Hierarchical strategy synthesis for pursuit-evasion problems

Rattanachai Ramaithitima, Siddharth Srivastava, Subhrajit Bhattacharya, Alberto Speranzon, Vijay Kumar

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

1 Scopus citations

Abstract

We present a novel approach for solving pursuit-evasion problems where multiple pursuers with limited sensing capabilities are used to detect all possible mobile evaders in a given environment. We make no assumptions about the number, the speed, or the maneuverability of evaders. Our algorithm takes as input a map of the environment and sensor models for the pursuers. We then obtain a ? graph representation of an environment using a Cech Complex. Even with such a representation, the configuration space grows exponentially with the number of pursuers. In order to address this challenge, we propose an abstraction framework to partition the configuration space into sets of topologically similar configurations that preserve the space of possible evader locations. We validate our approach on several simulated environments with varying topologies and numbers of pursuers.

Original languageEnglish (US)
Title of host publicationFrontiers in Artificial Intelligence and Applications
EditorsGal A. Kaminka, Frank Dignum, Eyke Hullermeier, Paolo Bouquet, Virginia Dignum, Maria Fox, Frank van Harmelen
PublisherIOS Press
Pages1370-1378
Number of pages9
ISBN (Electronic)9781614996712
DOIs
StatePublished - Jan 1 2016
Externally publishedYes
Event22nd European Conference on Artificial Intelligence, ECAI 2016 - The Hague, Netherlands
Duration: Aug 29 2016Sep 2 2016

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume285
ISSN (Print)0922-6389

Other

Other22nd European Conference on Artificial Intelligence, ECAI 2016
CountryNetherlands
CityThe Hague
Period8/29/169/2/16

ASJC Scopus subject areas

  • Artificial Intelligence

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