StachnissLab

Follow Olga

Research Interests

• Visual Place Recognition
• Localization, Mapping using Publicly Available Data

Short CV

Olga Vysotska is a PhD Student for the photogrammetry at the University of Bonn since August 2014. She received her Master Degree in Applied Computer Science at the University of Freiburg, Germany in 2014. Her Master thesis was about “Automatic Channel Selection and Neural Signal Estimation across Channels of Neural Probes”, which she wrote at Autonomous Intelligent Systems group of Prof. Dr. Wolfram Burgard. Before that, in 2011 she finished her Bachelor studies in Applied Mathematics, Faculty of Cybernetics, T.Shevchenko University of Kyiv, Ukraine.

Code releases

• Online Place Recognition – a library for graph-based visual places recognition in changing environments using image sequences.
  Star Watch
• Visual Place Recognition with Relocalization – an extension for the online place recognition library that is able to deal with arbitrary shaped trajectories.
  Star Watch
• Image Sequence Matcher – the simplest implementation of graph based search algorithm for matching image sequences.
  Star Watch

Teaching

• Master Project Mobile Mapping Systems, ss 2017, ss 2016, ss 2015
• Exercises for Photogrammetry & Remote Sensing, ws 2016/17, ws 2015/16, ws 2014/15

Publications

2023

• L. Lobefaro, M. V. R. Malladi, O. Vysotska, T. Guadagnino, and C. Stachniss, “Estimating 4D Data Associations Towards Spatial-Temporal Mapping of Growing Plants for Agricultural Robots,” in Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2023.
  [BibTeX] [PDF] [Code] [Video]

  @inproceedings{lobefaro2023iros,
  author = {L. Lobefaro and M.V.R. Malladi and O. Vysotska and T. Guadagnino and C. Stachniss},
  title = {{Estimating 4D Data Associations Towards Spatial-Temporal Mapping of Growing Plants for Agricultural Robots}},
  booktitle = iros,
  year = 2023,
  codeurl = {https://github.com/PRBonn/plants_temporal_matcher},
  videourl = {https://youtu.be/HpJPIzmXoag}
  }

2021

• N. Chebrolu, T. Läbe, O. Vysotska, J. Behley, and C. Stachniss, “Adaptive Robust Kernels for Non-Linear Least Squares Problems,” IEEE Robotics and Automation Letters (RA-L), vol. 6, pp. 2240-2247, 2021. doi:10.1109/LRA.2021.3061331
  [BibTeX] [PDF] [Video]

  @article{chebrolu2021ral,
  author = {N. Chebrolu and T. L\"{a}be and O. Vysotska and J. Behley and C. Stachniss},
  title = {{Adaptive Robust Kernels for Non-Linear Least Squares Problems}},
  journal = ral,
  volume = 6,
  issue = 2,
  pages = {2240-2247},
  doi = {10.1109/LRA.2021.3061331},
  year = 2021,
  videourl = {https://youtu.be/34Zp3ZX0Bnk}
  }

2020

• X. Chen, T. Läbe, A. Milioto, T. Röhling, O. Vysotska, A. Haag, J. Behley, and C. Stachniss, “OverlapNet: Loop Closing for LiDAR-based SLAM,” in Proc. of Robotics: Science and Systems (RSS), 2020.
  [BibTeX] [PDF] [Code] [Video]

  @inproceedings{chen2020rss,
  author = {X. Chen and T. L\"abe and A. Milioto and T. R\"ohling and O. Vysotska and A. Haag and J. Behley and C. Stachniss},
  title = {{OverlapNet: Loop Closing for LiDAR-based SLAM}},
  booktitle = rss,
  year = {2020},
  codeurl = {https://github.com/PRBonn/OverlapNet/},
  videourl = {https://youtu.be/YTfliBco6aw},
  }

• N. Chebrolu, T. Laebe, O. Vysotska, J. Behley, and C. Stachniss, “Adaptive Robust Kernels for Non-Linear Least Squares Problems,” arXiv Preprint, 2020.
  [BibTeX] [PDF]

  @article{chebrolu2020arxiv,
  title={Adaptive Robust Kernels for Non-Linear Least Squares Problems},
  author={N. Chebrolu and T. Laebe and O. Vysotska and J. Behley and C. Stachniss},
  journal = arxiv,
  year=2020,
  eprint={2004.14938},
  keywords={cs.RO},
  url={https://arxiv.org/pdf/2004.14938v2}
  }

2019

• O. Vysotska, “Visual Place Recognition in Changing Environments,” PhD Thesis, 2019.
  [BibTeX] [PDF]

  @PhdThesis{vysotska2019phd,
  author = {O. Vysotska},
  title = {Visual Place Recognition in Changing Environments},
  year = 2019,
  school =  {University of Bonn},
  URL = {https://hss.ulb.uni-bonn.de/2019/5593/5593.pdf},
  }

• O. Vysotska and C. Stachniss, “Effective Visual Place Recognition Using Multi-Sequence Maps,” IEEE Robotics and Automation Letters (RA-L), vol. 4, pp. 1730-1736, 2019.
  [BibTeX] [PDF] [Video]

  @article{vysotska2019ral,
  author = {O. Vysotska and C. Stachniss},
  title = {{Effective Visual Place Recognition Using Multi-Sequence Maps}},
  journal = ral,
  year = 2019,
  volume = 4,
  issue = 2,
  pages = {1730-1736},
  url = {https://www.ipb.uni-bonn.de/pdfs/vysotska2019ral.pdf},
  videourl = {https://youtu.be/wFU0JoXTH3c},
  }

• F. Yan, O. Vysotska, and C. Stachniss, ” Global Localization on OpenStreetMap Using 4-bit Semantic Descriptors,” in Proc. of the European Conf. on Mobile Robots (ECMR), 2019.
  [BibTeX] [PDF]

  @InProceedings{yan2019ecmr,
  author = {F. Yan and O. Vysotska and C. Stachniss},
  title = {{ Global Localization on OpenStreetMap Using 4-bit Semantic Descriptors}},
  booktitle = ecmr,
  year = {2019},
  }

• O. Vysotska, H. Kuhlmann, and C. Stachniss, “UAVs Towards Sustainable Crop Production,” in Workshop at Robotics: Science and Systems, 2019.
  [BibTeX] [PDF]

  @InProceedings{vysotska2019rsswsabstract,
  author = {O. Vysotska and H. Kuhlmann and C. Stachniss},
  title = {{UAVs Towards Sustainable Crop Production}},
  booktitle = {Workshop at Robotics: Science and Systems},
  year = {2019},
  note = {Abstract},
  }

2017

• O. Vysotska and C. Stachniss, “Improving SLAM by Exploiting Building Information from Publicly Available Maps and Localization Priors,” Journal of Photogrammetry, Remote Sensing and Geoinformation Science (PFG), vol. 85, iss. 1, pp. 53-65, 2017.
  [BibTeX] [PDF] [Video]

  @Article{vysotska2017pfg,
  title = {Improving SLAM by Exploiting Building Information from Publicly Available Maps and Localization Priors},
  author = {Vysotska, O. and Stachniss, C.},
  journal = pfg,
  year = {2017},
  number = {1},
  pages = {53-65},
  volume = {85},
  url = {https://www.ipb.uni-bonn.de/pdfs/vysotska2016pfg.pdf},
  videourl = {https://www.youtube.com/watch?v=dKHlF3OkEV4},
  }

• O. Vysotska and C. Stachniss, “Relocalization under Substantial Appearance Changes using Hashing,” in IROS Workshop on Planning, Perception and Navigation for Intelligent Vehicles, 2017.
  [BibTeX] [PDF] [Code]
  

  [none]

  @InProceedings{vysotska2017irosws,
  title = {Relocalization under Substantial Appearance Changes using Hashing},
  author = {O. Vysotska and C. Stachniss},
  booktitle = {IROS Workshop on Planning, Perception and Navigation for Intelligent Vehicles},
  year = {2017},
  abstract = {[none]},
  url = {https://www.ipb.uni-bonn.de/pdfs/vysotska2017irosws.pdf},
  codeurl = {https://github.com/Photogrammetry-Robotics-Bonn/vpr_relocalization},
  }

2016

• O. Vysotska and C. Stachniss, “Exploiting Building Information from Publicly Available Maps in Graph-Based SLAM,” in Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2016.
  [BibTeX] [PDF] [Video]
  

  [none]

  @InProceedings{vysotska16iros,
  title = {Exploiting Building Information from Publicly Available Maps in Graph-Based SLAM},
  author = {O. Vysotska and C. Stachniss},
  booktitle = iros,
  year = {2016},
  abstract = {[none]},
  url = {https://www.ipb.uni-bonn.de/pdfs/vysotska16iros.pdf},
  videourl = {https://www.youtube.com/watch?v=5RfRAEP-baM},
  }

• O. Vysotska and C. Stachniss, “Lazy Data Association For Image Sequences Matching Under Substantial Appearance Changes,” IEEE Robotics and Automation Letters (RA-L), vol. 1, iss. 1, pp. 213-220, 2016. doi:10.1109/LRA.2015.2512936
  [BibTeX] [PDF] [Code] [Video]
  

  Localization is an essential capability for mobile robots and the ability to localize in changing environments is key to robust outdoor navigation. Robots operating over extended periods of time should be able to handle substantial appearance changes such as those occurring over seasons or under different weather conditions. In this letter, we investigate the problem of efficiently coping with seasonal appearance changes in online localization. We propose a lazy data association approach for matching streams of incoming images to a reference image sequence in an online fashion. We present a search heuristic to quickly find matches between the current image sequence and a database using a data association graph. Our experiments conducted under substantial seasonal changes suggest that our approach can efficiently match image sequences while requiring a comparably small number of image to image comparisons

  @Article{vysotska16ral,
  title = {Lazy Data Association For Image Sequences Matching Under Substantial Appearance Changes},
  author = {O. Vysotska and C. Stachniss},
  journal = ral,
  year = {2016},
  number = {1},
  pages = {213-220},
  volume = {1},
  abstract = {Localization is an essential capability for mobile robots and the ability to localize in changing environments is key to robust outdoor navigation. Robots operating over extended periods of time should be able to handle substantial appearance changes such as those occurring over seasons or under different weather conditions. In this letter, we investigate the problem of efficiently coping with seasonal appearance changes in online localization. We propose a lazy data association approach for matching streams of incoming images to a reference image sequence in an online fashion. We present a search heuristic to quickly find matches between the current image sequence and a database using a data association graph. Our experiments conducted under substantial seasonal changes suggest that our approach can efficiently match image sequences while requiring a comparably small number of image to image comparisons},
  doi = {10.1109/LRA.2015.2512936},
  timestamp = {2016.04.18},
  url = {https://www.ipb.uni-bonn.de/pdfs/vysotska16ral-icra.pdf},
  codeurl = {https://github.com/Photogrammetry-Robotics-Bonn/online_place_recognition},
  videourl = {https://www.youtube.com/watch?v=l-hNk7Z4lSk},
  }

2015

• O. Vysotska, T. Naseer, L. Spinello, W. Burgard, and C. Stachniss, “Efficient and Effective Matching of Image Sequences Under Substantial Appearance Changes Exploiting GPS Prior,” in Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA), 2015, pp. 2774-2779. doi:10.1109/ICRA.2015.7139576
  [BibTeX] [PDF] [Code]

  @InProceedings{vysotska15icra,
  title = {Efficient and Effective Matching of Image Sequences Under Substantial Appearance Changes Exploiting GPS Prior},
  author = {O. Vysotska and T. Naseer and L. Spinello and W. Burgard and C. Stachniss},
  booktitle = icra,
  year = {2015},
  pages = {2774-2779},
  doi = {10.1109/ICRA.2015.7139576},
  timestamp = {2015.06.29},
  url = {https://www.ipb.uni-bonn.de/pdfs/vysotska15icra.pdf},
  codeurl = {https://github.com/ovysotska/image_sequence_matcher},
  }

• O. Vysotska and C. Stachniss, “Lazy Sequences Matching Under Substantial Appearance Changes,” in Workshop on Visual Place Recognition in Changing Environments at the IEEE Proc. of the IEEE Intl. Conf. on Robotics & Automation (ICRA), 2015.
  [BibTeX] [PDF]
  

  [none]

  @InProceedings{vysotska15icraws,
  title = {Lazy Sequences Matching Under Substantial Appearance Changes},
  author = {O. Vysotska and C. Stachniss},
  booktitle = {Workshop on Visual Place Recognition in Changing Environments at the IEEE } # icra,
  year = {2015},
  abstract = {[none]},
  timestamp = {2015.06.29},
  url = {https://www.ipb.uni-bonn.de/pdfs/vysotska15icra-ws.pdf},
  }

2014

• O. Vysotska, B. Frank, I. Ulbert, O. Paul, P. Ruther, C. Stachniss, and W. Burgard, “Automatic Channel Selection and Neural Signal Estimation across Channels of Neural Probes,” in Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), Chicago, USA, 2014.
  [BibTeX] [PDF]

  @InProceedings{vysotska2014iros,
  title = {Automatic Channel Selection and Neural Signal Estimation across Channels of Neural Probes},
  author = {O. Vysotska and B. Frank and I. Ulbert and O. Paul and P. Ruther and C. Stachniss and W. Burgard},
  booktitle = iros,
  year = {2014},
  address = {Chicago, USA},
  }

2013

• I. Bogoslavskyi, O. Vysotska, J. Serafin, G. Grisetti, and C. Stachniss, “Efficient Traversability Analysis for Mobile Robots using the Kinect Sensor,” in Proc. of the European Conf. on Mobile Robots (ECMR), Barcelona, Spain, 2013.
  [BibTeX] [PDF]
  

  [none]

  @InProceedings{bogoslavskyi2013,
  title = {Efficient Traversability Analysis for Mobile Robots using the Kinect Sensor},
  author = {I. Bogoslavskyi and O. Vysotska and J. Serafin and G. Grisetti and C. Stachniss},
  booktitle = ecmr,
  year = {2013},
  address = {Barcelona, Spain},
  abstract = {[none]},
  timestamp = {2014.04.24},
  url = {https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/bogoslavskyi13ecmr.pdf},
  }