12 papers
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…
Near-sensor Computing for Rapid Visuotactile Perception
Zhengying Zhu, Ruilin Zhang, Runze Hu +1
Visuotactile sensors reconstruct dense contact geometry from measured surface gradients, but host-based processing increases power consumption and introduces data-transfer delays a…
Ego2Robot: Scalable Robot Data Synthesis from Egocentric Human Data
Ye Wang, Pei Lin, Xiong-Hui Chen +12
Learning generalizable robot manipulation policies requires large-scale and diverse demonstration data. Egocentric human manipulation videos offer rich scene and task diversity, an…
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…
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…
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…
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…
ETac: A Lightweight and Efficient Tactile Simulation Framework for Learning Dexterous Manipulation
Zhe Xu, Feiyu Zhao, Xiyan Huang +1
Tactile sensors are increasingly integrated into dexterous robotic manipulators to enhance contact perception. However, learning manipulation policies that rely on tactile sensing…
NLiPsCalib: An Efficient Calibration Framework for High-Fidelity 3D Reconstruction of Curved Visuotactile Sensors
Xuhao Qin, Feiyu Zhao, Yatao Leng +2
Recent advances in visuotactile sensors increasingly employ biomimetic curved surfaces to enhance sensorimotor capabilities. Although such curved visuotactile sensors enable more c…
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…
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…
Encountered-Type Haptic Display via Tracking Calibrated Robot
Chenxi Xiao, Yuan Tian
In the past decades, a variety of haptic devices have been developed to facilitate high-fidelity human-computer interaction (HCI) in virtual reality (VR). In particular, passive ha…