UAV Cooperative Path Planning Method Based on Deep Learning Technology

With the development of modern information technology, as one of the core technologies of mission planning, UAV track planning (TP) has become an essential technical means to realize precision guided weapons. How to quickly plan a better track is one of the key technologies to improve the effectiveness of UAV combat system. Based on deep learning technology, this paper studies the coordinated path planning method of UAV; This paper introduces the composition of path planning, analyzes the difficulties existing in path planning and tracking control methods, finally studies and designs the UAV path planning process, finally introduces the network neural algorithm of deep learning technology into UAV cooperative path planning, and analyzes the UAV path planning system and mission threat through simulation experiments. In the simulation process, 45 nodes are excited at t = 5.828. Finally, combined with the example and simulation results, the feasibility of the TP algorithm is proved. The algorithm can plan the better track more efficiently, and can still plan the reasonable track with the increase of obstacles in the combat environment.