A Review of the Research on UAV Swarm Confrontation under Incomplete Information
UAV (Unmanned Aerial Vehicle) swarm, with its application advantages and development prospects, has become one of the current hot spots of interest for researchers in the field of artificial intelligence. The UAV swarm confrontation technology under incomplete information has become one of the research directions with the highest requirements for swarm cooperativeness and intelligence due to the high dynamics of swarm structure changes and the complex and variable environmental information that cannot be fully perceived. Its research achievements can promote the rapid development and wide application of intelligent unmanned systems. This paper comprehensively reviews of the recent progress in the research of UAV swarm confrontation under incomplete information environments. According to the Observe-Orient-Decide-Act (OODA) loop theory, the UAV swarm confrontation process is divided into four interlocking key components of situation assessment, intention inference, mission planning, and maneuver decision, and is further subdivided into eight sub-research objectives. By analyzing and comparing the relevant research works in recent years, the research focuses and difficulties of various tasks in the field of UAV swarm confrontation and the achieved research results are highlighted, and the challenges faced by UAV swarm confrontation technology are discussed, including the cooperative control of large-scale heterogeneous swarms, the handling of incomplete information, the modeling of complex decision-making processes, and the tackling of practical application tasks.
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维普
