5 citations · 15 across the 17 of their papers we have counts for
4 papers · 1 filter
Mixture of Frames Policy: Multi-Frame Action Denoising for Bimanual Mobile Manipulation
Dian Wang, Jisang Park, Xiaomeng Xu +3
Robotic manipulation is inherently multi-frame: local actions may be simple in an end-effector frame, while transport, upright-object handling, and whole-body coordination are bett…
Pix2Act: Image-Space Manipulation Policies with Equivariant Augmentation
Haojie Huang, Linfeng Zhao, Haotian Liu +9
Representing manipulation actions as 2D trajectories in the camera plane provides a compact and interpretable basis for learning complex 3D manipulation policies. However, it also…
Action Map Policy: Learning 3D Closed-loop Manipulation via Pixel Classification
Haojie Huang, Zhang Ye, Linfeng Zhao +7
The action space poses a major challenge in robot learning, since it is often high-dimensional, can span long time horizons, and frequently admits multi-modal optimal solutions. A…
HoMMI: Learning Whole-Body Mobile Manipulation from Human Demonstrations
Xiaomeng Xu, Jisang Park, Han Zhang +6
We present Whole-Body Mobile Manipulation Interface (HoMMI), a data collection and policy learning framework that learns whole-body mobile manipulation directly from robot-free hum…