Skip to content
Log in
Sponsored AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI

Author

Wen-Qiang Li

View on Semantic Scholar

4 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access 2026

AMC-LIEKF: An Adaptive Maximum Correntropy Left-Invariant Extended Kalman Filter Method for Tightly Coupled Multi-UWB/IMU Integration

The error-state extended Kalman filter (ESKF) is widely used to fuse ultrawideband (UWB) and inertial measurement unit (IMU) data for robust localization in global navigation satellite system (GNSS)-denied environments. However, conventional ESKF-based fusion methods still face challenges such as geometric inconsistenc...

Cheng-Peng Yin, Xiang Yu, Rui-Chang Fan et al. · 0 citations
Oct 2026

LUNA: Light-Based Urban Navigation and Anchor via Geometric Structural Constraints

Robust visual localization for uncrewed aerial vehicles (UAVs) in urban environments is a critical capability, yet it remains challenging in low-light conditions where texture degradation compromises standard feature extraction. Existing solutions often rely on computationally intensive image enhancement or heavy multi...

Xin-Da Li, Bing-Bing Hang, Wen-Qiang Li et al. · 0 citations
Open access Sep 2026

Scene-Adaptive Line-Aware Visual Measurement Conditioning for Stereo Visual–Inertial Odometry

Accurate stereo visual–inertial measurement is essential for mobile robots operating in Global Navigation Satellite System (GNSS)-denied and structurally complex environments. In stereo visual–inertial odometry (VIO), pose and trajectory outputs depend strongly on the point measurements delivered by the visual front en...

Yi Liang, Bing-Bing Hang, Wen-Qiang Li et al. · 0 citations
Open access Sep 2026

Residual-Guided Hybrid Stochastic Modeling: A Two-Stage Learning Framework for Urban GNSS Positioning Enhancement

A residual-guided hybrid stochastic modeling framework that adjusts the pseudo-range observations to reduce the positioning loss without requiring true pseudo-range errors, which are difficult to obtain in real-world scenarios is proposed.

Juan Yin, Wen-Qiang Li, Rui-Chang Fan et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.