Raster Map Modelling Method and Application for UAV-Intelligent Robot Cooperative Inspection Path Planning

With the upgrading of voltage level, the electromagnetic environment of large-scale hub substations and the electrical, thermal, and force problems of power equipment are becoming increasingly prominent, and lean inspection is crucial. However, to cope with substation inspection scenarios with serious electromagnetic interference, the path nodes planned by the traditional grid method (TGM) are too many and cannot maintain a certain safety distance from obstacles. Therefore, this paper proposes a grid graph modeling method applicable to UAV (unmanned aerial vehicle)-intelligent robot cooperative inspection path planning. First, the raster is generated based on the actual substation layout structure, and then the vertices of the obstacle raster are extracted as feature points as new alternative points to plan the path. Then the artificial potential field (APF) method improved by large neighborhood search (LNS) is used to construct the UAV-intelligent robot cooperative inspection path optimization model. The results show that the new raster modeling method can be applied to the path planning of the improved Artificial Potential Field method, and the path can be optimized to make the inspection safer, especially for the operation of the UAV, and can improve the convergence speed of the algorithm, which is better than the traditional raster modeling method in terms of the comprehensive performance.