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Autonomous swarm unmanned vehicles surveillance adapted to maritime environmental changes using algorithm inspired by adaptive mechanism of living organisms

We propose a swarm control algorithm for unmanned vehicles that adapts to unexpected environments while making the optimal formation. Our proposed algorithm, “autonomous and adaptive control”, is inspired by the control mechanism of living organisms and reconciles adaptability under a complex and changing environment and optimality for the various purposes of the system. In this paper, we apply the proposed algorithm to a surveillance system using multiple unmanned undersea vehicles that will be used in realistic operations. We made computational simulations of the surveillance system considering a real and complex seabed topography, sound speed profiles, and ocean current. We confirmed that the algorithm can work effectively in a complex and unexpected environment. The result show that the algorithm is can be used effectively in unexpected open-air conditions as well as in specific in-house conditions.