5 papers · 1 filter
Multi-Camera View Scaling for Data-Efficient Robot Imitation Learning
Yichen Xie, Yixiao Wang, Shuqi Zhao +4
The generalization ability of imitation learning policies for robotic manipulation is fundamentally constrained by the diversity of expert demonstrations, while collecting demonstr…
DexH2R: Task-oriented Dexterous Manipulation from Human to Robots
Shuqi Zhao, Xinghao Zhu, Yuxin Chen +5
Dexterous manipulation is a critical aspect of human capability, enabling interaction with a wide variety of objects. Recent advancements in learning from human demonstrations and…
DEXOP: A Device for Robotic Transfer of Dexterous Human Manipulation
Hao-Shu Fang, Branden Romero, Yichen Xie +9
We introduce perioperation, a paradigm for robotic data collection that sensorizes and records human manipulation while maximizing the transferability of the data to real robots. W…
DexCtrl: Towards Sim-to-Real Dexterity with Adaptive Controller Learning
Shuqi Zhao, Ke Yang, Yuxin Chen +5
Dexterous manipulation has seen remarkable progress in recent years, with policies capable of executing many complex and contact-rich tasks in simulation. However, transferring the…
Sparse Diffusion Policy: A Sparse, Reusable, and Flexible Policy for Robot Learning
Yixiao Wang, Yifei Zhang, Mingxiao Huo +8
The increasing complexity of tasks in robotics demands efficient strategies for multitask and continual learning. Traditional models typically rely on a universal policy for all ta…