An improved multi dimensional particle swarm based approach to multi UAV mission assignment

DOI:	10.11809/bqzbgcxb2023.07.030
Keywords:	spatial dimensionality; multi dimensional particle swarm algorithm; integer coding; multi UAV mission planning; set of fitness functions
Abstract:	This paper proposes a multi UAV mission assignment method based on an improved multi dimensional particle swarm algorithm to address the problems of uncertainty in the spatial dimension of multi UAV mission planning solutions and the change of mission requirements with time in complex battlefield environments. The method constructs a set of fitness functions and applies multiple fitness functions to restrict the population tendency, while using mapping variables based on time varying target values to establish a multi UAV target decision model with time varying target values. Then, it introduces an integer coding mechanism to construct multi dimensional particles oriented to the task sequence, and uses the improved adaptive multi dimensional particle swarm algorithm to obtain multi UAV mission planning optimization scheme under the optimal dimension. The simulation results show that the multi UAV mission planning method based on the improved multi dimensional particle swarm algorithm can obtain a better dynamic mission assignment effect in the optimal solution space with a faster convergence speed, which has good prospects for application.
Issue:	Vol. 44 No. 7 (2023)
Published:	2023-07-28
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