Fixed-wing UAVs have been widely used in military and civil fields. It is a common UAV reconnaissance task to collaborate to locate the suspicious target by multiple UAVs, and the target location performance is highly dependent on the trajectory planned for UAVs. To complete this task, a multi-UAV collaborative trajectory planning method based on target location constraint A* (TLCA*) is proposed. In this method, the evaluation function of A* is improved in two stages. Firstly, multi-UAV can collaborate to locate the target in the shortest time by using time constraint, and then use the attraction idea in APF to maintain the collaborative location, to obtain longer time target location information. Experimental results show that the improved algorithm can meet both kinematic constraints and collaborative location task constraints. Compared with MHA* algorithm, the task completion is improved by 13.63%, and the planning time is shortened by about 45 times.

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Multi-UAV Collaborative Trajectory Planning Method Based on Target Location Constraint A* Algorithm

  • Pengcheng Yuan,
  • Chen Zhang,
  • Cong Guan,
  • Jingyu Ru,
  • Hongli Xu

摘要

Fixed-wing UAVs have been widely used in military and civil fields. It is a common UAV reconnaissance task to collaborate to locate the suspicious target by multiple UAVs, and the target location performance is highly dependent on the trajectory planned for UAVs. To complete this task, a multi-UAV collaborative trajectory planning method based on target location constraint A* (TLCA*) is proposed. In this method, the evaluation function of A* is improved in two stages. Firstly, multi-UAV can collaborate to locate the target in the shortest time by using time constraint, and then use the attraction idea in APF to maintain the collaborative location, to obtain longer time target location information. Experimental results show that the improved algorithm can meet both kinematic constraints and collaborative location task constraints. Compared with MHA* algorithm, the task completion is improved by 13.63%, and the planning time is shortened by about 45 times.