49 citations · 85 across the 4 of their papers we have counts for
4 papers
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…
The Ingredients of Real-World Robotic Reinforcement Learning
Henry Zhu, Justin Yu, Abhishek Gupta +5
The success of reinforcement learning for real world robotics has been, in many cases limited to instrumented laboratory scenarios, often requiring arduous human effort and oversig…
Benchmarking In-Hand Manipulation
Silvia Cruciani, Balakumar Sundaralingam, Kaiyu Hang +3
The purpose of this benchmark is to evaluate the planning and control aspects of robotic in-hand manipulation systems. The goal is to assess the system's ability to change the pose…
Pneumatic Modelling for Adroit Manipulation Platform
Vikash Kumar, Visak CV
ADROIT Manipulation platform is a pneumatically actuated, tendon driven 28 degree of freedom platform being developed for investigating complex hand manipulation behaviors. ADROIT…