Dynamic path planning of UAV for three-dimensional moving target search in complex environment

In view of the fact that most of the current studies on path planning are limited to the fixed target or the static environment, a path planning method of unmanned aerial vehicle (UAV) for three-dimensional moving target search in complex environments is proposed. In this method, the interactive maneuvering model is used to predict the motion state of the target, and then using the idea of hierarchical planning for reference, the guidance point is generated by the weighted sparse A star algorithm, which is combined with the model predictive control algorithm. The motion state of the target can be estimated more accurately, and the UAV can respond in real time accordingly. By introducing the large step strategy in the stage of weighted sparse A star algorithm, not only the time cost of path planning can be reduced, but also the infeasible areas in complex environment can be avoided in real time. The simulation results show that this method has strong predictability for environmental change and target motion, so as to guide the UAV to respond in advance and get a better path while meeting the real-time requirements.