Power inspection path planning algorithm based on adaptive semantic map
In order to ensure the safe and stable operation of the power system,this study designs a power inspection path planning algorithm based on adaptive semantic map.Firstly,the power inspection image is obtained using the ORB-SLAM2 visual framework.After extracting the ORB features of the image,the YOLACT network is used to segment the image and obtain the instance mask.Secondly,deep information and adaptive region growth algorithm are used to complete semantic annotation.Thirdly,an adaptive seman-tic map of power inspection environment is constructed based on grid and Octree structure.Finally,based on the semantic map constructed above,the diffluent ant simulated annealing algorithm is combined with the chaos perturbation initialization algorithm to find an optimal patrol path.The experiment results show that the adaptive semantic map constructed by this algorithm can accurately describe the power inspection envi-ronment,and the power inspection path is short and the path planning efficiency is high.
semantic mapadaptivepower inspectionpath planningimproved ant colony algorithm
万方数据
维普
