Abstract:

The cluster combat application of unmanned ground vehicles(UVS) is a hot research issue of the intersection of artificial intelligence and battle command. Aiming at the cooperative path planning multiple unmanned vehicles not meeting the dynamic threat condition requirement, by combining the global path planning algorithm A-STAR with the local path planning algorithm RL, from the perspective of perception to behavioral decision making, the cooperative path planning model of multiple unmanned vehicles is studied. The cooperative combat situation threat algorithm, state and action space, reward function and sphere of influence function are designed, the sub-models of formation configuration strategy generation and dynamic optimization of strike path are carried out, and the cooperative path planning control model of multiple unmanned vehicles based on autonomous learning is constructed and solved. An application example shows that the proposed path planning model can effectively cope with the requirements of multi-unmanned vehicle collaborative path planning task in complex urban environment,and has important theoretical research and practical application value.

Key words: real environment, multiple unmanned vehicles, collaboration, path planning