Intrinsic Calibration of Multi-Beam LiDARs for Agricultural Robots

文献类型： 外文期刊

第一作者： Sun, Na

作者： Sun, Na;Zhao, Chunjiang;Sun, Na;Fan, Zhengqiang;Li, Tao;Feng, Qingchun;Zhao, Chunjiang;Qiu, Quan;Fan, Zhengqiang;Ji, Chao

作者机构：

关键词： three-dimensional; LiDAR; intrinsic calibration; nonlinear optimization; agricultural robot

期刊名称：REMOTE SENSING （ 影响因子：5.349； 五年影响因子：5.786 ）

ISSN：

年卷期： 2022 年 14 卷 19 期

页码：

收录情况： SCI

摘要： With the advantages of high measurement accuracy and wide detection range, LiDARs have been widely used in information perception research to develop agricultural robots. However, the internal configuration of the laser transmitter layout changes with increasing sensor working duration, which makes it difficult to obtain accurate measurement with calibration files based on factory settings. To solve this problem, we investigate the intrinsic calibration of multi-beam laser sensors. Specifically, we calibrate the five intrinsic parameters of LiDAR with a nonlinear optimization strategy based on static planar models, which include measured distance, rotation angle, pitch angle, horizontal distance, and vertical distance. Firstly, we establish a mathematical model based on the physical structure of LiDAR. Secondly, we calibrate the internal parameters according to the mathematical model and evaluate the measurement accuracy after calibration. Here, we illustrate the parameter calibration with three steps: planar model estimation, objective function construction, and nonlinear optimization. We also introduce the ranging accuracy evaluation metrics, including the standard deviation of the distance from the laser scanning points to the planar models and the 3 sigma criterion. Finally, the experimental results show that the ranging error of calibrated sensors can be maintained within 3 cm, which verifies the effectiveness of the laser intrinsic calibration.

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