Cooperative 4D trajectory planning for multi aerial vehicles combining receding horizon optimization and differential evolution algorithm in dynamic battlefield environment

Aiming to the problem of cooperative trajectory planning for multi aerial vehicles in dynamic battlefield environment, this article develops a cooperative four-dimensional trajectory planning method combining receding horizon optimization (RHO) and differential evolution algorithm, and the main contributions are threefold: (1) An effective framework for multi aerial vehicles cooperative trajectory planning in dynamic environment is introduced. Therein, RHO serves as the outer layer, while the DE algorithm is employed in the inner loop to implement local trajectory planning. (2) A population diversity-based adaptive DE algorithm, named PDADE, is proposed to tackle the issues of slow convergence speed and low convergence accuracy in the classical DE algorithm. (3) A flight speed adjustment strategy based on the required time of arrival is presented to ensure synchronization of arrival times. Eventually, some numerical simulations are conducted, and the performance of the proposed PDADE algorithm is compared with other seven state-of-the-art swarm optimization algorithms. The results demonstrate that PDADE achieves optimal convergence accuracy and convergence speed.