1.2k citations · 2.7k across the 112 of their papers we have counts for
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Point Tracking Improves World Action Models
Jiarui Guan, Wenshuai Zhao, Yue Pei +3
Robot policy learning benefits from world-action models that capture environment dynamics, but pixel-level prediction entangles dynamics with nuisance factors such as lighting and…
Dexterous Robotic Piano Playing at Scale
Le Chen, Yi Zhao, Jan Schneider +7
Endowing robot hands with human-level dexterity has been a long-standing goal in robotics. Bimanual robotic piano playing represents a particularly challenging task: it is high-dim…
RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands
Yi Zhao, Le Chen, Jan Schneider +5
It has been a long-standing research goal to endow robot hands with human-level dexterity. Bi-manual robot piano playing constitutes a task that combines challenges from dynamic ta…
RealAnt: An Open-Source Low-Cost Quadruped for Education and Research in Real-World Reinforcement Learning
Rinu Boney, Jussi Sainio, Mikko Kaivola +2
Current robot platforms available for research are either very expensive or unable to handle the abuse of exploratory controls in reinforcement learning. We develop RealAnt, a mini…
Learning to Drive (L2D) as a Low-Cost Benchmark for Real-World Reinforcement Learning
Ari Viitala, Rinu Boney, Yi Zhao +2
We present Learning to Drive (L2D), a low-cost benchmark for real-world reinforcement learning (RL). L2D involves a simple and reproducible experimental setup where an RL agent has…