Abstract
This paper proposes a calibration method for a self-rotating, linear-structured-light (LSL) scanning, three-dimensional reconstruction system based on plane constraints. The point cloud of plane target collected by the self-rotating, LSL scanning, 3D reconstruction system should be constrained to the basic principle of the plane equation; it can quickly and accurately calibrate the position parameters between the coordinate system of the LSL module and the coordinate system of the self-rotating, LSL scanning, 3D reconstruction system. Additionally, the transformation equation could be established with the calibrated optimal position parameters. This paper obtains the above-mentioned position parameters through experiments and uses the calibrated self-rotating, LSL scanning, 3D reconstruction system to perform three-dimensional scanning and reconstruction of the test piece. The experimental results show that the calibration method can effectively improve the measurement accuracy of the system.
Highlights
A self-rotating, linear-structured-light (LSL) scanning, 3D reconstruction system mounted on a mobile robot can be applied to the 3D reconstruction of the internal dimensions of structures such as pipelines [1,2,3], tunnels [4], tanks, indoor environments [5,6,7], nuclear reactor internals [8,9], underwater environments [10], etc
Aiming at the above problems, this paper proposes a calibration method for a selfrotating, LSL scanning, 3D reconstruction system based on plane constraints
According to the self-rotating, LSL scanning, 3D reconstruction system designed in Section 2, it was preliminarily estimated that the M value would be in the interval (110, 130), and the N value would be in the interval (395, 425)
Summary
A self-rotating, linear-structured-light (LSL) scanning, 3D reconstruction system mounted on a mobile robot can be applied to the 3D reconstruction of the internal dimensions of structures such as pipelines [1,2,3], tunnels [4], tanks, indoor environments [5,6,7], nuclear reactor internals [8,9], underwater environments [10], etc. It is necessary to establish a set of calibration methods to calibrate the position parameters between the coordinate system of the LSL module and the coordinate system of the self-rotating, LSL scanning, 3D reconstruction system to improve the measurement accuracy of the system. The distances are equal; the first data are used to find the offset angle, and the second data are used to verify the results, and the optimal solution is obtained This method only considers the skew problem and does not calibrate the position parameters of the two coordinate origins. By collecting the point cloud data of the plane target, based on the basic principle that the points on the plane target should be constrained by the plane equation, position parameters between the coordinate system of the LSL module and the coordinate system of the self-rotating, LSL scanning, 3D reconstruction system were calculated
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