4 papers · 1 filter
Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning
Shilin Shan, Chuhao Zhou, Ruize Wang +30
Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capability is particularly critical…
Heterogeneous Tactile Transformer
Jianxin Bi, Qiang Wang, Jayaram Reddy +4
Tactile sensors are inherently heterogeneous: a model trained on one sensor cannot be directly used on another, which limits learning contact-rich manipulation policies from divers…
VLA-Touch: Enhancing Vision-Language-Action Models with Dual-Level Tactile Feedback
Jianxin Bi, Kevin Yuchen Ma, Ce Hao +2
Tactile feedback is generally recognized to be crucial for effective interaction with the physical world. However, state-of-the-art Vision-Language-Action (VLA) models lack the abi…
Imitation Learning with Limited Actions via Diffusion Planners and Deep Koopman Controllers
Jianxin Bi, Kelvin Lim, Kaiqi Chen +2
Recent advances in diffusion-based robot policies have demonstrated significant potential in imitating multi-modal behaviors. However, these approaches typically require large quan…