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Daniel Honerkamp

PhD Student
Postal address:

Albert-Ludwigs-Universität Freiburg
Technische Fakultät
Robot Learning Lab
Georges-Köhler-Allee 080
D-79110 Freiburg i. Br., Germany

Office: Building 80, 01-23
Email: honerkamp@cs.uni-freiburg.de
Phone: +49 761 203-8010

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

Teaching

Seminars

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