Research On3D Reconstruction And Roadheader Positioning Method Of Roadway Based On Monocular Vision And Laser Radar Fusion

As an important traditional energy industry in China,the demand of intelligent development of coal is directly related to the process of national economy and social intelligence.In order to solve the problem of mining imbalance,the intelligent level of tunneling equipment needs to be improved.Although automation and informatization of coal mine equipment made great progress.However,the traditional underground equipment posture and roadway measurement methods have problems such as insufficient stability and difficult global positioning.The paper proposed the overall plan of roadway 3D reconstruction and equipment positioning based on monocular vision and laser radar,use multi-sensor fusion method to realize tunneling equipment pose measurement,construction of roadway map with two-dimensional grid and three-dimensional point cloud,provide rich map information for positioning and orientation of tunneling equipment in complex environment of coal mine,complete the visualization of roadway environment and equipment pose,it is of great significance and application value to realize the intelligent and efficient production with fewer people even unmanned.In view of the possible point cloud motion distortion and real-time calculation problems in the process of coal mine underground map construction,characteristic of roadway boundary,establish a model of roadway map observation for lidar.Gathering scanning data of laser radar and preprocess laser radar point cloud data,research on bilateral filtering algorithm and feature extraction algorithm.Through PLICP point cloud matching algorithm,establish minimizing error function to complete the inter-frame pose estimation,obtain unified point clouds from different perspectives in robot motion.Constructed 2D grid map of roadway with consistent coordinate system,ensure the accuracy and efficiency of laser radar mapping.lay the foundation for joint map building.Aiming at the problems of insufficient features and difficult depth acquisition in monocular vision measurement process,proposed a tunneling equipment pose measurement scheme based on monocular vision.Establishing camera calibration model,calculate camera parameters.Extracting environmental features and matching feature points with ORB feature detection method,using RANSAC algorithm to eliminate mismatched points.Establishing The model of polar geometry algorithm to solve the optimized matching point pairs,realizing of pose estimation between camera frames.Proposing a pose solution model based on triangulation depth calculation method,based on the three-dimensional space point coordinates,use PNP solution method to solve the tunneling equipment pose,enhance visual measurement accuracy and stability,and lay the foundation for three-dimensional reconstruction of roadway.Aiming at the problems of visual feature loss and positioning difficulty under global coordinate in complex environment of coal mine,proposed a framework of loosely coupled slam algorithm based on monocular vision and lidar,integration of tunneling equipment synchronous positioning and mapping system.Established a joint calibration model of monocular vision and laser radar and solved pose conversion matrix.Through sensor time soft synchronization method,with the help of the linear interpolation method,obtained the position and pose of the visual corresponding time,completing key frame pose matching,realizing sensor data lever fusion.Constructing 3D point cloud map offline optimization model,optimizing 3D point cloud map by minimizing reprojection error.According to the key frame pose matching,completing the matching of 3D point cloud and 2D grid map,and the 3D reconstruction of roadway and the solution of tunneling equipment pose are realized.Finally,building the experimental platform to verify the theoretical method and evaluate the measurement performance of the system.The paper respectively verified the performance of monocular vision and lidar slam method,the positioning performance of combined salm method,the results show that the combined pose calculation method can achieve better positioning accuracy.Moving robot to verify the whole roadway map construction and equipment positioning technology in the corridor.Get aligned 2D grid maps and 3D point cloud maps and tunneling equipment motion trajectory,verify the effectiveness of 3D reconstruction method and equipment positioning technique.