Multiple Unmanned Aerial Vehicles (UAVs) cooperative searching is an important research area in cooperative control. The objective is reducing the uncertainty of the search area and achieving the information about it. This paper presents an approach which combines Model Predictive Control (MPC) theory with the Genetic Algorithm (GA) to solve this problem. First, the formal representation of the search environment is established, the multi-UAV is modeled as a controlled system and the predictive model of the system is presented. Considering the uncertainty of the sensor measurement and the environment, a Search Probability Map (SPM) is defined and the updating method based on Bayes formula is presented. Based on SPM, information gain is defined to measure the search effects and used to be the optimization object in the predictive horizon. By using of GA, the solution of the optimization problem is got and it is taken as the input of the controlled system. Simulation results demonstrate the efficiency of the algorithm.
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