Multi-Satellite Collaboration Task Planning Based On Behavior Tree

As the number of satellites and satellite tasks continues to increase, multi-satellite collaboration task planning faces several challenges, including high complexity, high timeliness and limited scalability. This paper presents a method for task planning based on behavior tree, which leverages modularity and hierarchical structure of behavior tree to simplify planning process and enhance timeliness. We also propose an intelligent planning algorithm combining variable neighborhood search (VNS) algorithm with backtracking search algorithm (BSA) to reduce solution space and improve convergence speed. Experimental results show that this method improves satellite task planning timeliness by 16.7%, overcomes the flexibility and timeliness disadvantages of traditional methods in complex environments, and highlights the significant advantages and potential applications of behavior tree in multi-satellite collaboration field.