Dieter Büchler
Research Group Leader
Max-Planck-Ring 4
72076 Tübingen
Germany
My mission is to reach human performance at fast changing, uncertain, rich and high-dimensional tasks with robots. I believe this goal can be achieved by developing Machine Learning methods, especially Reinforcement Learning, for soft muscular systems.
I pursued a PhD in Machine Learning and Robotics with Jan Peters and Bernhard Schölkopf at the Robot Learning lab within the Empirical Inference dept. During my PhD I interned at X, the Moonshot Factory (formerly Google X). Before, I received a MSc degree in Biomedical Engineering at the Imperial College London and a BEng degree in Information and Electrical Engineering from HAW Hamburg in conjunction with Siemens.
For information and detailed construction details for the 4-DoF pneumatic artificial muscle actuated robot arm please send me an email: dbuechler[at]tue[dot]mpg[dot]de.
Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots
Video highlights the capabilities of robots actuated by pneumatic muscles to 1) generate highly accelerated motions and 2) prevent damage once such fast motions are executed on the real robot. We utilize this properties to tune controllers directly on the real system using Bayesian optimization without additional safety considerations. Data of unstable controllers (the racket motion is unstable in the video) can be incorporate rather than being avoided. Please also see the paper [1]
Video accompanying our ICRA 2016 paper 'A lightweight robotic arm with pneumatic muscles for robot learning'
Video accompanying our ICRA 2016 paper 'A lightweight robotic arm with pneumatic muscles for robot learning'. This video highlights the fast hitting motions that the four degrees of freedom robot is capable of generating and safely executing. This is realized purely using muscular actuation. This property is especially useful for Machine Learning approaches that explore. With our system we hope to enable exploration in fast motion domains and hence the application of Machine Learning in tasks like smashing table tennis balls.
Thank you for your interest in our group. We are constantly looking for motivated students that will work on projects related to muscular robots and learning, especially reinforcement learning. Please contact me via email and provide
- transcripts and
- a paragraph containing your motivation for applying.