3 papers
cs.RO2026
OmniTacTune: Policy-Agnostic Real-World RL for Tactile Residual Adaptation of Visual Policies
Kelin Yu, Haode Zhang, Harish Ravichandar +2
Visual policies learned from human videos, teleoperation, and robot demonstrations offer scalable motion priors, but often fail in contact-rich manipulation, where success signific…
cs.CV2025
ControlTac: Force- and Position-Controlled Tactile Data Augmentation with a Single Reference Image
Dongyu Luo, Kelin Yu, Amir-Hossein Shahidzadeh +3
Vision-based tactile sensing has been widely used in perception, reconstruction, and robotic manipulation. However, collecting large-scale tactile data remains costly due to the lo…
cs.RO2025
MimicTouch: Leveraging Multi-modal Human Tactile Demonstrations for Contact-rich Manipulation
Kelin Yu, Yunhai Han, Qixian Wang +3
Tactile sensing is critical to fine-grained, contact-rich manipulation tasks, such as insertion and assembly. Prior research has shown the possibility of learning tactile-guided po…