UAV/UGV Search and Capture of Goal-oriented Uncertain Targets

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Abstract

This paper considers a new, complex problem of UAV/UGV collaborative efforts to search and capture attackers under uncertainty. The goal of the defenders (UAV/UGV team) is to stop all attackers as quickly as possible, before they arrive at their selected goal. The uncertainty considered is twofold: the defenders do not know the attackers' location and destination, and there is also uncertainty in the defenders' sensing. We suggest a real-time algorithmic framework for the defenders, combining entropy and stochastic-temporal belief, that aims at optimizing the probability of a quick and successful capture of all of the attackers. We have empirically evaluated the algorithmic framework, and have shown its efficiency and significant performance improvement compared to other solutions.

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Key words

UAV/UGV collaborative efforts,stochastic-temporal belief,attacker capture,defender real-time algorithmic framework,probability optimization,goal-oriented uncertain targets,UAV/UGV search

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