基于LiDAR扫描角度修正的障碍目标定位方法

doi:10.16180/j.cnki.issn1007-7820.2024.01.006

Abstract

Abstract:

When two-dimensional Laser Radar (LiDAR) is used for obstacle detection, the position change of mobile robot's own attitude usually leads to the change of LiDAR reference position, which will produce a large error in the positioning calculation of obstacle. In this study, an obstacle target location method based on LiDAR scanning angle correction is proposed. The K-means clustering algorithm is used to divide the LiDAR point cloud data, and then the angle correction processing is performed on the clustered data, so that the processed data information is more consistent with the real value. Finally, each cluster data is enveloped to improve the accuracy of LiDAR scanning data. The test results show that the the proposed method can improve the positioning accuracy and meet the requirement of accurate obstacle positioning.

Key words: 2D-LiDAR, mobile robot, attitude change, reference position, cluster division, angle correction, obstacle target location, accuracy

CLC Number:

TN401

ZHANG Mingkun,CAI Wenyu,ZHANG Shuai. Obstacle Target Positioning Based on LiDAR Scanning Angle Correction[J].Electronic Science and Technology, 2024, 37(1): 41-47.

Figures/Tables 11

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参数	数值
M/unit	5.0
k/unit	3.0
D_scan/m	20.0
W/m	0.4

Obstacle Target Positioning Based on LiDAR Scanning Angle Correction

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