Ph.D. Student XU Ruijie Presents Novel Wi-Fi RTT/LiDAR/IMU Integration Framework at IEEE/ION PLANS 2025

Ph.D. Student XU Ruijie Presents Novel Wi-Fi RTT/LiDAR/IMU Integration Framework at IEEE/ION PLANS 2025

From April 28 to May 1, 2025, PhD student Ruijie Xu from TASLAB attended the prestigious IEEE/ION Position, Location and Navigation Symposium (PLANS) in Salt Lake City, Utah, USA. At this leading conference for positioning, navigation, and timing technologies, Xu presented innovative research titled Tightly-Coupled Wi-Fi/LiDAR/Inertial Integration via Factor Graph Optimization for UAS.

The presented work addresses critical challenges of positioning in outdoor-indoor transition scenarios for Unmanned Autonomous Systems (UAS) by introducing a novel tightly-coupled multi-sensor fusion framework via FGO, implementing comprehensive integration of Wi-Fi Round-Trip-Time (RTT), LiDAR, and inertial measurements at the raw data level within a unified factor graph optimization framework. The proposed approach employs fault detection exclusion method to effectively handle both RTT measurement anomalies and LiDAR-inertial odometry drift. Experimental results demonstrated remarkable positioning accuracy in controlled indoor and challenging outdoor environments, respectively—representing substantial improvements over both conventional Wi-Fi RTT positioning and traditional LiDAR-inertial odometry.

The participation in IEEE/ION PLANS 2025 provided valuable opportunities for academic exchange and collaboration with international researchers in the positioning and navigation community, further strengthening our lab’s global research presence in navigation and positioning field.