8 papers
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…
HT-Bench: Benchmarking and Learning Dexterous Full-Hand Tactile Representations with Egocentric Vision
Yuzhe Huang, Jiaping Wu, Jiaming Jiang +8
Establishing a universal benchmark for tactile representation learning in robotic manipulation remains challenging due to the diversity of tactile sensor designs, data formats, and…
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…
RGB-S: Image-Aligned Tactile Saliency for Robust Dexterous Manipulation
Shengcheng Luo, Kefei Wu, Xiaoying Zhou +3
Effective visuo-tactile integration is critical for robotic dexterous manipulation, especially when visual observations are unreliable or occluded. However, robustly aligning spars…