UAV Path Planning Method Based on Modified Beluga Whale Optimization

With more and more widely use of Unmanned Aerial Vehicle (UAV), UAV path planning in 3D environment has become a significant and complicated task. This paper presents a new method for UAV path planning, which is based on a modified version of the Beluga Whale Optimization (BWO) algorithm. The proposed method introduces Sine-cosine algorithm to improve the exploration process of BWO, and then this Sine-cosine modified BWO (SBWO) is used to plan the flight path for UAV. The simulation results show that SBWO has obvious advantages in convergence speed. Besides, the use of SBWO can get better results in UAV 3D path planning, which shortens the shortest path by 5.6% and the execution time by 40.3 % on average compared with other algorithms, fully demonstrating its effectiveness.