UAV Path Planning Method based on Dual-strategy Improved Sparrow Search Algorithm

The effectiveness and efficiency of using drones for power transmission line inspection are closely related to the design of the inspection path. When dealing with constraints involving complex terrain, original sparrow search algorithm (SSA) is susceptible to issues such as local optimization and premature convergence. Aiming at solving the problems of convergence of UAV path planning in transmission line corridor monitoring, a dual-strategy improved sparrow search algorithm (DSSA) is proposed. In the paper, the flight environment containing threatening area is modeled firstly. Then, circle mapping and mirror reflection learning strategies are employed to address these shortcomings of SSA. Finally, the improved DSSA's performance is evaluated through testing its effectiveness in solving the UAV path planning problem. Experimental results demonstrate that it can rapidly generate a safe and feasible path, thus validating the efficacy of the proposed algorithm.