TY - GEN
T1 - Hierarchical strategy synthesis for pursuit-evasion problems
AU - Ramaithitima, Rattanachai
AU - Srivastava, Siddharth
AU - Bhattacharya, Subhrajit
AU - Speranzon, Alberto
AU - Kumar, Vijay
N1 - Funding Information:
The authors gratefully acknowledge the support of ONR grant N00014-14-1-0510 and the United Technologies Research Center.
Publisher Copyright:
© 2016 The Authors and IOS Press.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85013113247&partnerID=8YFLogxK
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U2 - 10.3233/978-1-61499-672-9-1370
DO - 10.3233/978-1-61499-672-9-1370
M3 - Conference contribution
AN - SCOPUS:85013113247
T3 - Frontiers in Artificial Intelligence and Applications
SP - 1370
EP - 1378
BT - Frontiers in Artificial Intelligence and Applications
A2 - Kaminka, Gal A.
A2 - Dignum, Frank
A2 - Hullermeier, Eyke
A2 - Bouquet, Paolo
A2 - Dignum, Virginia
A2 - Fox, Maria
A2 - van Harmelen, Frank
PB - IOS Press
T2 - 22nd European Conference on Artificial Intelligence, ECAI 2016
Y2 - 29 August 2016 through 2 September 2016
ER -