Multi UAV cooperative mission planning under faults based on IDPSO

DOI:	10.11809/bqzbgcxb2023.06.030
Keywords:	UAV fault; task allocation; multi UAV coordination; improved discrete particle swarm optimization (IDPSO); Cauchy operator ; nonlinear time varying variation strategy; Hungarian algorithm
Abstract:	Aiming at the multi UAV cooperative mission planning after faults, this paper proposes a task reassignment method based on a combination of improved discrete particle swarm optimization (IDPSO) and Hungarian algorithm. Firstly, the Hungarian algorithm is used to rapidly rearrange the formation of UAVs under faults. Then, Cauchy operator is introduced to improve the global search ability of IDPSO to enhance the search space. At the same time, a nonlinear time varying mutation strategy is also proposed to accelerate the convergence speed of the algorithm. The IDPSO not only accelerates the convergence speed, but also improves the optimality of the solution. In addition, in the process of allocation, the environmental obstacles are taken into consideration, so the allocation results are more realistic and reasonable. Finally, the basic particle swarm optimization algorithm is used for UAV track planning, and the simulation experiments are carried out in three dimensional space. The results show that the designed algorithm can effectively improve the optimization results of the task allocation, which provides a theoretical basis for cooperative task allocation after multiple UAV faults.
Published:	2023-06-28
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