Camera and laser radar joint calibration method based on L-shaped calibration plate

Abstract

The invention relates to a camera and laser radar joint calibration method based on an L-shaped calibration plate. The method includes: firstly, installing a camera and a laser radar on to-be-calibrated equipment; secondly, placing the L-shaped calibration plate on the ground in the field of view of equipment to be calibrated; starting a camera and a laser radar, carrying out data collection, and obtaining an image containing the L-shaped calibration plate and point cloud data; performing angular point detection on the image data to obtain pixel coordinates of feature angular points on two planes of the L-shaped calibration plate; performing plane segmentation and fitting on the point cloud data to obtain an equation of two planes of the L-shaped calibration plate, and further obtaining coordinates of feature angular points on the planes in a laser radar coordinate system through geometric information; and finally, on the basis of the pixel coordinates of the detected angular points and the coordinates in the laser radar coordinate system, calculating and obtaining pose changes of the camera and the laser radar. According to the method, the position of the angular point feature in the point cloud data can be accurately obtained, and the accuracy of joint calibration of the camera and the laser radar is greatly improved.

Description

technical field [0001] The invention relates to the joint calibration of a camera and a laser radar in the calibration field, in particular to a method for joint calibration of a camera and a laser radar based on an L-shaped calibration plate. Background technique [0002] Autonomous vehicles use various sensors to perceive the environment. In order to achieve high-quality perception in complex environments, it is necessary to fuse a variety of different sensor data to achieve more comprehensive perception. In autonomous driving systems, the most commonly used sensors are RGB cameras and multi-line lidar. RGB cameras can obtain high-resolution color and texture information, but cannot obtain high-precision depth information from image data. According to the time difference between emitting and receiving laser light, laser radar provides accurate distance and azimuth information of the detected point, and can work well at night. However, laser radar does not provide color in...

AI Technical Summary

Problems solved by technology

However, for low-beam lidar, due to the sparsity of the point cloud, it cannot accurately obtain the specific position of the feature points of the calibration plate in space, resulting in an increase in the matching error between the feature points in the image and the corresponding points in space, thereby reducing the Accuracy of camera and lidar extrinsic calibration

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