回転初期化と段階的洗練による汎用LiDARキャリブレーション
Rotation Initialization and Stepwise Refinement for Universal LiDAR Calibration
複数LiDARの外部キャリブレーションを、事前知識不要の回転初期化と幾何・運動情報を統合した段階的最適化により、センサ非依存で高精度に行う手法を提案した。
著者: Yifan Duan, Xinran Zhang, Guoliang You, Yilong Wu, Xingchen Li, Yao Li, Xiaomeng Chu, Jie Peng, Yu Zhang, Jianmin Ji, Yanyong Zhang
分類: cs.RO
原文アブストラクト
Autonomous systems often employ multiple LiDARs to leverage the integrated advantages, enhancing perception and robustness. The most critical prerequisite under this setting is the estimating the extrinsic between each LiDAR, i.e., calibration. Despite the exciting progress in multi-LiDAR calibration efforts, a universal, sensor-agnostic calibration method remains elusive. According to the coarse-to-fine framework, we first design a spherical descriptor TERRA for 3-DoF rotation initialization with no prior knowledge. To further optimize, we present JEEP for the joint estimation of extrinsic and pose, integrating geometric and motion information to overcome factors affecting the point cloud registration. Finally, the LiDAR poses optimized by the hierarchical optimization module are input to time synchronization module to produce the ultimate calibration results, including the time offset. To verify the effectiveness, we conduct extensive experiments on eight datasets, where 16 diverse types of LiDARs in total and dozens of calibration tasks are tested. In the challenging tasks, the calibration errors can still be controlled within 5cm and 1{\deg} with a high success rate.
