Robotics: Science and Systems V

Efficient, guaranteed search with multi-agent teams

G. Hollinger, S. Singh and A. Kehagias

Abstract:

Here we present an anytime algorithm for clearing an environment using multiple searchers. Prior methods in the literature treat multi-agent search as either a worst-case problem (i.e., clear an environment of an adversarial evader with potentially infinite speed), or an average-case problem (i.e., minimize average capture time given a model of the target’s motion). We introduce an algorithm that combines finite-horizon planning with spanning tree traversal methods to generate plans that clear the environment of a worst-case adversarial target and have good average-case performance considering a target motion model. Our algorithm is scalable to large teams of searchers and yields theoretically bounded average-case performance. We have tested our proposed algorithm through a large number of experiments in simulation and with a team of robot and human searchers in an office building. Our combined search algorithm both clears the environment and reduces average capture times by up to 75% when compared to a purely worst-case approach.

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Bibtex:

@INPROCEEDINGS{ Hollinger-RSS-09,
    AUTHOR    = {G. Hollinger AND S. Singh AND A. Kehagias},
    TITLE     = {Efficient, guaranteed search with multi-agent teams},
    BOOKTITLE = {Proceedings of Robotics: Science and Systems},
    YEAR      = {2009},
    ADDRESS   = {Seattle, USA},
    MONTH     = {June},
    DOI       = {10.15607/RSS.2009.V.034} 
}