9 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…
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…
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…