ターゲットレス環境における高解像度LiDARとカメラのピクセル精度外部キャリブレーション
Pixel-level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments
チェッカーボードを使わず、自然エッジ特徴の位置合わせにより高解像度LiDARとRGBカメラの外部キャリブレーションをピクセル精度で自動化する手法を提案した論文。
著者: Chongjian Yuan, Xiyuan Liu, Xiaoping Hong, Fu Zhang
分類: cs.RO
原文アブストラクト
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.
