10 citations · 10 across the 1 of their papers we have counts for
3 papers
cs.RO2020★ 10 cited
Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning
Archit Sharma, Michael Ahn, Sergey Levine +3
Reinforcement learning provides a general framework for learning robotic skills while minimizing engineering effort. However, most reinforcement learning algorithms assume that a w…
cs.RO2019
ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots
Michael Ahn, Henry Zhu, Kristian Hartikainen +4
ROBEL is an open-source platform of cost-effective robots designed for reinforcement learning in the real world. ROBEL introduces two robots, each aimed to accelerate reinforcement…
cs.RO2019
Multi-Agent Manipulation via Locomotion using Hierarchical Sim2Real
Ofir Nachum, Michael Ahn, Hugo Ponte +2
Manipulation and locomotion are closely related problems that are often studied in isolation. In this work, we study the problem of coordinating multiple mobile agents to exhibit m…