10 papers
FELT: Generating Tactile Signals from Vision for Visuo-Tactile Manipulation
Zinan Li, Yiyang Ling, Yuming Gu +8
The sense of touch is central to manipulation, especially when vision is occluded or ambiguous. Although combining vision and touch improves manipulation, learning robust visuo-tac…
PREFAIL: Identifying Precursors to Failures in Robotic Lift-and-Place Tasks to Improve Task Execution Performance
Zeyu Shangguan, Rajas Chitale, Rutvik Patel +2
Non-prehensile manipulation enables flexible material handling with part carriers, but friction-based support makes high-speed motions failure-prone, while slower operation increas…
HANDFUL: Sequential Grasp-Conditioned Dexterous Manipulation with Resource Awareness
Ethan Foong, Yunshuang Li, Hao Jiang +2
Dexterous robot hands offer rich opportunities for multifunctional manipulation, where a robot must execute multiple skills in sequence while maintaining control over previously gr…
Fix the Mind, Not the Move: Interpretable AI Assistance via Knowledge-Gap Localization
Ayano Hiranaka, Ya-Chuan Hsu, Stefanos Nikolaidis +2
AI assistants in human-AI collaboration often correct suboptimal human actions through behavioral feedback (e.g., alerts or steering-wheel nudges in assistive driving). Such interv…
OFlow: Injecting Object-Aware Temporal Flow Matching for Robust Robotic Manipulation
Kuanning Wang, Ke Fan, Chenhao Qiu +5
Robust robotic manipulation requires not only predicting how the scene evolves over time, but also recognizing task-relevant objects in complex scenes. However, existing VLA models…
Learning Geometry-Aware Nonprehensile Pushing and Pulling with Dexterous Hands
Yunshuang Li, Yiyang Ling, Gaurav S. Sukhatme +1
Nonprehensile manipulation, such as pushing and pulling, enables robots to move, align, or reposition objects that may be difficult to grasp due to their geometry, size, or relatio…