棋盘
激光雷达
校准
计算机视觉
测距
人工智能
计算机科学
同时定位和映射
遥感
数学
地理
几何学
移动机器人
电信
机器人
统计
作者
Qing Wang,Chao Yan,Rongxuan Tan,Youyang Feng,Yang Sun,Yu Liu
出处
期刊:Measurement
[Elsevier]
日期:2022-09-23
卷期号:203: 111971-111971
被引量:13
标识
DOI:10.1016/j.measurement.2022.111971
摘要
Accurate and robust calibration of intrinsic and extrinsic parameters is crucial to multi-sensor simultaneous localization and mapping (SLAM) systems. However, extrinsic calibration of heterogeneous sensors is challenging owing to the differences in data acquisition methods. Therefore, we propose a more robust and convenient method to calibrate the intrinsic parameters for the camera and extrinsic parameters for cameras and light detection and ranging (LiDAR) sensors based on a 3D checkerboard. We tested the algorithm in simulation and real-world environments. Experiments in the simulation environment showed that our proposed method had similar accuracy as the state-of-the-art calibration method velo2cam_calibration.1 However, our proposed algorithm had less interaction and was more automatic. The real-world test also confirmed the results of our proposed method. Thus, the proposed method is a convenient means to calibrate intrinsic parameters for cameras, and extrinsic parameters for cameras and LiDAR sensors based on a 3D checkerboard.
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