Frederik Ebert

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
Frederik Ebert, Sudeep Dasari, Alex Lee, Chelsea Finn Sergey Levine
Conference on Robot Learning (CoRL), 2018
arXiv / code / video results and data

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
Frederik Ebert, Chelsea Finn, Alex Lee, Sergey Levine
Conference on Robot Learning (CoRL), 2017 (Long Talk)
arXiv / code / video results and data

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