Distributed multi-UAV cooperation for path planning by an NTVPSO-ADE algorithm
Liangliang Lu, Jiyang Dai, Ying Jin · 2022 41st Chinese Control Conference (CCC) · 2022
Multi-UAV cooperative trajectory planning faces issues such as model establishment difficulty and a considerable amount of computation. This work proposes a distributed hybrid particle swarm optimization (PSO) and differential evolution (DE) technique. A nonlinear time-varying PSO (NTVPSO) is developed to update the velocity and position of the PSO, aiming at the difficult balance of exploration and exploitation search for PSO. An adaptive DE (ADE) is proposed in order to improve the information sharing between particles and the algorithm's convergence speed. In order to realize the collaborative planning of multiple UAVs, a distributed method is used to solve the single UAV trajectory planning task by using NTVPSO-ADE. The trace is fed back to the PSO velocity update formula to guide the direction of particle movement. The simulation results show that the algorithm is highly competitive in terms of path optimality and can be used as a viable alternative to solve multi-UAV cooperative trajectory planning problems.