An Improved Calibration Method for a Rotating 2D LIDAR System.

Yadan Zeng,Shuang Song,Mingqiang Lin,Houde Dai,Wei Jiang,Max Meng,Bo Sun,Heng Yu

doi:10.3390/s18020497

Abstract

This paper presents an improved calibration method of a rotating two-dimensional light detection and ranging (R2D-LIDAR) system, which can obtain the 3D scanning map of the surroundings. The proposed R2D-LIDAR system, composed of a 2D LIDAR and a rotating unit, is pervasively used in the field of robotics owing to its low cost and dense scanning data. Nevertheless, the R2D-LIDAR system must be calibrated before building the geometric model because there are assembled deviation and abrasion between the 2D LIDAR and the rotating unit. Hence, the calibration procedures should contain both the adjustment between the two devices and the bias of 2D LIDAR itself. The main purpose of this work is to resolve the 2D LIDAR bias issue with a flat plane based on the Levenberg–Marquardt (LM) algorithm. Experimental results for the calibration of the R2D-LIDAR system prove the reliability of this strategy to accurately estimate sensor offsets with the error range from −15 mm to 15 mm for the performance of capturing scans.

Highlights

Light detection and ranging (LIDAR) is a substantial contributing sensor for autonomous driving [1,2], 3D reconstruction [3,4,5], simultaneous localization and mapping (SLAM) [6,7,8,9,10] and visual navigation [11,12,13,14], etc
Several 3D scans were captured in three typical scenarios to prove the efficiency of adding bias adjustment
For the case of R2D-LIDAR system calibration, it was beneficial for adjusting sensor offset first since the bias angle that affects the transformation from spherical coordinates to rectangular coordinates behaves in a nonlinear fashion

Summary

Introduction

Light detection and ranging (LIDAR) is a substantial contributing sensor for autonomous driving [1,2], 3D reconstruction [3,4,5], simultaneous localization and mapping (SLAM) [6,7,8,9,10] and visual navigation [11,12,13,14], etc. With the benefits of high accuracy and ignoring of background illumination, the rotating two-dimensional light detection and ranging (R2D-LIDAR) becomes an attractive sensor for outdoor mobile robots [15]. A specially R2D-LIDAR system, which was composed of a 2D LIDAR and a rotating unit, performs more dense point cloud data with a low-cost prototype. Such a R2D-LIDAR system is a good choice for most applications. The skewing of the two devices, i.e., the 2D LIDAR and rotating unit, is a critical problem in the R2D-LIDAR system. To solve the skewing with two center excursion problems, Alismail et al [15]

Objectives

Methods

Findings

Conclusion