24 citations · 27 across the 2 of their papers we have counts for
5 papers · 1 filter
Model-free Reinforcement Learning for Robust Locomotion using Demonstrations from Trajectory Optimization
Miroslav Bogdanovic, Majid Khadiv, Ludovic Righetti
We present a general, two-stage reinforcement learning approach to create robust policies that can be deployed on real robots without any additional training using a single demonst…
TriFinger: An Open-Source Robot for Learning Dexterity
Manuel Wüthrich, Felix Widmaier, Felix Grimminger +12
Dexterous object manipulation remains an open problem in robotics, despite the rapid progress in machine learning during the past decade. We argue that a hindrance is the high cost…
Learning to Explore in Motion and Interaction Tasks
Miroslav Bogdanovic, Ludovic Righetti
Model free reinforcement learning suffers from the high sampling complexity inherent to robotic manipulation or locomotion tasks. Most successful approaches typically use random sa…
Learning Variable Impedance Control for Contact Sensitive Tasks
Miroslav Bogdanovic, Majid Khadiv, Ludovic Righetti
Reinforcement learning algorithms have shown great success in solving different problems ranging from playing video games to robotics. However, they struggle to solve delicate robo…
Leveraging Contact Forces for Learning to Grasp
Hamza Merzic, Miroslav Bogdanovic, Daniel Kappler +2
Grasping objects under uncertainty remains an open problem in robotics research. This uncertainty is often due to noisy or partial observations of the object pose or shape. To enab…