Abstract
AbstractAiming at the problem of fixed-wing unmanned aerial vehicle (UAV) path planning, considering the actual flight conditions and flight performance of UAV, a multi-constraint UAV path planning model is constructed with the minimum flight range and correction times as the objective function. The improved A* algorithm is used to solve the problem: in order to adapt to the model, the objective function of the model is used as the evaluation function; in order to speed up the search efficiency, the branch and bound method is used for iterative search. The simulation results show that: the model can achieve bi-objective optimization, and it is reasonable. Compared with the traditional A* algorithm, the improved algorithm can better balance the optimization flight range and correction times, and save the algorithm planning time, and effectively complete the fast path planning of fixed-wing UAV with multiple constraints.KeywordsFixed-wing UAVPath planningPositioning errorImproved A* algorithmBranch and bound method
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