Research on Collaborative Path Planning Method for Cluster of Cruise Missiles
For the problem that traditional heuristic algorithms are difficult to extract empirical models from large sample ter-rain data in a timely manner,a cooperative path planning method based on attention reinforcement learning for multi-patrol missiles is proposed.This collaborative optimization method integrates the influencing factors such as survival probability,path length,load balance and endurance constraints.Attention neural networks are used to generate cooperative reconnaissance strategies for patrol missiles,and a large amount of simulated data is tested to optimize the attention network using the REINFORCE algorithm.The ex-perimental results show that the proposed method can effectively solve the multi-patrol missile path planning problem with high re-al-time requirements,and the solution time is smaller than that of traditional algorithms.
国家科技期刊平台
NSTL
万方数据
