A calibration method of 2D LIDAR-Visual sensors embedded on an agricultural robot

Robust Calibration Technique for Precise Transformation of Low-Resolution 2D LiDAR Points to Camera Image Pixels in Intelligent Autonomous Driving Systems

“…Since the image points and corresponding LiDAR points are known, the MRE can be calculated by projecting the LiDAR points onto the image. Figure 8 shows the MRE obtained using various approaches: i.e., standard homography [17], optimized homography, and refined homography. A total of 30 data pairs of LiDAR scan and camera image were used for estimating the calibration parameters.…”

“…This work utilized a static pattern and a movable planar board to obtain the corresponding points between two sensors to estimate the homography matrix (i.e., a 3 × 3 matrix). Generally, estimating homography requires four or more corresponding points with no more than two collinear points [17]. To satisfy this condition, in this work, the edges of the calibration pattern, called edge points (five edges labeled as P 1 , P 2 , P 3 , P 4 , and P 5 ), were considered as the correspondence points.…”

“…Furthermore, to perform the calibration, the corresponding points from the LiDAR-camera have to be obtained. Hence, based on the technique used to obtain these corresponding points, the calibration approaches can be classified as target [1][2][3][4][5][6][7][9][10][11][12][13][14][15][16][17][18][19]22,23] and targetless [8,20,21].…”

“…In target-based methods, a calibration pattern is used to obtain the corresponding points to set up the constraint equations to compute the transformation matrix (i.e., rotational and translational vectors called extrinsic parameters). Commonly used calibration patterns to obtain the corresponding points between LiDAR-camera systems are the planar board [5][6][7]12,15,17], the V-shaped board [4,9,10,14], and the triangular board [1,11]. In [1], Li used a triangular checkerboard to compute the extrinsic parameters by minimizing the distance between the calculated projection and the real projection of the edges of the calibration pattern.…”

“…Abanay [17] has developed an approach to compute the plan-to-plan homography matrix using the manually selected image points obtained with the help of the IR image of the dual planar calibration patterns. The authors have used the SVD method to compute the homography matrix; however, the reprojection error was higher in this approach.…”