A joint measurement method based on lidar and binocular visible light camera

Abstract

The invention provides a joint measurement method based on a laser radar and a binocular visible light camera, which can obtain more accurate and dense three-dimensional information of a target simply and efficiently. In this joint measurement method, the lidar is assumed to be a camera device with fixed internal parameters, the 3D point cloud data is directly projected into a 2D image, and the image processing method is used to calibrate the lidar device and the dual The rotation and translation relationship between the cameras; among them, the idea of ​​finding the matrix norm and matrix trace is innovatively introduced to solve the rotation matrix; finally, the fusion of lidar and binocular stereo vision point cloud data can not only obtain accurate positions And attitude information, and can reconstruct the special texture and characteristic information of the target surface, which is very useful for the rendezvous and docking of spacecraft in the military field, the capture of hostile satellites, etc., as well as the workpiece measurement and unmanned driving in the civilian field. Value.

Description

technical field [0001] The invention belongs to the technical field of radar and visual measurement, and relates to a method for measuring three-dimensional information. Background technique [0002] Binocular vision mainly studies how to use computers to realize the functions of human eyes, that is, to use two-dimensional projection images to realize the perception, recognition and understanding of three-dimensional scenes in the objective world. With the rapid development of computer technology, people have more and more demands on 3D models. The working principle of binocular stereo vision measurement is to shoot a scene with two cameras in different positions, and obtain the three-dimensional coordinate value of the point according to the parallax of the spatial point in the two images. [0003] After long-term development of the visual measurement system, many advanced image processing methods have appeared. But vision systems can still only be used in engineering env...

AI Technical Summary

Problems solved by technology

[0009] 2) It is easy to introduce cumulative errors, and the accuracy is not guaranteed

The fitting process of the three planes must have errors, which will lead to the introduction of errors in the solution of the intersection points of the three planes, and then the calculated other grid coordinates will have errors

The results obtained by such methods are often not good, because the dependent calibration points need to be very large, and the calibration data must be optimized to obtain good calibration values

[0010] 3) As many grid points as possible should be used in the calibration to reduce the error, because the three-dimensional target has three sides, in order to allow the camera to capture as many grid points as possible, there are requirements for the placement of the target, if placed randomly, the captured The layout of the grid points in the image is irregular, and it is difficult to automatically complete the matching between the 3D grid points and the grid points of the 2D image. If there are too many points, manual intervention is very troublesome.

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