Real-Time Path Generation for UAV Swarms Using Receding Planning Framework and Priority Decoupling Mechanism

This paper presents a real-time path planning method combining receding planning framework and priority decoupling mechanism to solve the large-scale UAV swarms path generation problems. The receding planning framework is employed to decompose the swarm path planning problem into a number of short-horizon planning problems for reducing the problem dimension. In each receding horizon, the priority decoupling mechanism converts the swarm path planning problem as a series of single-UAV path planning problems to further reduce the computational cost. For the short-horizon single-UAV path planning problem, a customized sparse A* search algorithm (SAS) is used to compute the optimal/suboptimal paths efficiently. The obstacle/collision detection method is developed to eliminate inactive obstacle/collision avoidance constraints according to the relative position relation among obstacles and UAVs. The efficiency and effectiveness of the proposed method are verified in simulation with up to 50 UAVs and indoor flight experiments on 8 quadrotors. The experimental results demonstrate that this method can generate safe swarm paths within a few seconds and guide UAVs to fly in confined environments with obstacles.