12 citations · 21 across the 7 of their papers we have counts for
8 papers
RobotIO: A Python Library for Robot Manipulation Experiments
Lukas Hermann, Max Argus, Adrian Roefer +2
Setting up robot environments to quickly test newly developed algorithms is still a difficult and time consuming process. This presents a significant hurdle to researchers interest…
What Matters in Language Conditioned Robotic Imitation Learning over Unstructured Data
Oier Mees, Lukas Hermann, Wolfram Burgard
A long-standing goal in robotics is to build robots that can perform a wide range of daily tasks from perceptions obtained with their onboard sensors and specified only via natural…
Affordance Learning from Play for Sample-Efficient Policy Learning
Jessica Borja-Diaz, Oier Mees, Gabriel Kalweit +3
Robots operating in human-centered environments should have the ability to understand how objects function: what can be done with each object, where this interaction may occur, and…
CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
Oier Mees, Lukas Hermann, Erick Rosete-Beas +1
General-purpose robots coexisting with humans in their environment must learn to relate human language to their perceptions and actions to be useful in a range of daily tasks. More…
Pre-training of Deep RL Agents for Improved Learning under Domain Randomization
Artemij Amiranashvili, Max Argus, Lukas Hermann +2
Visual domain randomization in simulated environments is a widely used method to transfer policies trained in simulation to real robots. However, domain randomization and augmentat…
Hindsight for Foresight: Unsupervised Structured Dynamics Models from Physical Interaction
Iman Nematollahi, Oier Mees, Lukas Hermann +1
A key challenge for an agent learning to interact with the world is to reason about physical properties of objects and to foresee their dynamics under the effect of applied forces.…