Multi-Strategy Beluga Optimization Algorithm for UAV 3D Trajectory Planning

Aiming at the problem of UAV 3D trajectory planning in mountainous environment, a UAV 3D trajectory planning method based on Hybrid Spiral Adaptive Beluga Whale Optimization (HSABWO) is proposed, which firstly establishes a UAV 3D trajectory planning model in mountainous environment. Then, we introduce Chebyshev chaos mapping in Beluga Whale Optimization (BWO) to improve the quality of the initialized population, introduce the exponential adaptive exploration strategy to improve the global optimization ability, and embed the variable spiral exploration factor to avoid the algorithm falling into the local optimum, and introduce the vertical and horizontal crossover strategy to improve the algorithm's convergence speed and accuracy, and improve the algorithm's convergence speed and accuracy by testing in the basic test function. The performance of the improved algorithm is verified in the basic test function. Finally, the improved Moby Dick optimization algorithm is used for UAV 3D trajectory planning in mountainous environment. The simulation results show that the proposed improved Moby Dick optimization algorithm reduces the trajectory cost of the UAV path planning method significantly, and can effectively avoid the flight threat area.