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Author

Ligang Liu

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Preprint Sep 2026

FoLD: Force-Informed Learning for Dexterous Articulated Object Manipulation

Transferring human demonstrations to dexterous robots remains challenging because differences in hand morphology and contact dynamics often cause retargeted motions to fail at producing the intended object behavior. We present \textbf{FoLD}, a framework for learning dexterous manipulation of articulated objects through...

Hao-Wei Shen, Ti-Ngai Li, Yu-Meng Liu et al. · 0 citations
Preprint Sep 2026

InterMASH: A Unified Geometric Representation for Grasp Synthesis

A conditional Diffusion Transformer that operates directly in the proposed InterMASH representation space and jointly generates hand geometry and contact, improving consistency and physical plausibility and shows that cross-embodiment fine-tuning with human grasp data can improve robotic grasp success and diversity.

Xuan-Ze Yang, Yu-Meng Liu, Hai-Yang Xin et al. · 0 citations
Open access Aug 2026

Mocap Denoising via Sparsity Optimization on High‐Order Motion Feature

This work introduces a novel motion prior based on the sparsity of high‐order temporal derivatives, serving as a kinematic proxy for impulsive force generation and achieves linear complexity, enabling efficient processing of long sequences.

Chenbin Li, Ligang Liu, Yongcong Zhang · 0 citations

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