Calibration of rotating 2D LIDAR based on simple plane measurement

Abstract

Purpose This paper aims to calibrate the mounted parameters between the LIDAR and the motor in a low-cost 3D LIDAR device. It proposes the model of the aimed 3D LIDAR device and analyzes the influence of all mounted parameters. The study aims to find a way more accurate and simple to calibrate those mounted parameters. Design/methodology/approach This method minimizes the coplanarity and area of the plane scanned to estimate the mounted parameters. Within the method, the authors build different cost function for rotation parameters and translation parameters; thus, the parameter estimation problem of 4-degree-of-freedom (DOF) is decoupled into 2-DOF estimation problem, achieving the calibration of these two types of parameters. Findings This paper proposes a calibration method for accurately estimating the mounted parameters between a 2D LIDAR and rotating platform, which realizes the estimation of 2-DOF rotation parameters and 2-DOF translation parameters without additional hardware. Originality/value Unlike previous plane-based calibration techniques, the main advantage of the proposed method is that the algorithm can estimate the most and more accurate parameters with no more hardware.

Design and Motion Planning of a Biped Climbing Robot with Redundant Manipulator

“…According to Equations (21)(22)(23)(24)(25)(26), the curves of position and pose angle of the end of the manipulator in the simulation are shown in Figures 17 and 18. In the first 5 s of the simulation, the end of the manipulator move forms the start point to working position along the spatial curve, and then move along a straight line at the root of the bracket.…”

“…In the first 5 s of the simulation, the end of the manipulator move forms the start point to working position along the spatial curve, and then move along a straight line at the root of the bracket. ω x = 0, 5 ≤ < 20 (24) ω y = 28.8 , 0 ≤ < 5 0, 5 ≤ < 20 (25) ω z = 28.8 , 0 ≤ < 5 0, 5 ≤ < 20 (26) According to Equations (21)(22)(23)(24)(25)(26), the curves of position and pose angle of the end of the manipulator in the simulation are shown in Figures 17 and 18. In the first 5 s of the simulation, the end of the manipulator move forms the start point to working position along the spatial curve, and then move along a straight line at the root of the bracket.…”

“…The IPC communicates with all 12 joint modules through the EtherCAT BUS, since it is suitable for the real-time control of the DC motor. Two microcontroller units (MCU), MCU1 and MCU2, are used to control the servo motor for the two rotating 2D LIDAR sensors and acquire the 3D point cloud of the work scene by fusing the angle information of the servo and the 2D point information from the 2D LIDAR [21]. The 3D point cloud information of the work scene is sent to the IPC for further processing through the CAN BUS.…”

MEMS-Scanner Testbench for High Field of View LiDAR Applications

“…Calibration of 3D LiDARs has been performed in the past, mainly focusing on the calibration of the entire device and the effects on mounting [ 6 , 7 ]. This ensures that the position of detected objects is correct compared to the coordinate system of the car.…”

Design of a Predictive RBF Compensation Fuzzy PID Controller for 3D Laser Scanning System

“…For the 3D laser scanning system, many researchers focus only on the optimization of the calibration process [16][17][18][19][20], while neglecting the influence of 2D Lidar motion control on the scanning results. In fact, there is a deviation between the actual pitching motion of the 2D Lidar and the ideal motion.…”