Department News

Awards for Two Master Theses at the Autonomous Motion Department

  • 07 June 2017

Cédric de Crousaz and Julian Viereck receive the ETH Medal for their outstanding Master Theses

Sebastian Trimpe Ludovic Righetti Julian Viereck Alexander Herzog


Finalist for the Best Robotic Vision Paper

  • 01 June 2017

at the 2017 IEEE/RAS International Conference on Robotics and Automation

The paper "Probabilistic Articulated Real-Time Tracking for Robot Manipulation" by Cristina Garcia Cifuentes, Jan Issac, Manuel Wüthrich, Stefan Schaal and Jeannette Bohg was finalist for the Best Robotic Vision paper at the 2017 IEEE/RAS International Conference on Robotics and Automation.

Cristina Garcia Cifuentes Manuel Wüthrich Jan Issac Stefan Schaal Jeannette Bohg


Release of Bayesian Articulated Object Tracking Libraries

  • 29 May 2017

Robust and real-time Bayesian articulated object tracking methods, implemented in C++ and CUDA.

We release open-source code and data sets on Bayesian articulated object tracking. The library contains approaches towards problems ranging from single object tracking to full robot arm pose estimation. The data sets allow the quantitative evaluation of alternative approaches thanks to accurate ground-truth annotations.

Cristina Garcia Cifuentes Jan Issac Manuel Wüthrich Jeannette Bohg



Local networking event for female researchers from Tübingen

  • 28 April 2017

Hosted this time by Jeannette Bohg

Jeannette Bohg


DOOMED - A new online learning approach from AMD in the spotlight

  • 01 March 2017

Text: Kathryn Ryan. New Rochelle, February 21, 2017.

Robotics researchers have developed a novel adaptive control approach based on online learning that allows for the correction of dynamics errors in real time using the data stream from the robot. The strategy is described in an article published in Big Data, a peer-reviewed journal from Mary Ann Liebert, Inc., publishers. The article is available free on the Big Data website until March 14, 2017.

Franzi Meier Daniel Kappler Nathan Ratliff Stefan Schaal


Big Data in Robotics

  • 02 January 2017

Guest edited by Jeannette Bohg, Matei Ciocarlie, Javier Civera, Lydia E. Kavraki.

... new big data methods have the potential to allow robots to understand and operate in significantly more complex environments than was possible even in the recent past. This should lead to a qualitative leap in the performance and deployability of robotics in a wide array of practical applications and real settings.

Jeannette Bohg


Finalist for the Best Interactive Session Paper

  • 17 November 2016

at the IEEE-RAS International Conference on Humanoid Robots (Humanoids 2016)

Brahayam Ponton Alexander Herzog Ludovic Righetti Stefan Schaal


Finalist for Best Paper Award

  • 28 October 2016

at the 4th RSI International Conference on Robotics and Mechatronics (ICROM).

Majid Khadiv Alexander Herzog Stefan Schaal Ludovic Righetti


Finalist for WODES 2016 Best Student Paper

  • 01 June 2016

Simon Ebner´s paper on the results of his master thesis

Topic: "Communication rate analysis for event-based state estimation"

Simon Ebner