Ye Liang — accepted AI-conference papers

2026

A Novel DNN-Based Semi-Parametric Calibration Method for Parallel Robots Considering Non-Kinematic Parameters

Shuai Fan, Ye Liang, Yudong Wang, Lisi Geng, Cheng Zeng, Shaohui Feng +1

RA-L 2026

The pointing accuracy of pose adjusting parallel robots (PAPRs) is critical for the imaging quality of Cherenkov telescopes, making kinematic calibration crucial for improvement. However, non-geometric error sources like elastic deformation and joint clearances create an inevitable difference betwee

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2025

A Gait Phase Detection and Gait Spatio-temporal Features Extraction Method Based on the Inertial Measurement Unit*

Shuai Fan, Huiyong Luo, Yao Xiao, Ye Liang, Zelin Su, Guangkui Song +1

IROS 2025

The quantitative evaluation of the improvement of physical function is crucial for patients with impaired motor function, such as stroke, in conducting related rehabilitation training activities. Specially, a practical and easy-to-operate gait feature detection and extraction system for a home is ur

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