激光雷达
计算机科学
稳健性(进化)
点云
计算机视觉
人工智能
像素
校准
遥感
GSM演进的增强数据速率
测距
地理
数学
统计
基因
电信
化学
生物化学
作者
Chongjian Yuan,Xiyuan Liu,Xiaoping Hong,Fu Zhang
标识
DOI:10.48550/arxiv.2103.01627
摘要
In this letter, we present a novel method for automatic extrinsic calibration of high-resolution LiDARs and RGB cameras in targetless environments. Our approach does not require checkerboards but can achieve pixel-level accuracy by aligning natural edge features in the two sensors. On the theory level, we analyze the constraints imposed by edge features and the sensitivity of calibration accuracy with respect to edge distribution in the scene. On the implementation level, we carefully investigate the physical measuring principles of LiDARs and propose an efficient and accurate LiDAR edge extraction method based on point cloud voxel cutting and plane fitting. Due to the edges' richness in natural scenes, we have carried out experiments in many indoor and outdoor scenes. The results show that this method has high robustness, accuracy, and consistency. It can promote the research and application of the fusion between LiDAR and camera. We have open-sourced our code on GitHub to benefit the community.
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