Abstract
We consider the problem of multiple agents or robots searching in a coordinated fashion for a target in the plane. This is motivated by Search and Rescue operations (SAR) in the high seas which in the past were often performed with several vessels, and more recently by swarms of aerial drones and/or unmanned surface vessels. Coordinating such a search in an effective manner is a non trivial task. In this paper, we develop first an optimal strategy for searching with k robots starting from a common origin and moving at unit speed. We then apply the results from this model to more realistic scenarios such as differential search speeds, late arrival times to the search effort and low probability of detection under poor visibility conditions. We show that, surprisingly, the theoretical idealized model still governs the search with certain suitable minor adaptations.
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Notes
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For example, the cost of an unmanned search vehicle is in the order of tens of thousands of dollars which can be amortized over hundreds of searches, while the cost of conventional search efforts range from the low hundred thousands of dollars up to sixty million dollars for high profile searches such as Malaysia Airlines MH370 and Air France 447. This suggests that somewhere in the order of a few hundred to a few tens of thousands of robots can be brought to bear in such a search.
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López-Ortiz, A., Maftuleac, D. (2016). Optimal Distributed Searching in the Plane with and Without Uncertainty. In: Kaykobad, M., Petreschi, R. (eds) WALCOM: Algorithms and Computation. WALCOM 2016. Lecture Notes in Computer Science(), vol 9627. Springer, Cham. https://doi.org/10.1007/978-3-319-30139-6_6
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DOI: https://doi.org/10.1007/978-3-319-30139-6_6
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