11 papers · 1 filter
TrAct: Bridging Robot Control and Visual Prediction with Visual Tracks
Zhi Cao, Howard Ji, Kevin Zhang +4
Robot actions are inherently embodiment-specific and only weakly aligned with image-space visual changes, limiting their effectiveness as conditioning signals for robot world model…
RoboTTT: Context Scaling for Robot Policies
Yunfan Jiang, Yevgen Chebotar, Ruijie Zheng +8
Recent robot foundation models operate with single-step or short-history visuomotor context. We introduce Test-Time-Training Robot Policies (RoboTTT), a robot model and training re…
T-Rex: Tactile-Reactive Dexterous Manipulation
Dantong Niu, Zhuoyang Liu, Zekai Wang +31
The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based Vision-Language-Action (VLA) mo…
StereoPolicy: Improving Robotic Manipulation Policies via Stereo Perception
Evans Han, Yunfan Jiang, Yingke Wang +6
Recent advances in robot imitation learning have produced powerful visuomotor policies that manipulate diverse objects from visual inputs. However, monocular observations lack dept…
SimFoundry: Modular and Automated Scene Generation for Policy Learning and Evaluation
Nadun Ranawaka, Josiah Wong, Wei-Lin Pai +15
Training and evaluating robot policies in the real world is costly and difficult to scale. We introduce SimFoundry, a modular and automated system for zero-shot real-to-sim scene c…
IMPASTO: Integrating Model-Based Planning with Learned Dynamics Models for Robotic Oil Painting Reproduction
Yingke Wang, Hao Li, Yifeng Zhu +6
Robotic reproduction of oil paintings using soft brushes and pigments requires force-sensitive control of deformable tools, prediction of brushstroke effects, and multi-step stroke…