A path planning method for UAVs based on multi-objective pigeon-inspired optimisation and differential evolution
by Bingda Tong; Lin Chen; Haibin Duan
International Journal of Bio-Inspired Computation (IJBIC), Vol. 17, No. 2, 2021

Abstract: Inspired by the behaviour of pigeon flocks, an improved method of path planning and autonomous formation for unmanned aerial vehicles based on the pigeon-inspired optimisation and differential evolution is proposed in this paper. Firstly, the mathematical model for UAV path planning is devised as a multi-objective optimisation with three indices, i.e., the length of a path, the sinuosity of a path, and the risk of a path. Then, the method integrated by pigeon-inspired optimisation and mutation strategies of differential evolution is developed to optimise feasible paths. Besides, Pareto dominance is applied to select the global best position of a pigeon. Finally, a series of simulation results compared with standard particle swarm optimisation algorithm and standard differential evolution algorithm show the effectiveness of our method.

Online publication date: Thu, 08-Apr-2021

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