DLR German Aerospace Center
Institute of Robotics and Mechatronics
Prof. Triebel's main research area are machine learning algorithms applied to robot perception tasks. These mainly include object segmentation and classification, semantic mapping, navigation, and 3D environment modelling. In particular, he focusses on persistent and autonomous learning techniques, which will make learning more useful for concrete applications in robotics by providing more independence on a human supervisor and by featuring a high level of adaptivity and the ability to efficiently update the learned models online. Furthermore, Dr. Triebel investigates algorithms for robot perception that provide reliable confidence estimates and an awareness of the internal state of the system ("introspection"). This leads to more explainable and ultimately safer autononous robot systems.
Prof. Triebel received his PhD in 2007 from the University of Freiburg in Germany. The title of his PhD thesis is “Three-dimensional Perception for Mobile Robots”. From 2007 to 2011, he was a postdoctoral researcher at ETH Zurich, where he worked on machine learning algorithms for robot perception within several EU-funded projects. Then, from 2011 to 2013 he worked in the Mobile Robotics Group at the University of Oxford, where he developed unsupervised and online learning techniques for detection and classification applications in mobile robotics and autonomous driving. From 2013 to 2023, Rudolph worked as a lecturer at TU Munich, where he teached master level courses in the area of Machine Learning for Computer Vision. In 2015, he was appointed as leader of the Department of Perception and Cognition at the Robotics Institute of DLR, and in 2023 he was appointed as a university professor at Karlsruhe Institute of Technology (KIT) in "Intelligent Robot Perception".