2020
DOI: 10.1109/tmech.2020.2996901
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Guarding a Territory Against an Intelligent Intruder: Strategy Design and Experimental Verification

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Cited by 17 publications
(2 citation statements)
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“…As the players' objectives imply, M-RA differential games have high relevance to the adversarial scenarios in which players compete or cooperate for a set of states in the game state space. For example, mobile ground vehicles can be employed to defend a building of interest so as to minimize some metric, such as the number of malicious vehicles entering the building (Fu and Liu, 2020;Shishika et al, 2021). In wildlife protection, the use of unmanned aerial vehicles against illegal poachers is a promising alternative to typical field methods.…”
Section: Applicationsmentioning
confidence: 99%
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“…As the players' objectives imply, M-RA differential games have high relevance to the adversarial scenarios in which players compete or cooperate for a set of states in the game state space. For example, mobile ground vehicles can be employed to defend a building of interest so as to minimize some metric, such as the number of malicious vehicles entering the building (Fu and Liu, 2020;Shishika et al, 2021). In wildlife protection, the use of unmanned aerial vehicles against illegal poachers is a promising alternative to typical field methods.…”
Section: Applicationsmentioning
confidence: 99%
“…This review is concerned with the M-RA differential games, with a particular interest in simple motions, which were first discussed by (Mitchell et al, 2005;Margellos and Lygeros, 2011;Zhou et al, 2012) and then extended into many variations and practical applications (Huang et al, 2014;Selvakumar and Bakolas, 2019;Fu and Liu, 2020). The problem is closely related to lifeline games (Garcia et al, 2019b;Yan et al, 2021a;Yan et al, 2021b;Chen and Yu, 2022), two-target differential games (Blaquière et al, 1969;Olsder and Breakwell, 1974;Pachter and Getz, 1980;Getz and Pachter, 1981) and target guarding differential games (Mohanan et al, 2018).…”
mentioning
confidence: 99%