Abstract

This paper investigates the substation inspection problems of multimobile robots for large power stations in smart microgrids. Most multirobot inspection robots generally face the challenge of path planning, while the current widely used biological excitation neural network methods often have the defect of the neuronal active field near boundaries and obstacles. To end this, we propose an improved biological excitation neural network method for path planning based on a detailed architecture and ontology framework, through which the single-point inspection, multipoint inspection, and full-area inspection tasks of substations in smart microgrids can be well completed. Simulation results show that the designed IBENN-based multirobot collaboration inspection system can effectively shorten the path as well as the number of turns and then show better performance than most existing results when implementing various substation inspection tasks.