UAV/UGV Search and Capture of Goal-Oriented Uncertain Targets*This research was supported in part by ISF grant #1337/15 and part by a grant from MOST, Israel and the JST Japan.

IROS(2018)

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摘要
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 attackersu0027 location and destination, and there is also uncertainty in the defendersu0027 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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关键词
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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