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PD Dr. habil. Rudolph Triebel

DLR German Aerospace Center
Institute of Robotics and Mechatronics
Perception and Cognition
Oberpfaffenhofen
Muenchener Str. 20
82234 Wessling

telephone: +49 8153 28-4289
email: PD Dr. habil. Rudolph Triebel

Research Interests

Dr. 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.

 

Short CV

Dr. 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. Since 2013, Rudolph works as a lecturer at TU Munich, where he teaches master level courses in the area of Machine Learning for Computer Vision. In 2015, he was appoined as leader of the Department of Perception and Cognition at the Robotics Institute of DLR.

 

Publications

  • Wout Boerdijk, Marcus Gerhard Müller, Maximilian Durner, Martin Sundermeyer, Werner Friedl et 5 al.:
    Rock Instance Segmentation from Synthetic Images for Planetary Exploration Missions
    In: 2021 IEE/RSJ International Conference on Intelligent Robots and Systems, IROS (Workshops). Advances in Space Robotics and Back to Earth (IROS WS), 01 Oct 2021, Prague (online), 2021. [elib]
  • Lukas Meyer, Michal Smisek, Alejandro Fontan Villacampa, Laura Oliva Maza, Daniel Medina et 7 al.:
    The MADMAX data set for visual‐inertial rover navigation on Mars
    Journal of Field Robotics. Wiley, 2021. DOI 10.1002/rob.22016, ISSN 1556-4959. [elib]
  • Marco Sewtz, Xiaozhou Luo, Johannes Landgraf, Tim Bodenmüller, Rudolph Triebel:
    Robust Approaches for Localization on Multi-camera Systems in Dynamic Environments
    In: 2021 International Conference on Automation, Robotics and Applications, ICARA 2021. 2021 7th International Conference on Automation, Robotics and Applications (ICARA), 4-6 Feb. 2021, Prag, Tschechien, 2021. DOI 10.1109/ICARA51699.2021.9376475, ISBN 978-073814290-6. [elib]
  • Maria Lyssenko, Christoph Gladisch, Christian Heinzemann, Matthias Woehrle, Rudolph Triebel:
    From Evaluation to Verification: Towards Task-oriented Relevance Metricsfor Pedestrian Detection in Safety-critical Domains
    In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). Safe Artificial Intelligence for Automated Driving (SAIAD), 19.Juni 2021, virtuell, 2021. DOI 10.1109/CVPRW53098.2021.00013, ISBN 978-1-6654-4899-4, ISSN 2160-7516. [elib]
  • Mallikarjuna Vayugundla, Tim Bodenmüller, Martin J. Schuster, Marcus G. Müller, Lukas Meyer et 12 al.:
    The MMX Rover on Phobos: The Preliminary Design of the DLR Autonomous Navigation Experiment
    In: 2021 IEEE Aerospace Conference, AERO 2021. 2021 IEEE Aerospace Conference (50100), Virtual, 2021. DOI 10.1109/AERO50100.2021.9438496, ISBN 978-172817436-5, ISSN 1095-323X. [elib]
  • Manuel Stoiber, Martin Pfanne, Klaus Strobl, Rudolph Triebel, Alin Olimpiu Albu-Schäffer:
    A Sparse Gaussian Approach to Region-Based 6DoF Object Tracking
    In: 15th Asian Conference on Computer Vision, ACCV 2020, Lecture Notes in Computer Science (LNCS). 15th Asian Conference on Computer Vision, ACCV 2020, 30 Nov - 04 Dec 2020, Kyoto, Japan, 2020. [elib]
  • Felix Schiel, Annette Hagengruber, Jörn Vogel, Rudolph Triebel:
    Incremental learning of EMG-based Control commands using Gaussian Processes
    In: Conference on Robot Learning 2020. Conference on Robot Learning (CoRL) 2020, 16.-18. Nov 2020, virtual conference, 2020. [elib]
  • Matthias Humt, Jongseok Lee, Rudolph Triebel:
    Bayesian Optimization Meets Laplace Approximation for Robotic Introspection
    IROS 2020 Long-Term Autonomy Workshop, 25. Okt. - 25. Nov. 2020, Las Vegas, USA (online), 2020. [elib]
  • Riccardo Giubilato, Cedric Le Gentil, Mallikarjuna Vayugundla, Teresa Vidal-Calleja, Rudolph Triebel:
    GPGM-SLAM: Towards a Robust SLAM System for Unstructured Planetary Environments with Gaussian Process Gradient Maps
    Workshop on Planetary Exploration Robotics, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct 2020, Las Vegas (Virtual), 2020. [elib]
  • Martin J. Schuster, Marcus G. Müller, Sebastian G. Brunner, Hannah Lehner, Peter Lehner et 33 al.:
    The ARCHES Space-Analogue Demonstration Mission: Towards Heterogeneous Teams of Autonomous Robots for Collaborative Scientific Sampling in Planetary Exploration
    IEEE Robotics and Automation Letters, vol. 5 (4). IEEE - Institute of Electrical and Electronics Engineers, 2020. DOI 10.1109/LRA.2020.3007468, ISSN 2377-3766. [elib]
  • Marco Sewtz, Tim Bodenmüller, Rudolph Triebel:
    Robust MUSIC-Based Sound Source Localization in Reverberant and Echoic Environments
    In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020. IEEE/RSJ International Conference on Robots and Systems IROS, Las Vegas, USA, 2020. ISBN 978-172816212-6, ISSN 2153-0858. [elib]
  • Maximilian Denninger, Rudolph Triebel:
    3D Scene Reconstruction from a Single Viewport
    In: 16th European Conference on Computer Vision, ECCV 2020, European Conference on Computer Vision, vol. 16. European Conference on Computer Vision ECCV 2020, 23.-28. August 2020, Virtuell, 2020. DOI 10.1007/978-3-030-58542-6_4, ISBN 978-3-030-58541-9. [elib]
  • Jonathan Wenger, Hedvig Kjellström, Rudolph Triebel:
    Non-Parametric Calibration for Classification
    In: 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020. International Conference on Artificial Intelligence and Statistics (AISTATS), 26. - 28. August 2020, Virtual, 2020. [elib]
  • Jongseok Lee, Matthias Humt, Jianxiang Feng, Rudolph Triebel:
    Estimating Model Uncertainty of Neural Networks in Sparse Information Form
    In: International Conference on Machine Learning (ICML). 37th International Conference on Machine Learning (ICML), Vienna, Austria, 2020. [elib]
  • Kashmira Shinde, Jongseok Lee, Matthias Humt, Aydin Sezgin, Rudolph Triebel:
    Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry
    In: Workshop on AI for Autonomous Driving (AIAD), the 37th International Conference on Machine Learning (ICML). Workshop on AI for Autonomous Driving (AIAD), the 37 th International Conference on Machine Learning (ICML), Vienna, Austria, 2020. [elib]
  • Alejandro Fontan Villacampa, Javier Civera, Rudolph Triebel:
    Information-Driven Direct RGB-D Odometry
    In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 13-19 June 2020, Seattle, WA, USA, USA, 2020. DOI 10.1109/CVPR42600.2020.00498, ISBN 978-172817168-5, ISSN 1063-6919. [elib]
  • Anko Börner, Heinz-Wilhelm Hübers, Odej Kao, Florian Schmidt, Sören Becker et 13 al.:
    Sensor Artificial Intelligence and its Application to Space Systems – A White Paper
    2020. [elib]
  • Jongseok Lee, Ribin Radhakrishna Balachandran, Iurii Sarkisov, Marco De Stefano, Andre Coelho et 4 al.:
    Visual-Inertial Telepresence for Aerial Manipulation
    In: IEEE International Conference on Robotics and Automation ICRA. 2020 IEEE International Conference on Robotics and Automation, Paris, 2020. [elib]
  • Marco Sewtz, Tim Bodenmüller, Rudolph Triebel:
    Sound Source Localization for Robotic Application
    In: ICRA Workshop. Unconventional Sensor in Robotics, Paris, Frankreich, 2020. [elib]
  • Martin Sundermeyer, Maximilian Durner, En Yen Puang, Zoltan-Csaba Marton, Narunas Vaskevicius et 2 al.:
    Multi-Path Learning for Object Pose Estimation Across Domains
    In: IEEE Conference on Computer Vision and Pattern Recognition. IEEE Conference on Computer Vision and Pattern Recognition, Seattle, USA, 2020. [elib]
  • Riccardo Giubilato, Mallikarjuna Vayugundla, Martin Schuster, Wolfgang Stürzl, Armin Wedler et 2 al.:
    Relocalization With Submaps: Multi-Session Mapping for Planetary Rovers Equipped With Stereo Cameras
    IEEE Robotics and Automation Letters, vol. 5 (2). IEEE - Institute of Electrical and Electronics Engineers, 2020. DOI 10.1109/LRA.2020.2964157, ISSN 2377-3766. [elib]
  • Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Rudolph Triebel:
    Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection
    International Journal of Computer Vision. Springer, 2020. DOI 10.1007/s11263-019-01243-8, ISSN 0920-5691. [elib]
  • Wout Boerdijk, Martin Sundermeyer, Maximilian Durner, Rudolph Triebel:
    Self-Supervised Object-in-Gripper Segmentation from Robotic Motions
    In: Proceedings of Machine Learning Research. CoRL 2020, 16.-18. Nov. 2020, Virtual, 2020. [elib]
  • Cedric Le Gentil, Mallikarjuna Vayugundla, Riccardo Giubilato, Teresa Vidal-Calleja, Rudolph Triebel:
    Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments
    In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). International Conference on Intelligent Robots and Systems (IROS), Virtual, 2020. [elib]
  • Jiayu Liu, Ioannis Chiotellis, Rudolph Triebel, Daniel Cremers:
    Effective Version Space Reduction for Convolutional Neural Networks
    In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2020. European Conference on Machine Learning and Principles and Practive of Knowledge Discovery in Databases (ECML-PKDD), 14.-18. Sep 2020, Virtual, 2020. [elib]
  • Martin J. Schuster, Bernhard Rebele, Marcus G. Müller, Sebastian G. Brunner, Andreas Dömel et 27 al.:
    The ARCHES Moon-Analogue Demonstration Mission: Towards Teams of Autonomous Robots for Collaborative Scientific Sampling in Lunar Environments
    European Lunar Symposium (ELS), 12.-14. Mai 2020, virtuell (Padua, Italien), 2020. [elib]
  • Marco Sewtz, Tim Bodenmüller, Rudolph Triebel:
    Design of a Microphone Array for Rollin Justin
    In: ICRA Workshop. Sound Source Localization and its Application for Robots, Montreal, Canada, 2019. [elib]
  • Florian Steidle, Wolfgang Stürzl, Rudolph Triebel:
    Visual-inertial sensor fusion with a bio-inspired polarization compass for navigation of MAVs
    In: IMAV2019 Proceedings. 11th International Micro Air Vehicle Competition and Conference, 30 Sep - 04 Oct 2019, Madrid, Spain, 2019. [elib]
  • Philipp Lutz, Marcus Gerhard Müller, Moritz Maier, Samantha Stoneman, Teodor Tomic et 6 al.:
    ARDEA — An MAV with skills for future planetary missions
    Journal of Field Robotics. Wiley, 2019. DOI 10.1002/rob.21949, ISSN 1556-4959. [elib]
  • En Yen Puang, Peter Lehner, Zoltan-Csaba Marton, Maximilian Durner, Rudolph Triebel et 1 al.:
    Visual Repetition Sampling for Robot Manipulation Planning
    In: IEEE International Conference on Robotics and Automation ICRA. ICRA 2019, 20-24 May, Montreal, 2019. [elib]
  • Martin J. Schuster, Marcus G. Müller, Sebastian G. Brunner, Hannah Lehner, Peter Lehner et 11 al.:
    Towards Heterogeneous Robotic Teams for Collaborative Scientific Sampling in Lunar and Planetary Environments
    Workshop on Informed Scientific Sampling in Large-scale Outdoor Environments at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, 2019. [elib]
  • Christian Nissler, Maximilian Durner, Zoltan-Csaba Marton, Rudolph Triebel:
    Simultaneous Calibration and Mapping
    In: Experimental Robotics. 2018 International Symposium on Experimental Robotics (ISER), 5-8 Nov 2018, Buenos Aires, Argentina, 2018. [elib]
  • Maximilian Denninger, Rudolph Triebel:
    Persistent Anytime Learning of Objects from Unseen Classes
    In: IEEE International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018), 01 Oct - 05 Oct 2018, Madrid, Spain, 2018. [elib]
  • Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, Rudolph Triebel:
    Implicit 3D Orientation Learning for 6D Object Detection from RGB Images
    In: Proceedings of the European Conference on Computer Vision (ECCV) 2018. European Conference on Computer Vision, 10-13 Sep 2018, Munich, Germany, 2018. [elib]
  • Martin Sundermeyer, En Yen Puang, Zoltan-Csaba Marton, Maximilian Durner, Rudolph Triebel:
    Learning Implicit Representations of 3D Object Orientations from RGB
    ICRA 2018 Workshop on Representing a Complex World, Brisbane, Australia, 2018. [elib]
  • Manuel Brucker, Maximilian Durner, Zoltan-Csaba Marton, Rares Ambrus, Axel Wendt et 3 al.:
    Semantic Labeling of Indoor Environments from 3D RGB Maps
    In: Proceedings - IEEE International Conference on Robotics and Automation. IEEE International Conference on Robotics and Automation, Brisbane, Australien, 2018. [elib]
  • Manuel Brucker, Maximilian Durner, Zoltan-Csaba Marton, Bálint-Benczédi Ferenc, Martin Sundermeyer et 1 al.:
    6DoF Pose Estimation for Industrial Manipulation based on Synthetic Data
    International Symposium on Experimental Robotic, Argentinien, 2018. [elib]
  • Ioannis Chiotellis, Franziska Zimmermann, Daniel Cremers, Rudolph Triebel:
    Incremental Semi-Supervised Learning from Streams for Object Classification
    In: IEEE International Conference on Intelligent Robots and Systems. International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018. [elib]
  • Iris Lynne Grixa, Philipp Schulz, Wolfgang Stürzl, Rudolph Triebel:
    Appearance-based Along-route Localization for Planetary Missions
    In: IEEE International Conference on Intelligent Robots and Systems. IROS 2018, 01-05 Oct 2018, Madrid, 2018. [elib]
  • Mark Post, Romain Michalec, Alessandro Bianco, Xiu Yan, Andrea De Maio et 17 al.:
    InFuse Data Fusion Methodology for Space Robotics, Awareness and Machine Learning
    In: Proceedings of the International Astronautical Congress, IAC. 69th International Astronautical Congress, Oct 2018, Bremen, Germany, 2018. [elib]
  • Christian Nissler, Zoltan-Csaba Marton, Hannes Kisner, Ulrike Thomas, Rudolph Triebel:
    A Method for Hand-Eye and Camera-to-Camera Calibration for Limited Fields of View
    In: IEEE International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Kanada, 2017. [elib]
  • Maximilian Durner, Zoltan-Csaba Marton, Simon Kriegel, Manuel Brucker, Sebastian Riedel et 2 al.:
    Automated Benchmarks and Optimization of Perception Tasks
    IROS 2017: 2nd Workshop on Machine Learning Methods for High-Level Cognitive Capabilities in Robotics, 28 September 2017, Vancouver, Canada, 2017. [elib]
  • Mark Post, Fabrice Souvannavong, Shashank Govinderaj, Jeremi Gancet, Vincent Bissonnette et 15 al.:
    InFuse : infusing perception and data fusion into space robotics with open building blocks
    In: Informatics in Control, Automation and Robotics. 14th International Conference on Informatics in Control, Automation and Robotics, 2017-07-26 - 2017-07-28, Madrid, Spain, 2017. [elib]
  • Maximilian Durner, Simon Kriegel, Sebastian Riedel, Manuel Brucker, Zoltan Csaba Marton et 2 al.:
    Experience-based Optimization of Robotic Perception
    In: International Conference on Advanced Robotics, Proceedings, ICAR. ICAR 2017 - 18th International Conference on Advanced Robotics, 10-12 July 2017, Hong Kong, China, 2017. DOI 10.1109/ICAR.2017.8023493, ISBN 978-1-5386-3157-7. [elib]
  • Shashank Govindaraj, Jeremi Gancet, Mark Post, Raul Dominguez, Fabrice Souvannavog et 14 al.:
    INFUSE: A COMPREHENSIVE FRAMEWORK FOR DATA FUSION IN SPACE ROBOTICS
    14th symposium on Advanced Space Technologies in Robotics and Automation, 20-22 June 2017, Leiden, the Netherlands, 2017. [elib]
  • Monika Ullrich, Haider Ali, Maximilian Durner, Zoltan-Csaba Marton, Rudolph Triebel:
    Selecting CNN Features for Online Learning of 3D Objects
    In: IEEE International Conference on Intelligent Robots and Systems. IROS 2017, 24-28 Sept 2017, Vancouver, Canada, 2017. [elib]
  • Tick Son Wang, Zoltan-Csaba Marton, Manuel Brucker, Rudolph Triebel:
    How Robots Learn to Classify New Objects Trained from Small Data Sets
    1st Conference on Robot Learning, 13-15 Nov 2017, Mountain View, United States, 2017. [elib]
  • Rudolph Triebel, Hugo Grimmett, Rohan Paul, Ingmar Posner:
    Driven Learning for Driving: How Introspection Improves Semantic Mapping
    In: Robotics Research, The 16th International Symposium ISRR, Springer Tracts in Advanced Robotics, vol. 114. Springer International Publishing Switzerland. 2016. DOI 10.1007/978-3-319-28872-7_26, ISBN 978-3-3 19-28870-3. [elib]
  • Ioannis Chiotellis, Rudolph Triebel, Thomas Windheuser, Daniel Cremers:
    Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding
    In: ECCV. European Conference on Computer Vision (ECCV), Amsterdam, Netherlands, 2016. [elib]
  • Alexander Narr, Rudolph Triebel, Daniel Cremers:
    Stream-based Active Learning for Efficient and Adaptive Classification of 3D Objects
    In: IEEE International Conference on Robotics and Automation ICRA. Int. Conf. on Robotics and Automation, Stockholm, Sweden, 2016. [elib]

 

Last updated on Monday, 18 January 2021 by PD Dr. habil. Rudolph Triebel