Search Results for author: Thomas Lampe

Found 14 papers, 2 papers with code

Representation Matters: Improving Perception and Exploration for Robotics

no code implementations3 Nov 2020 Markus Wulfmeier, Arunkumar Byravan, Tim Hertweck, Irina Higgins, Ankush Gupta, tejas kulkarni, Malcolm Reynolds, Denis Teplyashin, Roland Hafner, Thomas Lampe, Martin Riedmiller

Furthermore, the value of each representation is evaluated in terms of three properties: dimensionality, observability and disentanglement.

Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics

no code implementations2 Jan 2020 Michael Neunert, Abbas Abdolmaleki, Markus Wulfmeier, Thomas Lampe, Jost Tobias Springenberg, Roland Hafner, Francesco Romano, Jonas Buchli, Nicolas Heess, Martin Riedmiller

In contrast, we propose to treat hybrid problems in their 'native' form by solving them with hybrid reinforcement learning, which optimizes for discrete and continuous actions simultaneously.

Self-Supervised Sim-to-Real Adaptation for Visual Robotic Manipulation

no code implementations21 Oct 2019 Rae Jeong, Yusuf Aytar, David Khosid, Yuxiang Zhou, Jackie Kay, Thomas Lampe, Konstantinos Bousmalis, Francesco Nori

In this work, we learn a latent state representation implicitly with deep reinforcement learning in simulation, and then adapt it to the real domain using unlabeled real robot data.

Domain Adaptation

Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer

no code implementations21 Oct 2019 Rae Jeong, Jackie Kay, Francesco Romano, Thomas Lampe, Tom Rothorl, Abbas Abdolmaleki, Tom Erez, Yuval Tassa, Francesco Nori

Learning robotic control policies in the real world gives rise to challenges in data efficiency, safety, and controlling the initial condition of the system.

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