Daniel Honerkamp
PhD Student | ||
Postal address: |
Albert-Ludwigs-Universität Freiburg |
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Office: | Building 80, 01-23 | |
Email: |
honerkamp@cs.uni-freiburg.de |
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Phone: |
+49 761 203-8010 |
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About me
I am a PhD student in the Robot Learning Lab at the University of Freiburg in Germany.
My research aims to address the challenges in applying reinforcement learning to real world systems. This includes work around learning skills, representation learning, sample efficiency and self-supervision. I am also very interested in multi-disciplinary connections, such as with mechanism design and multi-agent systems.
Background
- 05/2020 - current: Ph.D. Student in the Robot Learning Lab, University of Freiburg
- 10/2018 - 04/2020: Machine Learning Engineer at Fetch.ai, Cambridge UK
- 10/2017 - 09/2018: M.Sc. Computational Statistics and Machine Learning, University College London
- 10/2013 - 07/2016: B.A. Economics, University of Zurich
Research Interests
- Reinforcement Learning
- Embodied AI
- Mobile Manipulation
Current Research Projects
Publications
-
Fabian Schmalstieg*,
Daniel Honerkamp*,
Tim Welschehold,
Abhinav Valada,
Learning Hierarchical Interactive Multi-Object Search for Mobile Manipulation
IEEE Robotics and Automation Letters (RA-L), 2023.
Download, Publisher page, Website BibTeX -
Daniel Honerkamp,
Tim Welschehold,
Abhinav Valada,
N2M2:Learning Navigation for Arbitrary Mobile Manipulation Motions in Unseen and Dynamic Environments
IEEE Transactions on Robotics (T-RO), 2023.
>> Best Paper Award, IROS 2022 Workshop on Mobile Manipulation and Embodied Intelligence.
Download, Publisher page, Video Demo BibTeX -
Daniel Honerkamp,
Suresh Guttikonda,
Abhinav Valada,
Active Particle Filter Networks: Efficient Active Localization in Continuous Action Spaces and Large Maps
IROS 2022 Workshop Probabilistic Robotics in the Age of Deep Learning, 2022.
Download Video Demo BibTeX -
Abdelrahman Younes*,
Daniel Honerkamp*,
Tim Welschehold,
Abhinav Valada,
SoundSpaces Challenge 2022 - 2nd Place
Conference on Computer Vision and Pattern Recognition (CVPR) Embodied AI Workshop, 2022.
Video Challenge -
Fabian Schmalstieg*,
Daniel Honerkamp*,
Tim Welschehold,
Abhinav Valada,
Learning Long-Horizon Robot Exploration Strategies for Multi-Object Search in Continuous Action Spaces
Proceedings of the International Symposium on Robotics Research (ISRR).
Download Demo BibTeX -
Abdelrahman Younes*,
Daniel Honerkamp*,
Tim Welschehold,
Abhinav Valada,
Catch Me If You Hear Me: Audio-Visual Navigation in Complex Unmapped Environments with Moving Sounds
IEEE Robotics and Automation Letters (RA-L), 2022.
Download BibTeX -
Abdelrahman Younes*,
Daniel Honerkamp*,
Tim Welschehold,
Abhinav Valada,
SoundSpaces Challenge 2021 - 1st Place
Conference on Computer Vision and Pattern Recognition (CVPR) Embodied AI Workshop, 2021.
Video Challenge -
Daniel Honerkamp,
Tim Welschehold,
Abhinav Valada,
Learning Kinematic Feasibility for Mobile Manipulation through Deep Reinforcement Learning
IEEE Robotics and Automation Letters (RA-L), 2021.
Download Video Demo BibTeX -
Marcin Abram,
Daniel Honerkamp
Jonathan Ward,
Jin-Mann Wong
Democratising blockchain: A minimal agency consensus model
International Conference on Blockchain Economics, Security and Protocols (Tokenomics), Paris, 2019.
Download BibTeX
Presentations
- Learning for Mobile Manipulation, 2022 IROS Tutorial: Open and Trustworthy Deep Learning for Robotics”
- Learning for Mobile Manipulation, 2022 Summer School “Continuous Engineering and Deep Learning for Trustworthy Autonomous Systems”
- Learning Kinematic Feasibility for Mobile Manipulation, 2022 MoveIt Community Meeting
Teaching
Seminars
- Co-organizer, Learning with Limited Supervision, University of Freiburg, SS 2021/22
- Co-organizer, Deep Learning for Autonomous Systems Seminar, University of Freiburg, WS 2020/21
- Co-organizer, Deep Learning Lab, University of Freiburg, SS 2020
- Co-organizer, Self-Supervised Learning Seminar, University of Freiburg, SS 2020
- Co-organizer, Autonomy for manipulation reading group, University of Freiburg
Current Students
- Active camera control and noisy perception for indoor exploration, S. Prassanna, Master Project
- Co-Design of Mobile Manipulation Platforms, R. Schneider, Master Project
- Scene Graph Affordances, R. Verma, Master Project
Past Students
- Hierarchical interactive multi-object-search, 2023, F. Schmalstieg, Master Thesis (together with Tim Welschehold)
- Representation learning and sensor fusion for arm collision avoidance in mobile manipulation via reinforcement learning, 2023, A. Khalid Master Thesis (together with Tim Welschehold)
- Model-Free RL for Robot Manipulation: Avoiding Configuration Jumps and Overestimation, 2022, A. Khalid, Master Project (together with Tim Welschehold)
- Reinforcement Learning for Indoor Multi-Object Exploration, 2022, F. Schmalstieg, Master Project (together with Tim Welschehold)
- Dynamical Audio-Visual Navigation: Catching Unheard Moving Sound Sources in Unmapped 3D Environments, 2021, Abdelrahman Younes, Master Thesis (together with Tim Welschehold)
- Deep active localization in continuous action spaces and realistic scenes, 2021, Suresh Guttikonda, Master Project