Direkt zum Inhalt springen
Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich

Menu

Links

Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:
CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

More


Dr. Vladyslav Usenko

AlumniTechnical University of Munich

Department of Informatics
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office: 
Mail: vlad.usenko@tum.de

Find me on Google Scholar, Gitlab, Github, Linkedin.

Research Interests

Visual-Inertial Odometry

We've created the Visual-Inertial Dataset, a novel dataset with a diverse set of sequences in different scenes for evaluating Visual-Inertial odometry.

This video shows "Visual-Inertial Mapping with Non-Linear Factor Recovery".



This video shows "Direct Visual-Inertial Odometry with Stereo Cameras" presented at ICRA 2016



This video shows "Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization" presented at ICRA 2018, based on the Master's thesis of Lukas von Stumberg that I supervised.

Visual Navigation for MAVs

  • EuRoC Competition
  • 2018-02-28: Our team TUM Flyers has presented the final Field-Test demonstration of the EuRoC Project.

  • 2017-05-11: Our team TUM Flyers has been ranked 1st in Stage 2 and admitted to Stage 3 of the EuRoC Challenge 3. See this link for details.
  • 2015-05-13: Our team TUM Flyers has been admitted to Stage 2 of the EuRoC Challenge 3 with the top scoring proposal! See this link for details.
  • 2014-12-01: Our team TUM Flyers has won Stage 1 of the EuRoC Challenge 3 on Servicing and Inspection with MAVs in Industrial Use-Cases. See this link for details.
  • Real-Time Trajectory Replanning for MAVs using Uniform B-splines and 3D Circular Buffer

More information about the project is here.

  • Other Projects

This video shows an Autonomous Exploration with a Low-Cost Quadrocopter using Semi-Dense Monocular SLAM. This is Bachelor's Thesis of Lukas von Stumberg, which I co-supervised:



Publications


Export as PDF, XML, TEX or BIB

Book Chapters
2020
[]TUM Flyers: Vision—Based MAV Navigation for Systematic Inspection of Structures (V. Usenko, L. von Stumberg, J. Stückler and D. Cremers), Chapter in Bringing Innovative Robotic Technologies from Research Labs to Industrial End-users (F. Caccavale, C. Ott, B. Winkler, Z. Taylor, eds.), Springer International Publishing, 2020.  [bibtex] [doi]
2019
[]A Review and Quantitative Evaluation of Direct Visual–Inertial Odometry (L. von Stumberg, V. Usenko and D. Cremers), Chapter in Multimodal Scene Understanding (M. Yang, B. Rosenhahn, V. Murino, eds.), Academic Press, 2019.  [bibtex] [doi]
Journal Articles
2020
[]Visual-Inertial Mapping with Non-Linear Factor Recovery (V. Usenko, N. Demmel, D. Schubert, J. Stueckler and D. Cremers), In IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robotics and Automation (ICRA), IEEE, volume 5, 2020. ([arxiv]) [bibtex] [doi] [pdf]
2018
[]Omnidirectional DSO: Direct Sparse Odometry with Fisheye Cameras (H. Matsuki, L. von Stumberg, V. Usenko, J. Stueckler and D. Cremers), In IEEE Robotics and Automation Letters & Int. Conference on Intelligent Robots and Systems (IROS), IEEE, 2018. ([arxiv]) [bibtex] [pdf]
2015
[]Cloud-based collaborative 3D mapping in real-time with low-cost robots (G. Mohanarajah, V. Usenko, M. Singh, R. D'Andrea and M. Waibel), In IEEE Transactions on Automation Science and Engineering, IEEE, volume 12, 2015.  [bibtex] [pdf]
Conference and Workshop Papers
2020
[]Efficient Derivative Computation for Cumulative B-Splines on Lie Groups (C. Sommer, V. Usenko, D. Schubert, N. Demmel and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.  [bibtex] [doi] [arXiv:1911.08860] [pdf]Oral Presentation
2019
[]Rolling-Shutter Modelling for Visual-Inertial Odometry (D. Schubert, N. Demmel, L. von Stumberg, V. Usenko and D. Cremers), In International Conference on Intelligent Robots and Systems (IROS), 2019. ([arxiv]) [bibtex] [pdf]
2018
[]The Double Sphere Camera Model (V. Usenko, N. Demmel and D. Cremers), In Proc. of the Int. Conference on 3D Vision (3DV), 2018. ([arxiv]) [bibtex] [arXiv:1807.08957] [pdf]
[]Direct Sparse Odometry With Rolling Shutter (D. Schubert, N. Demmel, V. Usenko, J. Stueckler and D. Cremers), In European Conference on Computer Vision (ECCV), 2018. ([supplementary][arxiv]) [bibtex] [pdf]Oral Presentation
[]The TUM VI Benchmark for Evaluating Visual-Inertial Odometry (D. Schubert, T. Goll, N. Demmel, V. Usenko, J. Stueckler and D. Cremers), In International Conference on Intelligent Robots and Systems (IROS), 2018. ([arxiv]) [bibtex] [pdf]
[]Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization (L. von Stumberg, V. Usenko and D. Cremers), In International Conference on Robotics and Automation (ICRA), 2018. ([supplementary][video][arxiv]) [bibtex] [pdf]
2017
[]Real-Time Trajectory Replanning for MAVs using Uniform B-splines and a 3D Circular Buffer (V. Usenko, L. von Stumberg, A. Pangercic and D. Cremers), In International Conference on Intelligent Robots and Systems (IROS), 2017. ([arxiv]) [bibtex] [pdf]Best Paper Award - Finalist (link)
[]From Monocular SLAM to Autonomous Drone Exploration (L. von Stumberg, V. Usenko, J. Engel, J. Stueckler and D. Cremers), In European Conference on Mobile Robots (ECMR), 2017.  [bibtex] [pdf]
2016
[]A Photometrically Calibrated Benchmark For Monocular Visual Odometry (J. Engel, V. Usenko and D. Cremers), In arXiv:1607.02555, 2016.  [bibtex] [pdf]
[]Direct Visual-Inertial Odometry with Stereo Cameras (V. Usenko, J. Engel, J. Stueckler and D. Cremers), In International Conference on Robotics and Automation (ICRA), 2016.  [bibtex] [pdf] [video]
2015
[]Reconstructing Street-Scenes in Real-Time From a Driving Car (V. Usenko, J. Engel, J. Stueckler and D. Cremers), In Proc. of the Int. Conference on 3D Vision (3DV), 2015.  [bibtex] [pdf]
2012
[]Furniture Classification using WWW CAD Models (V. Usenko, F. Seidel, Z. Marton, D. Pangercic and M. Beetz), In IROS'12 Workshop on Active Semantic Perception, 2012.  [bibtex] [pdf]
PhD Thesis
2019
[]Visual-Inertial Navigation for Autonomous Vehicles (V Usenko), PhD thesis, Technische Universität München, 2019. (library link) [bibtex] [pdf]
Powered by bibtexbrowser
Export as PDF, XML, TEX or BIB

Teaching

Winter Semester 2018/2019:

Summer Semester 2018:

Winter Semester 2017/2018:

Winter Semester 2016/2017:

Winter Semester 2015/2016:



Summer Semester 2015:



Summer Semester 2014:

Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:
CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

More