Abstract
AbstractThis paper focuses on the problem of cooperative search using a team of Unmanned Aerial vehicles (UAVs). The objective is to visit as many unknown area as possible, while avoiding collision. We present an approach which combines model predictive control(MPC) theory with genetic algorithm(GA) to solve this problem. First, the team of UAVs is modelled as a controlled system, and its next state is predicated by MPC theory. According to the predicted state, we then establish an optimization problem. By use of GA, we get the solution of the optimization problem and take it as the input of the controlled system. Simulation results demonstrate the feasibility of our algorithm.KeywordsGenetic AlgorithmUnmanned Aerial VehicleModel Predictive ControlHexagonal CellRecede Horizon ControlThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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