Improved Golden Jackal Optimization-based 3D Path Planning of UAV in Distribution Network Inspection

This paper proposes an improved Golden Jackal optimization (IGJO) to solve the three-dimensional path planning of unmanned aerial vehicle (UAV) in the complex inspection environment of distribution network. The proposed Golden Jackal observation strategy improves the location update formula by considering the boundary information of the search space of the solution. At the same time, a balanced renewal mechanism is proposed to enhance the ability of the population to jump out of the local extremum. According to the inspection task and environment characteristics of distribution network of UAV, the fitness function model of route planning is constructed, and a three-dimension (3D) simulation map model is built. The effect of IGJO is verified by two groups of simulation experiments. The experimental results show that IGJO has better solution quality, good algorithm robustness and fast convergence characteristics, which verify the feasibility and superiority of IGJO in solving complex 3D path planning problems.