A Cooperative Approach to Multi-UAVs Search for Mobile Targets Based on Pigeon-Inspired Optimization

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Abstract
To improve the search efficiency and reduce the impact of the uncertainty of mobile targets on multi-UAVs search, this paper proposes a search decision-making method based on the receding horizon control (RHC) and pigeon-inspired optimization (PIO). According to advance intelligence information and detection information of onboard sensors, the search environment is described with the target occupancy probability updated based on the Bayesian theory. In order to describe the search environment more accurately, we also introduce certainty information and pheromone information. Then under the conditions of targets discovery profit, expected detection profit, cooperation profit and the execution cost, the cooperative profit function is built. Aiming at reducing the amount of calculation and improving the search efficiency, we employ the method of PIO based on RHC to obtain the decision-making orders. The simulation results have verified the effectiveness of the proposed method.

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