LUGOT: LiDAR and UWB Fusion for Global Given Object Tracking Under Mobile Anchors

Yuanyuan Li, Yuan Zou*, Xudong Zhang*, Zheng Zang, Wenjing Sun, Jie Fan, Xiaoran Lu, Xingkun Li, Jiahui Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The global trajectory of the leading vehicle in Global Navigation Satellite System (GNSS)-denied scenarios is important for vehicle formation. To achieve this, this article proposes light detection and ranging (LiDAR)-ultrawideband (UWB) global object tracking (LUGOT), which fuses LiDAR simultaneous localization and mapping (SLAM) and UWB for object tracking in a global coordinate system within mobile-anchor scenarios. First, based on LiDAR-SLAM, the global high-frequency pose of the following vehicle is obtained. This pose is then synchronized with the UWB ultrahigh-frequency timestamp using piecewise cubic Hermite interpolating polynomial (PCHIP). Next, the synchronized data are combined with UWB measurements. Finally, the combined data are filtered using the introduced extended Kalman filter (EKF)/unscented Kalman filter (UKF) with embedded outlier detection to determine the state of the object in the global coordinate system. To evaluate the filtering effect, this article introduces cubic smoothing spline fitting to smooth the raw global path of the object as the ground truth. The experimental fleet platform was built to evaluate the effectiveness, outlier detection, and filtering effect of LUGOT. It avoids the long-tail effect and can be quickly commercialized with current technology.

Original languageEnglish
Pages (from-to)4882-4896
Number of pages15
JournalIEEE Sensors Journal
Volume25
Issue number3
DOIs
Publication statusPublished - 2025

Keywords

  • Extended Kalman filter (EKF)
  • global object tracking
  • light detection and ranging (LiDAR)
  • simultaneous localization and mapping (SLAM)
  • ultrawideband (UWB)
  • unscented Kalman Filter (UKF)

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