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

• Published in: IEEE sensors journal 2024-11, p.1-1
• Main Authors: Li, Yuanyuan, Zou, Yuan, Zhang, Xudong, Zang, Zheng, Sun, Wenjing, Fan, Jie, Lu, Xiaoran, Li, Xingkun, Liu, Jiahui
• Format: Article
• Language: English
• Subjects: Extended Kalman Filter (EKF); Filtering; Global object tracking; Interpolation; Kalman filters; Laser radar; Light Detection and Ranging (LiDAR); Object tracking; Pedestrians; Real-time systems; Sensors; Simultaneous localization and mapping; Simultaneous Localization and Mapping (SLAM); Trajectory; Ultra-wideband (UWB); Unscented Kalman Filter (UKF)
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2024.3503056

The global trajectory of the leading vehicle in GNSS-denied scenarios is important for vehicle formation. To achieve this, this paper proposes LiDAR-UWB Global Object Tracking (LUGOT), which fuses LiDAR-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 PCHIP (Piecewise Cubic Hermite Interpolating Polynomial). Next, the synchronized data is combined with UWB measurements. Finally, the combined data is filtered using the introduced EKF/UKF with embedded outlier detection to determine the state of the object in the global coordinate system. To evaluate the filtering effect, this paper 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. The source code for LUGOT is available at: https://github.com/ly3106/LUGOT.