11 citations · 15 across the 5 of their papers we have counts for
7 papers
Vision-Force Admittance Learning for Peg Insertion into a Movable Hole
Yuzhong Chen, Yongqing Liang, Yunzhi Xu +6
Precise manipulation in dynamic environments, whether induced by a mobile robot base or a target with unknown motion, remains a major challenge in robotics. Manipulation in dynamic…
From Intention to Execution: Probing the Generalization Boundaries of Vision-Language-Action Models
Irving Fang, Juexiao Zhang, Shengbang Tong +1
One promise that Vision-Language-Action (VLA) models hold over traditional imitation learning for robotics is to leverage the broad generalization capabilities of large Vision-Lang…
GARF: Learning Generalizable 3D Reassembly for Real-World Fractures
Sihang Li, Zeyu Jiang, Grace Chen +9
3D reassembly is a challenging spatial intelligence task with broad applications across scientific domains. While large-scale synthetic datasets have fueled promising learning-base…
FusionSense: Bridging Common Sense, Vision, and Touch for Robust Sparse-View Reconstruction
Irving Fang, Kairui Shi, Xujin He +7
Humans effortlessly integrate common-sense knowledge with sensory input from vision and touch to understand their surroundings. Emulating this capability, we introduce FusionSense,…
VLM See, Robot Do: Human Demo Video to Robot Action Plan via Vision Language Model
Beichen Wang, Juexiao Zhang, Shuwen Dong +2
Vision Language Models (VLMs) have recently been adopted in robotics for their capability in common sense reasoning and generalizability. Existing work has applied VLMs to generate…
LUWA Dataset: Learning Lithic Use-Wear Analysis on Microscopic Images
Jing Zhang, Irving Fang, Juexiao Zhang +7
Lithic Use-Wear Analysis (LUWA) using microscopic images is an underexplored vision-for-science research area. It seeks to distinguish the worked material, which is critical for un…
EgoPAT3Dv2: Predicting 3D Action Target from 2D Egocentric Vision for Human-Robot Interaction
Irving Fang, Yuzhong Chen, Yifan Wang +8
A robot's ability to anticipate the 3D action target location of a hand's movement from egocentric videos can greatly improve safety and efficiency in human-robot interaction (HRI)…