A hierarchical mission planning method was proposed to solve a simultaneous attack mission planning problem for multi-unmanned aerial vehicles (UAVs). The method consisted of three phases aiming to decouple and solve the mission planning problem. In the first phase, the Pythagorean hodograph (PH) curve was used in the path estimation process for each UAV, which also served as the input for the task allocation process. In the second phase, a task allocation algorithm based on a negotiation mechanism was proposed to assign the targets. Considering the resource requirement, time-dependent value of targets and resource consumption of UAVs, the proposed task allocation algorithm can generate a feasible allocation strategy and get the maximum system utility. In the last phase, a path planning method was proposed to generate a simultaneous arrival PH path for each UAV considering UAV’s kinematic constraint and collision avoidance with obstacles. The comparison simulations showed that the path estimation process using the PH curve and the proposed task allocation algorithm improved the system utility, and the hierarchical mission planning method has potential in a real mission.
Development of Reinforcement Learning Based Mission Planning Method for Active Off-board Decoys on Naval Platforms
