Reducing sensitivity to localization error through local search

Monica Anderson, Nikolaos Papanikolopoulos

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

1 Scopus citations

Abstract

Many researchers study the search of unknown areas with teams of cooperating robots. Robot cooperation often relies upon shared representations built from shared information. When robots share information, they inadvertently share the error associated with that information. In this research, we realistically assume that all position-based data has some amount of localization error. We model the propagation of this error in cooperative search. We conjecture that propagation of error differs based on whether search targets are shared or locally discovered. Search errors due to inaccurate position estimates are quantified and compared in both approaches via simulations.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
Pages1339-1342
Number of pages4
DOIs
StatePublished - Dec 1 2007
Event2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007 - San Diego, CA, United States
Duration: Oct 29 2007Nov 2 2007

Publication series

NameIEEE International Conference on Intelligent Robots and Systems

Other

Other2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
Country/TerritoryUnited States
CitySan Diego, CA
Period10/29/0711/2/07

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