61 citations · 350 across the 65 of their papers we have counts for
5 papers · 1 filter
FOMI: A Force-Feedback Manipulation Interface for Teaching Contact-Rich Manipulation
Yishu Shen, Yiming Luo, Ruilin Wang +7
Robot-free collection with handheld interfaces enables scalable acquisition of human demonstrations for policy learning. However, existing handheld interfaces often provide limited…
Zero-WAM: In-Context World-Action Modeling from Human Videos for Open-Ended Task Generalization
Jiaming Zhou, Qihang Zhang, Gangwei Xu +9
Zero-shot cross-task generalization, where a policy must execute manipulation tasks never seen during training, remains a central challenge in robot learning. In large language mod…
Native Video-Action Pretraining for Generalizable Robot Control
Qihang Zhang, Lin Li, Luyao Zhang +26
The advent of video-action models offers a promising path for robot control. Nevertheless, we argue that repurposing video generative models designed for digital content creation i…
JODA: Composable Joint Dynamics for Articulated Objects
Tianhong Gao, Cheng Yu, Yinghao Xu +1
Articulated objects used in simulation and embodied AI are typically specified by geometry and kinematic structure, but lack the fine-grained dynamical effects that govern realisti…
Flow as the Cross-Domain Manipulation Interface
Mengda Xu, Zhenjia Xu, Yinghao Xu +4
We present Im2Flow2Act, a scalable learning framework that enables robots to acquire real-world manipulation skills without the need of real-world robot training data. The key idea…