

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