Multi-UAV Cooperative Target Search Based on Behavior Expression Tree

This paper considers the problem of target search in unknown environments and proposes a Unmanned Aerial Vehicle (UAV) cooperative target search based on Behavior Expression Tree (BET). Using behavior expression tree as the structure of UAV motion control strategies helps handle unknown and complex environments, effectively solving problems such as target search, group response and obstacle avoidance. A Heuristic Optimization Algorithm based on Behavior Expression Tree (HOA-BET) is proposed to train and generate an effective behavior expression tree. Multiple tree update operators are designed to help the tree population update and evolve. The relationship between target search efficiency and UAV trajectory rationality is balanced through a mixed approach of multiple indicators. The effectiveness and reliability of the algorithm and control strategy have been demonstrated through comparison with various methods. Experiments in various scenarios have shown the adaptability of the control strategy generated by the algorithm to the environment. Additionally, it has good results when applied to large-scale target search.