4 papers · 1 filter
Robot Self-Improvement via Human-Video Dynamics Models
Hanzhi Chen, Anran Zhang, Simon Schaefer +5
A central question in robot learning is how to acquire skills from the kinds of data that humans learn from: passive observation, embodied practice, and the experience of failure.…
GOPLA: Generalizable Object Placement Learning via Synthetic Augmentation of Human Arrangement
Yao Zhong, Hanzhi Chen, Simon Schaefer +2
Robots are expected to serve as intelligent assistants, helping humans with everyday household organization. A central challenge in this setting is the task of object placement, wh…
Actron3D: Learning Actionable Neural Functions from Videos for Transferable Robotic Manipulation
Anran Zhang, Hanzhi Chen, Yannick Burkhardt +4
We present Actron3D, a framework that enables robots to acquire transferable 6-DoF manipulation skills from just a few monocular, uncalibrated, RGB-only human videos. At its core l…
VidBot: Learning Generalizable 3D Actions from In-the-Wild 2D Human Videos for Zero-Shot Robotic Manipulation
Hanzhi Chen, Boyang Sun, Anran Zhang +2
Future robots are envisioned as versatile systems capable of performing a variety of household tasks. The big question remains, how can we bridge the embodiment gap while minimizin…