Tactical Environment Path Planning Based on Improved A* Algorithm

Aiming at the problems faced by tactical environment path planning, such as limited computing and storage resources of combat units and unstable tactical communication network, a tactical environment path planning technology based on improved A* algorithm is proposed. Firstly, a convolutional neural network is used to obtain the depth feature information of the 3D geographic grid model, and then the machine learning is used to modify the A* algorithm heuristic function to determine the optimal candidate target nodes, and then distributed microservices are constructed for the path planning service, and finally the feasibility and effectiveness of the technique in the tactical environment is verified through simulation experiments.