collaborators

6 papers

cs.CV2026

ViBA: Implicit Bundle Adjustment with Geometric and Temporal Consistency for Robust Visual Matching

Xiaoji Niu, Yuqing Wang, Yan Wang +2

Most existing image keypoint detection and description methods rely on datasets with accurate pose and depth annotations, limiting scalability and generalization, and often degradi…

cs.RO2026

PA-LVIO: Real-Time LiDAR-Visual-Inertial Odometry and Mapping with Pose-Only Bundle Adjustment

Hailiang Tang, Tisheng Zhang, Liqiang Wang +3

Real-time LiDAR-visual-inertial odometry and mapping is crucial for navigation and planning tasks in intelligent transportation systems. This study presents a pose-only bundle adju…

cs.RO2025

i2Nav-Robot: A Large-Scale Indoor-Outdoor Robot Dataset for Multi-Sensor Fusion Navigation

Hailiang Tang, Tisheng Zhang, Liqiang Wang +9

Accurate and reliable navigation is crucial for autonomous unmanned ground vehicles (UGVs). However, current UGV datasets fall short in meeting the demands for advancing navigation…

cs.RO2025

MSC-LIO: An MSCKF-Based LiDAR-Inertial Odometry with Same-Plane Cluster Tracking

Tisheng Zhang, Man Yuan, Linfu Wei +2

The multi-state constraint Kalman filter (MSCKF) has been proven to be more efficient than graph optimization for visual-based odometry while with similar accuracy. However, it has…

cs.RO2025

MR-ULINS: A Tightly-Coupled UWB-LiDAR-Inertial Estimator with Multi-Epoch Outlier Rejection

Tisheng Zhang, Man Yuan, Linfu Wei +3

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 en…

cs.RO2025

SELC: Self-Supervised Efficient Local Correspondence Learning for Low Quality Images

Yuqing Wang, Yan Wang, Hailiang Tang +1

Accurate and stable feature matching is critical for computer vision tasks, particularly in applications such as Simultaneous Localization and Mapping (SLAM). While recent learning…