Optimal Distributed Searching in the Plane with and without Uncertainty
This addresses search and rescue operations using swarms of drones or vessels, providing a theoretical framework for coordination, though it appears incremental in extending idealized models to practical conditions.
The paper tackles the problem of coordinating multiple agents to search for a target in the plane, developing an optimal strategy for k robots starting from a common origin and moving at unit speed, and shows that this model can be adapted to realistic scenarios like differential speeds and poor visibility with minor changes.
We consider the problem of multiple agents or robots searching 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.