Abstract
The fusion of 3D LiDAR and colour cameras requires the most accurate possible calibration of external parameters. In this paper, we reduce the edge errors of the LiDAR by selecting planar feature constraints. A new calibrator is used in the execution of our approach. A checkerboard calibration board is used to firstly solve the camera’s internal parameters. Next, a regular pyramid with checkerboard on three sides and a checkerboard calibration board is used as the calibrator to scan, extract the intersection of four planes as the feature points, and finally solve the external parameters of the LiDAR and the camera by registering the feature points. In addition, the method collects and processes multiple sets of data and introduces a global optimisation mechanism for loop closure detection to reduce cumulative errors.
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