8 papers · 1 filter
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…
Grounded World Model for Semantically Generalizable Planning
Quanyi Li, Lan Feng, Haonan Zhang +4
In Model Predictive Control (MPC), world models predict the future outcomes of various action proposals, which are then scored to guide the selection of the optimal action. For vis…
SkillVLA: Tackling Combinatorial Diversity in Dual-Arm Manipulation via Skill Reuse
Xuanran Zhai, Zekai Huang, Longyan Wu +5
Recent progress in vision-language-action (VLA) models has demonstrated strong potential for dual-arm manipulation, enabling complex behaviors and generalization to unseen environm…
Abstracting Robot Manipulation Skills via Mixture-of-Experts Diffusion Policies
Ce Hao, Xuanran Zhai, Yaohua Liu +1
Diffusion-based policies have recently shown strong results in robot manipulation, but their extension to multi-task scenarios is hindered by the high cost of scaling model size an…
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…
Demonstrating the Octopi-1.5 Visual-Tactile-Language Model
Samson Yu, Kelvin Lin, Harold Soh
Touch is recognized as a vital sense for humans and an equally important modality for robots, especially for dexterous manipulation, material identification, and scenarios involvin…