MR-ULINS: マルチエポック外れ値除去を備えたUWB-LiDAR-慣性の密結合推定器
MR-ULINS: A Tightly-Coupled UWB-LiDAR-Inertial Estimator with Multi-Epoch Outlier Rejection
UWB・LiDAR・IMUを密結合し、UWBの系統誤差とNLOS外れ値をオンラインで推定・除去することで、GNSS拒否環境で約0.1mの高精度測位を実現した。
著者: Tisheng Zhang, Man Yuan, Linfu Wei, Yan Wang, Hailiang Tang, Xiaoji Niu
分類: cs.RO, eess.SP
原文アブストラクト
The LiDAR-inertial odometry (LIO) and the ultra-wideband (UWB) have been integrated together to achieve driftless positioning in global navigation satellite system (GNSS)-denied environments. However, the UWB may be affected by systematic range errors (such as the clock drift and the antenna phase center offset) and non-line-of-sight (NLOS) signals, resulting in reduced robustness. In this study, we propose a UWB-LiDAR-inertial estimator (MR-ULINS) that tightly integrates the UWB range, LiDAR frame-to-frame, and IMU measurements within the multi-state constraint Kalman filter (MSCKF) framework. The systematic range errors are precisely modeled to be estimated and compensated online. Besides, we propose a multi-epoch outlier rejection algorithm for UWB NLOS by utilizing the relative accuracy of the LIO. Specifically, the relative trajectory of the LIO is employed to verify the consistency of all range measurements within the sliding window. Extensive experiment results demonstrate that MR-ULINS achieves a positioning accuracy of around 0.1 m in complex indoor environments with severe NLOS interference. Ablation experiments show that the online estimation and multi-epoch outlier rejection can effectively improve the positioning accuracy. Besides, MR-ULINS maintains high accuracy and robustness in LiDAR-degenerated scenes and UWB-challenging conditions with spare base stations.
