collaborators

10 papers

cs.RO2026

Touch2Robot: Robot Touch in the Human Demonstration Loop

Shengcheng Luo, Xiaoyang Cheng, Hong Ying +6

Human demonstrations offer a scalable way to collect manipulation data, but their contacts may be unstable or infeasible when transferred to a robot hand. Collecting demonstrations…

cs.RO2026

τ: Learning Touch-Augmented Vision-Language-Action Models from Future Visual Supervision

Ning Cheng, Jinan Xu, Wanlin Li +5

Incorporating tactile sensing into Vision-Language-Action (VLA) models holds promise for contact-rich manipulation, where visual observations alone often fail to capture critical c…

cs.RO2026

CAAT: Contact-Aware Attention Scaling and Tactile Masking for Data-Efficient Contact-Rich Manipulation

Jiaming Jiang, Yuzhe Huang, Hao Liang +7

In contact-rich manipulation, visual observations primarily guide motion in free space, whereas tactile observations become particularly informative during contact. However, standa…

cs.RO2026

DexMani: Human-Derived Manipulability Guidance for Dexterous Rotation

Xiaoyang Chen, Shengcheng Luo, Haoran Guo +4

Dexterous object rotation is a sequential contact problem: each support, release, and re-contact decision must both produce the desired object motion, and prepare the hand configur…

cs.RO2026

Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learning

Shengcheng Luo, Xiyan Huang, Zhe Xu +3

Blind grasping with a dexterous hand is a crucial manipulation capability. Nevertheless, learning such tactile-only policies for real robots remains challenging due to the tactile…

cs.RO2026

Tac2Pix: Image-Space Visuo-Tactile Fusion for Dexterous Manipulation

Shengcheng Luo, Kefei Wu, Xiaoying Zhou +3

Vision and touch are naturally complementary for dexterous manipulation. Yet they are represented in fundamentally different forms: visual observations are dense and spatially stru…

cs.RO2026

TaF-VLA: Tactile-Force Alignment in Vision-Language-Action Models for Force-aware Manipulation

Yuzhe Huang, Pei Lin, Wanlin Li +5

Vision-Language-Action (VLA) models have recently emerged as powerful generalists for robotic manipulation. However, due to their predominant reliance on visual modalities, they fu…

cs.RO2025

SuperMag: Vision-based Tactile Data Guided High-resolution Tactile Shape Reconstruction for Magnetic Tactile Sensors

Peiyao Hou, Danning Sun, Meng Wang +5

Magnetic-based tactile sensors (MBTS) combine the advantages of compact design and high-frequency operation but suffer from limited spatial resolution due to their sparse taxel arr…

cs.RO2025

ControlVLA: Few-shot Object-centric Adaptation for Pre-trained Vision-Language-Action Models

Puhao Li, Yingying Wu, Ziheng Xi +8

Learning real-world robotic manipulation is challenging, particularly when limited demonstrations are available. Existing methods for few-shot manipulation often rely on simulation…

cs.RO2025

PP-Tac: Paper Picking Using Tactile Feedback in Dexterous Robotic Hands

Pei Lin, Yuzhe Huang, Wanlin Li +3

Robots are increasingly envisioned as human companions, assisting with everyday tasks that often involve manipulating deformable objects. Although recent advances in robotic hardwa…