1 citations · 1 across the 16 of their papers we have counts for
17 papers
Learning Visual Feature-Based World Models via Residual Latent Action
Xinyu Zhang, Zhengtong Xu, Yutian Tao +3
World models predict future transitions from observations and actions. Existing works predominantly focus on image generation only. Visual feature-based world models, on the other…
Tube Diffusion Policy: Reactive Visual-Tactile Policy Learning for Contact-rich Manipulation
Teng Xue, Alberto Rigo, Bingjian Huang +4
Contact-rich manipulation is central to many everyday human activities, requiring continuous adaptation to contact uncertainty and external disturbances through multi-modal percept…
Learning Tactile-Aware Quadrupedal Loco-Manipulation Policies
Pokuang Zhou, Yuhao Zhou, Quan Khanh Luu +7
Quadrupedal loco-manipulation is commonly built on visual perception and proprioception. Yet reliable contact-rich manipulation remains difficult: vision and proprioception alone c…
Stiffness Copilot: An Impedance Policy for Contact-Rich Teleoperation
Yeping Wang, Zhengtong Xu, Pornthep Preechayasomboon +4
In teleoperation of contact-rich manipulation tasks, selecting robot impedance is critical but difficult. The robot must be compliant to avoid damaging the environment, but stiff t…
TacVLA: Contact-Aware Tactile Fusion for Robust Vision-Language-Action Manipulation
Kaidi Zhang, Heng Zhang, Zhengtong Xu +7
Vision-Language-Action (VLA) models have demonstrated significant advantages in robotic manipulation. However, their reliance on vision and language often leads to suboptimal perfo…
MuxGel: Simultaneous Dual-Modal Visuo-Tactile Sensing via Spatially Multiplexing and Deep Reconstruction
Zhixian Hu, Zhengtong Xu, Sheeraz Athar +2
High-fidelity visuo-tactile sensing is important for precise robotic manipulation, yet most vision-based tactile sensors rely on opaque coatings that enable tactile sensing but blo…