14 papers
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…
FORGE: Towards Functional Tool-Use Generalization via Keypoint Trajectory Reasoning
Chuhao Zhou, Liquan Wang, Shuxin Cao +5
While humans readily repurpose a book, a stone, or a shoe to drive a nail, robots trained on specific tools fail to transfer the same function to novel ones -- a gap we formalize a…
Conformal Path Reasoning: Trustworthy Knowledge Graph Question Answering via Path-Level Calibration
Shuhang Lin, Chuhao Zhou, Xiao Lin +5
Knowledge Graph Question Answering (KGQA) offers grounded, interpretable reasoning, but existing methods often fail to provide reliable coverage guarantees over retrieved answers.…
Rethinking Implicit Spatial Representation in Visuomotor Policy Learning
Xiangyu Chen, Yuxuan Hu, Chuhao Zhou +1
Generative model-based imitation learning has become a widely adopted paradigm for robotic manipulation, where policy performance depends critically on the conditioned visual repre…
Gaze2Act: Gaze-Conditioned Vision-Language-Action Policies for Interactive Robot Manipulation
Kuangji Zuo, Gen Li, Bofan Lyu +9
Vision-Language-Action (VLA) models have recently shown strong potential for robot learning by following language instructions. However, in practice, language alone is often insuff…
CompassAD: Intent-Driven 3D Affordance Grounding in Functionally Competing Objects
Jingliang Li, Jindou Jia, Tuo An +7
When told to "cut the cake," a robot must choose the knife over nearby scissors, despite both objects affording the same cutting function. In real-world scenes, multiple objects ma…