Convergence of autonomous mobile robots with inaccurate sensors and movements

Reuven Cohen, David Peleg

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

31 Scopus citations

Abstract

The common theoretical model adopted in recent studies on algorithms for systems of autonomous mobile robots assumes that the positional input of the robots is obtained by perfectly accurate visual sensors, that robot movements are accurate, and that internal calculations performed by the robots on (real) coordinates are perfectly accurate as well. The current paper concentrates on the effect of weakening this rather strong set of assumptions, and replacing it with the more realistic assumption that the robot sensors, movement and internal calculations may have slight inaccuracies. Specifically, the paper concentrates on the ability of robot systems with inaccurate sensors, movements and calculations to carry out the task of convergence. The paper presents several impossibility results, limiting the inaccuracy allowing convergence. The main positive result is an algorithm for convergence under bounded measurement, movement and calculation errors.

Original languageEnglish
Title of host publicationSTACS 2006
Subtitle of host publication23rd Annual Symposium on Theoretical Aspects of Computer Science, Proceedings
Pages549-560
Number of pages12
DOIs
StatePublished - 2006
Externally publishedYes
EventSTACS 2006: 23rd Annual Symposium on Theoretical Aspects of Computer Science, Proceedings - Marseille, France
Duration: 23 Feb 200625 Feb 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3884 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceSTACS 2006: 23rd Annual Symposium on Theoretical Aspects of Computer Science, Proceedings
Country/TerritoryFrance
CityMarseille
Period23/02/0625/02/06

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