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Author

Masayoshi Tomizuka

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Preprint Sep 2026

TacGooseBumps (TacGB): Retrofitting Normal-Only Tactile Sensors with Shear Encoding for Learning Contact-Rich Manipulation

Contact-rich policies often fail because distinct physical states look alike yet require different actions. Cameras may not reveal whether a connector is aligned or fully seated, while many normal-only tactile sensors can miss the tangential interactions perpendicular to the grasping direction that distinguish these st...

Wen-Jie Li, Bing Yang, Yu-Xin Chen et al. · 0 citations
Preprint Sep 2026

A Reconfigurable Dual-Opposition Architecture for Single-Hand Assembly and Manipulation

In-hand assembly is constrained by the need to maintain grasps on two separate parts while controlling their relative motion within a single hand. To enable both in-hand assembly and manipulation, we present a reconfigurable dual-opposition architecture. Specifically, to support simultaneous grasping of two parts and c...

William Su, Yunosuke Nakamura, Yi-Xiao Wang et al. · 1 citation
Preprint Sep 2026

TacGooseBumps (TacGB): Retrofitting Normal-Only Tactile Sensors with Shear Encoding for Learning Contact-Rich Manipulation

Contact-rich policies often fail because distinct physical states look alike yet require different actions. Cameras may not reveal whether a connector is aligned or fully seated, while many normal-only tactile sensors can miss the tangential interactions perpendicular to the grasping direction that distinguish these st...

Wen-Jie Li, Bing Yang, Yu-Xin Chen et al. · 0 citations
Review Aug 2026

Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning

Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capability is particularly critical in contact-sensitive manipulation, where successful task execution depends not only on visual perception and motion generation, but also on...

Shilin Shan, Chu-Hao Zhou, Rui-Ze Wang et al. · 0 citations
Preprint Aug 2026

AdaDexGrasp: Adaptive Dexterous Grasping via 3D Visuo-Tactile Representation Fusion

This work proposes a unified visuo-tactile-fusion grasping framework that integrates grasp generation, feasibility prediction, and adaptive refinement and introduces an efficient visuo-tactile representation that tightly fuses object geometry with tactile feedback by associating tactile signals with finger identities.

Xi-Rui Liang, Jia-Qi Liang, Jing-Kai Xu et al. · 0 citations

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