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05/20/2023
DexPBT: Scaling up Dexterous Manipulation for Hand-Arm Systems with Population Based Training
In this work, we propose algorithms and methods that enable learning dex...
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10/25/2022
DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality
Recent work has demonstrated the ability of deep reinforcement learning ...
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06/21/2022
EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine
There has been significant progress in developing reinforcement learning...
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04/14/2022
Accelerated Policy Learning with Parallel Differentiable Simulation
Deep reinforcement learning can generate complex control policies, but r...
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10/27/2021
Reinforcement Learning in Factored Action Spaces using Tensor Decompositions
We present an extended abstract for the previously published work TESSER...
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10/02/2021
OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation
Learning performant robot manipulation policies can be challenging due t...
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08/24/2021
Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning
Isaac Gym offers a high performance learning platform to train policies ...
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08/22/2021
Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger
We present a system for learning a challenging dexterous manipulation ta...
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05/31/2021
Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Reinforcement Learning in large action spaces is a challenging problem. ...
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02/27/2020
In-Hand Object Pose Tracking via Contact Feedback and GPU-Accelerated Robotic Simulation
Tracking the pose of an object while it is being held and manipulated by...
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07/10/2019
Non-Smooth Newton Methods for Deformable Multi-Body Dynamics
We present a framework for the simulation of rigid and deformable bodies...
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10/12/2018
GPU-Accelerated Robotic Simulation for Distributed Reinforcement Learning
Most Deep Reinforcement Learning (Deep RL) algorithms require a prohibit...
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10/12/2018
