Hengwang Ding — accepted AI-conference papers

2026

CPBA-LIWO: Continuous-Time LiDAR-Inertial-Wheel Odometry Based on Probabilistic Bundle Adjustment

Song Wu, Yunzhou Zhang, Yuezhang Lv, Wu Li, Sizhan Wang, Su Yan +1

ICRA 2026poster

LiDAR-based odometry is widely used in ground robot localization. However, current methods encounter challenges in accuracy and robustness due to structural degradation, system observational error, and accumulated error. To address the above issues, we propose CPBA-LIWO, a continuous-time LiDAR-Iner…

Cited by 0 Scholar ↗

2025

MSPA-LIO: LiDAR-Inertial Odometry with Multi-Scale Plane Adjustment

Su Yan, Shuying Zhao, Yunzhou Zhang, Hengwang Ding, Wu Li, Sizhan Wang +1

IROS 2025

Most current LiDAR-based odometry methods use point-to-local plane registration to constrain poses, ignoring the explicit plane structure in the environment. Due to noise interference and uneven distribution of point cloud, local planes are prone to tilt, resulting in registration errors. Therefore,

Cited by 0 Source ↗Scholar ↗