Underground roadway shape variable monitoring algorithm based on laser radar

Abstract

In order to solve the problem of correct monitoring of underground roadway shape variables, a monitoring algorithm of underground roadway shape variables based on laser radar is designed based on the installation of high-precision laser radar and vehicle aided positioning system in underground intelligent vehicle; the overall framework of the monitoring algorithm is established, and the key technologies in laser radar data acquisition and preprocessing are described in detail; based on the existing knowledge accumulation of underground roadway scene monitoring and around the feature extraction of discrete points, an improved special point registration algorithm is constructed, which solves the problem that the feature points of roadway scene are sparse and can not be registered effectively; the distance from point to surface is used to pick out outliers, quickly calculate the offset of points, quickly extract high-density outliers through the density clustering algorithm of DBSCAN, quickly screen the deformation area, analyze the deformation degree, and realize the intelligent deformation monitoring of underground roadway surface. The test results show that the roadway deformation monitoring algorithm based on laser radar can monitor the roadway surface shape changes under logging in real time, dynamically and accurately, and can ensure the normal operation of underground roadway and protect the safety of miners’ life and property.

Keywords

• laser radar
• deformation monitoring
• density clustering
• icp algorithm
• underground roadway