Transactions of Nanjing University of Aeronautics & Astronautics
Coordinated Path Planning for UAVs Based on Sheep Optimization
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Abstract:
Using the traditional swarm intelligence algorithm to solve the cooperative path planning problem for multi-UAVs is easy to incur the problems of local optimization and a slow convergence rate. A cooperative path planning method for multi-UAVs based on the improved sheep optimization is proposed to tackle these. Firstly， based on the three-dimensional planning space， a multi-UAV cooperative cost function model is established according to the path planning requirements， and an initial track set is constructed by combining multiple-population ideas. Then an improved sheep optimization is proposed and used to solve the path planning problem and obtain multiple cooperative paths. The simulation results show that the sheep optimization can meet the requirements of path planning and realize the cooperative path planning of multi-UAVs. Compared with grey wolf optimizer （GWO）， improved gray wolf optimizer（IGWO）， chaotic gray wolf optimizer（CGWO）， differential evolution （DE） algorithm， and particle swam optimization （PSO）， the convergence speed and search accuracy of the improved sheep optimization are significantly improved.
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V279
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