Julius Rückin

PhD Student
Contact:
Email: jrueckin@nulluni-bonn.de
Tel: +49 – 228 – 73 – 29 04
Fax: +49 – 228 – 73 – 27 12
Office: Nussallee 15, 1. OG, room 1.001
Address:
University of Bonn
Photogrammetry, IGG
Nussallee 15
53115 Bonn

Google Scholar | LinkedIn

Research Interests

  • Integrated Planning and Learning
  • Reinforcement Learning
  • Active Learning
  • Agricultural Robotics

Short CV

Julius Rückin is a doctoral student in Robotics at the University of Bonn and Cluster of Excellence “PhenoRob” since February 2021. Before starting in Bonn, he did his Master in Mathematics in Data Science at the Technical University of Munich, Germany (Oct 2018 – Dec 2020). In the 2019 season, he led a team of computer science and engineering students building an autonomous race car that competed in international Formula Student competitions. During his Master’s, he worked for Merantix Momentum (Berlin, Germany), a machine-learning solutions provider, as a Machine Intelligence Engineer developing machine-learning software for mid-sized enterprises and large corporations.

Projects

  • PhenoRob – Robotics and Phenotyping for Sustainable Crop Production (DFG Cluster of Excellence)

Teaching

  • 2021 – Decision-Making for Autonomous Robots

Publications

2024

  • A. Vashisth, J. Rückin, F. Magistri, C. Stachniss, and M. Popović, “Deep Reinforcement Learning with Dynamic Graphs for Adaptive Informative Path Planning,” IEEE Robotics and Automation Letters (RA-L), vol. 9, iss. 9, pp. 7747-7754, 2024. doi:10.1109/LRA.2024.3421188
    [BibTeX] [PDF] [Code] 
    @article{vashisth2024ral,
author = {A. Vashisth and J. R\"uckin and F. Magistri and C.
Stachniss and M. Popovi\'c},
title = {{Deep Reinforcement Learning with Dynamic Graphs for Adaptive
Informative Path Planning}},
journal = ral,
volume = {9},
number = {9},
pages = {7747-7754},
year = 2024,
doi = {10.1109/LRA.2024.3421188},
codeurl = {https://github.com/dmar-bonn/ipp-rl-3d},
}
  • M. Popović, J. Ott, J. Rückin, and M. J. Kochenderfer, “Learning-based methods for adaptive informative path planning,” Robotics and autonomous systems, vol. 179, p. 104727, 2024.
    [BibTeX] [PDF] [Code] 
    @article{popovic2024jras,
title = {{Learning-based methods for adaptive informative path planning}},
author = {Popovi{\'c}, Marija and Ott, Joshua and R{\"u}ckin, Julius and Kochenderfer, Mykel J},
journal = jras,
volume = {179},
pages = {104727},
year = {2024},
codeurl = {https://dmar-bonn.github.io/aipp-survey},
}
  • J. Rückin, F. Magistri, C. Stachniss, and M. Popović, “Semi-Supervised Active Learning for Semantic Segmentation in Unknown Environments Using Informative Path Planning,” IEEE Robotics and Automation Letters (RA-L), vol. 9, iss. 3, pp. 2662-2669, 2024. doi:10.1109/LRA.2024.3359970
    [BibTeX] [PDF] [Code] 
    @article{rueckin2024ral,
author = {J. R\"uckin and F. Magistri and C. Stachniss and M. Popovi\'c},
title = {{Semi-Supervised Active Learning for Semantic Segmentation in Unknown Environments Using Informative Path Planning}},
journal = ral,
year = {2024},
volume = {9},
number = {3},
pages = {2662-2669},
issn = {2377-3766},
doi = {10.1109/LRA.2024.3359970},
codeurl = {https://github.com/dmar-bonn/ipp-ssl},
}

2023

  • J. Rückin, F. Magistri, C. Stachniss, and M. Popovic, “An Informative Path Planning Framework for Active Learning in UAV-based Semantic Mapping,” Ieee transactions on robotics (tro), vol. 39, iss. 6, pp. 4279-4296, 2023. doi:10.1109/TRO.2023.3313811
    [BibTeX] [PDF] [Code] 
    @article{rueckin2023tro,
author = {J. R\"{u}ckin and F. Magistri and C. Stachniss and M. Popovic},
title = {{An Informative Path Planning Framework for Active Learning in UAV-based Semantic Mapping}},
journal = tro,
year = {2023},
codeurl = {https://github.com/dmar-bonn/ipp-al-framework},
doi={10.1109/TRO.2023.3313811},
volume={39},
number={6},
pages={4279-4296},
}
  • L. Jin, X. Chen, J. Rückin, and M. Popović, “NeU-NBV: Next Best View Planning Using Uncertainty Estimation in Image-Based Neural Rendering,” in Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2023.
    [BibTeX] [PDF] [Code] 
    @inproceedings{jin2023iros,
title = {{NeU-NBV: Next Best View Planning Using Uncertainty Estimation in Image-Based Neural Rendering}},
booktitle = iros,
author = {Jin, Liren and Chen, Xieyuanli and Rückin, Julius and Popović, Marija},
year = {2023},
codeurl = {https://github.com/dmar-bonn/neu-nbv},
}
  • J. Westheider, J. Rückin, and M. Popović, “Multi-UAV Adaptive Path Planning Using Deep Reinforcement Learning,” in Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2023.
    [BibTeX] [PDF] [Code] 
    @inproceedings{westheider2023iros,
title = {{Multi-UAV Adaptive Path Planning Using Deep Reinforcement Learning}},
author = {Westheider, Jonas and R{\"u}ckin, Julius and Popovi{\'c}, Marija},
booktitle = iros,
year = {2023},
codeurl = {https://github.com/dmar-bonn/ipp-marl},
}
  • T. Zaenker, J. Rückin, R. Menon, M. Popović, and M. Bennewitz, “Graph-based view motion planning for fruit detection,” in Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2023.
    [BibTeX] [PDF] 
    @inproceedings{zaenker2023iros,
title = {{Graph-based view motion planning for fruit detection}},
author = {Zaenker, Tobias and R{\"u}ckin, Julius and Menon, Rohit and Popovi{\'c}, Marija and Bennewitz, Maren},
booktitle = iros,
year = {2023},
}

2022

  • J. Rückin, L. Jin, F. Magistri, C. Stachniss, and M. Popović, “Informative Path Planning for Active Learning in Aerial Semantic Mapping,” in Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2022.
    [BibTeX] [PDF] [Code] 
    @InProceedings{rueckin2022iros,
author = {J. R{\"u}ckin and L. Jin and F. Magistri and C. Stachniss and M. Popovi\'c},
title = {{Informative Path Planning for Active Learning in Aerial Semantic Mapping}},
booktitle = iros,
year = {2022},
codeurl = {https://github.com/dmar-bonn/ipp-al},
}
  • J. Rückin, L. Jin, and M. Popović, “Adaptive Informative Path Planning Using Deep Reinforcement Learning for UAV-based Active Sensing,” in Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA), 2022.
    [BibTeX] [PDF] [Code] 
    @inproceedings{rueckin2022icra,
author = {R{\"u}ckin, Julius and Jin, Liren and Popović, Marija},
booktitle = icra,
title = {{Adaptive Informative Path Planning Using Deep Reinforcement Learning for UAV-based Active Sensing}},
year = {2022},
codeurl = {https://github.com/dmar-bonn/ipp-rl},
}
  • L. Jin, J. Rückin, S. H. Kiss, T. Vidal-Calleja, and M. Popović, “Adaptive-resolution field mapping using Gaussian process fusion with integral kernels,” IEEE Robotics and Automation Letters (RA-L), vol. 7, iss. 3, p. 7471–7478, 2022.
    [BibTeX] [PDF] [Code] 
    @article{jin2022ral,
title={{Adaptive-resolution field mapping using Gaussian process fusion with integral kernels}},
author={Jin, Liren and R{\"u}ckin, Julius and Kiss, Stefan H and Vidal-Calleja, Teresa and Popovi{\'c}, Marija},
journal=ral,
volume={7},
number={3},
pages={7471--7478},
year={2022},
codeurl = {https://github.com/dmar-bonn/argpf_mapping},
}