Abstract

One of the main challenges in multi-unmanned aerial vehicle search and rescue missions is to efficiently distribute the search and rescue tasks over several unmanned aerial vehicles. Rescuing survivors quickly is critical since survivors have a limited life span. In this paper, we present a multi-unmanned aerial vehicle task allocation system inspired by area-restricted search, a foraging behavior of animals in which they focus on a local foraging area after finding prey in order to increase prey encounters. The algorithm’s performance was assessed in comparison to opportunistic coordination schemes. Simulation experiments indicated noticeable improvement in the mean rescue time. Also, the algorithm demonstrated better net throughput than the baseline performance, especially in small fleet sizes, without compromising runtime performance.

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