Task Allocation and Trajectory Planning for Collaborative Adversarial Multi-UAVsystems

A algorithm-based approach for cooperative task allocation in multi-UAV adversarial missions is proposed. Taking into account flight time., fuel consumption., and introducing adversarial benefits as the optimization objective., the task allocation optimization mathematical model is constructed., considering flight constraints of the UAVs. Subsequently., a CLPSO algorithm is proposed for solving the problem., which exhibits superior global search capability compared to existing PSO algorithms. First., the particle positions are encoded as a set of matrix vectors., from which a corresponding set of feasible task assignment solutions is decoded., achieving the discretization of the particle swarm algorithm solution. Next., the CLPSO is employed to calculate the individual best and global best solutions for the particles., determining the corresponding strike sequence. Finally., a B-spline curve is fitted to the obtained strike sequence to generate a smooth path that is suitable for UAV flight. Simulation experiments demonstrate that the proposed method effectively addresses the task allocation problem in heterogeneous multi-UAV collaborative adversarial scenarios.