I'm a PhD student in Computer Science at UC Berkeley advised by Prof. Sergey Levine and part of the Berkeley Artificial Intelligence Laboratory (BAIR) . In my research I focus on the development of algorithms for robotic manipulation using techniques from deep learning, deep reinforcement learning and classical robotics.I completed a Bachelor's degree in mechatronics and information technology and a master's degree in "Robotics Cognition Intelligence" at TU Munich (TUM).
Previously I have worked at the mechatronics institute of the German Aerospace Center (DLR) on the mechanical design and control system of a quadruped robot.
Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning
To enable a robot to continuously retry a task, we devise a self-supervised algorithm for learning image registration, which can keep track of objects of interest for the duration of the trial. We demonstrate that this idea can be combined with a video-prediction based controller to enable complex behaviors to be learned from scratch using only raw visual inputs, including grasping, repositioning objects, and non-prehensile manipulation.
Self-Supervised Visual Planning with Temporal Skip Connections
We present three simple improvements to self-supervised visual foresight algorithm that lead to substantially better visual planning capabilities. Our method can perform tasks that require longer-term planning and involve multiple objects.
© 2016 Frederik Ebert