基于改进DECBBA-SR算法的异构多无人飞行器任务分配OA

Aiming at the problem of real-time multi-class complex task planning of heterogeneous multi-unmanned aerial vehicles under obstacle environment,the distributed solution of task assignment model is studied.An improved consensus-based bundling algorithm(CBBA)is proposed.The marginal cost function of task package construction is redesigned and the path planning cost calculation is coupled based on the rapidly-exploring random tree star(RRT*)algorithm.The task selection operation is optimized during package construction,and a local on-demand selection communication optimization conflict resolution mechanism is designed.A local task path set reconstruction mechanism is proposed for solving dynamic task assignment problems.The simulation results show that under the obstacle and dynamic environment,the convergence time of dynamic assignment of the improved algorithm is reduced by 38.1%,the total score is increased by 15.1%,and the total flight distance is reduced by 58.0%.Moreover,it satisfies multiple constraints such as task timing,time window,aircraft resource limitation,dynamic task addition,etc.,and achieves efficient task assignment with high feasibility and real-time performance.