Decision-Making Support Method for High Speed Aircraft Swarm Path Planning Based on Semantic Information

The semantic information obtained during the perception process can provide primary feature information of the target and the environment. This information can be used to infer the deep-level features of the target and predict the target's future behavior, thereby optimizing decision-making. This paper focuses on the scenario of coordinated attack by high-speed aircraft swarm. We construct a semantic information network of the defender and the environment. Based on the primary feature information, we infer high-level information such as the defender's maneuvering route, the threat level to the attacker, and the reaction time. Based on the inferred future situation model, the artificial potential field (APF) method is used for collaborative path planning of high-speed aircrafts. This work is a basic framework for decision support for collaborative path planning of high-speed aircraft.