Research on Calibration Algorithm of Camera and LiDAR for Transport Vehicles in Open-pit Mines

Abstract

In the intelligent driving system of transport vehicles in open-pit mines, the data fusion of camera and LiDAR plays a vital role in the detection, recognition and tracking of obstacles. Aiming at the problem of camera and LiDAR spatial coordinate unity, that is establishing the correspondence between 2D coordinate system of image and 3D coordinate system of point cloud, this paper proposes a camera and LiDAR calibration method based on chessboard calibration board. Firstly, Zhang Zhengyou Calibration Method is used to calibrate the camera internal parameters, and the internal parameter matrix and distortion coefficient are obtained.Then the camera and LiDAR respectively extract the corner coordinates of the calibration plate edge, and multiple groups of the three-dimensional coordinates of point cloud and two-dimensional coordinates of the image are obtained. Based on multiple groups of feature point pairs, the external parameter matrix is obtained by EPnP algorithm. In order to verify the calibration accuracy, this paper projects the point cloud on the image plane and compares its point pair accuracy. Experimental results show that, this method can obtain the position and pose relationship between cameras and LiDAR, and the projection error is less than 3 pixels, which solved the problem of camera and LiDAR space calibration of transport vehicles in open-pit mines.

Keywords

• lidar
• camera
• parameter calibration
• fusing display
• point cloud projection
• transport vehicles in open-pit mines