On the Role of the Action Space in Robot Manipulation Learning and Sim-to-Real Transfer

no code implementations • 6 Dec 2023 • Elie Aljalbout, Felix Frank, Maximilian Karl, Patrick van der Smagt

Our findings have important implications for the design of RL algorithms for robot manipulation tasks, and highlight the need for careful consideration of action spaces when training and transferring RL agents for real-world robotics.

Reinforcement Learning (RL) Robot Manipulation

Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation

no code implementations • 29 Jan 2021 • Felix Frank, Alexandros Paraschos, Patrick van der Smagt, Botond Cseke

We unify previous adaptation techniques, for example, various types of obstacle avoidance, via-points, mutual avoidance, in one single framework and combine them to solve complex robotic problems.

Robotics