3D High-precision Map Reconstruction Algorithm for Open-pit Mines Based on Harris3D-FPFH-MC
Three-dimensional high-precision map is the basis of intelligent transportation system in open-pit coal mine.Aiming at the consistency problem of three-dimensional map construction of large-scale height change scenes in open-pit coal mine,a three-dimensional map reconstruction method based on Harris3D-FPFH-MC is proposed.Firstly,the modified dynamic radius filtering method is used to preprocess the original point cloud data and remove the noise points in the point cloud.Sec-ondly,the ground point cloud is extracted by RANSAC method,and the ground plane equation is constructed by least square method for the extracted three-dimensional point cloud.Then,Harris3D-FPFH is used to expand the feature vector to form a 249-dimensional description vector of the key points.The point cloud matching pair is obtained based on the mutual consistency method,and the rotation and shift matrix between the two frame point clouds is calculated to build a three-dimensional map.Fi-nally,in the link of map optimization,the delay link is added to realize the back-end optimization of map construction.The ex-perimental results show that compared with the traditional Lio_Sam and Lego_Loam algorithms,the proposed algorithm reduces the absolute trajectory error and relative pose error,improves the accuracy of the 3D map of open-pit coal mine,effectively a-voids the problem of closed loop error or failure of closed loop caused by similar scenes in structure,and ensures the accuracy and robustness of the constructed map.It provides technical support for the application of point cloud registration technology in coal mines.
万方数据
维普
