Path Planning of Substation Inspection Robot Based on SA-GA Algorithm

Power inspection is a crucial aspect in ensuring the safety and stability of electrical equipment. To address the challenges of high difficulty and low efficiency in substation inspection tasks, a novel approach is presented in this paper – a substation inspection robot path planning method based on a genetic simulated annealing algorithm. This method involves applying simulated annealing to the offspring population generated through selection, crossover, and mutation operations in the genetic algorithm. The result is the derivation of the optimal path for the inspection robot within the substation. Compared to traditional genetic algorithms and simulated annealing algorithms, this approach offers distinct advantages. It demonstrates superior optimization capabilities and convergence properties, effectively resolving the intricate path planning predicaments faced by inspection robots within substations. By synergizing the strengths of genetic algorithms and simulated annealing, this method surpasses the limitations of each technique in isolation.