車輪型移動ロボットのためのステアリングオフセットと平面LiDAR外部パラメータのオンライン同時較正
Online Joint Calibration of Steering Offset and Planar LiDAR Extrinsics for Wheeled Mobile Robots
倉庫移動ロボットのステアリングオフセットとLiDAR外部パラメータを、拡張カルマンフィルタを用いてオンラインで同時推定する手法を提案し、実データで横方向誤差を大幅に低減できることを示した。
著者: Subodh Mishra, Arindam Dhar, Suprotim Majumdar, Naveen Arulselvan
分類: cs.RO
原文アブストラクト
Accurate steering sensing and LiDAR-to-vehicle extrinsics are crucial for reliable path tracking in warehouse mobile robots (WMRs); miscalibration often leads to snaking, weaving, and elevated cross-track error (CTE). In practice, steering ``zero'' is commonly set manually (e.g., eyeballing straightness via a PS4 joystick), while LiDAR extrinsics are assumed from CAD and may drift after maintenance. Such static, manual procedures frequently cause miscalibration in safety-critical environments. This paper presents an Extended Kalman Filter (EKF)--based method for online estimation of steering offset and planar LiDAR extrinsics within a bicycle-kinematics model, providing a principled alternative to manual calibration. Experiments on real datasets show that correcting steering offset reduces CTE substantially, validating the effectiveness of the proposed approach.