Vladimír Kubelka

Vladimír Kubelka

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vladimir.kubelka.1@ulaval.ca

Expertise: Search and rescue, localization, sensor fusion, field deployments

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Vladimír has received his master’s degree in Cybernetics and Robotics from the Czech Technical University in Prague (2013). The experiments for the master’s thesis were performed at the ASL lab (ETH Zurich) during his visiting student internship. After that, he continued as a Ph.D. student at CTU and focused on the problem of data fusion and state estimation for ground robots in harsh conditions. He had the opportunity to participate in two EU-funded search and rescue projects NIFTi and TRADR. These projects offered real-world scenarios to test the localization algorithms. The main challenge were sensor outages (because of dark areas, smoke), unstable terrain and semi-structured environments (e.g., earthquake aftermath). He defended his Ph.D. thesis in 2018 (supervised by Michal Reinstein and Tomáš Svoboda) and enrolled as a postdoc fellow with the NORLAB. The Canadian winter brings new challenges for the ground mobile robots: deep snow, adversary conditions for optical sensors and changing terrain caused by wind and blizzards.

His research topics are sensor fusion and state estimation for mobile ground robots. He is interested in the problems related to deployment of robots in harsh environments.

Education

Publications

Journal Articles

  1. Rouček, T., Pecka, M., Čížek, P., Petříček, T., Bayer, J., Šalanský, V., Azayev, T., Heřt, D., Petrlík, M., Báča, T., Spurný, V., Krátký, V., Petráček, P., Baril, D., Vaidis, M., Kubelka, V., Pomerleau, F., Faigl, J., Zimmermann, K., … Krajník, T. (2022). System for multi-robotic exploration of underground environments CTU-CRAS-NORLAB in the DARPA Subterranean Challenge. Field Robotics, 2(1), 1779–1818. https://doi.org/10.55417/fr.2022055
     Publisher    Bibtex source
  2. Baril, D., Deschênes, S.-P., Gamache, O., Vaidis, M., LaRocque, D., Laconte, J., Kubelka, V., Giguère, P., & Pomerleau, F. (2022). Kilometer-scale autonomous navigation in subarctic forests: challenges and lessons learned. Field Robotics, 2(1), 1628–1660. https://doi.org/10.55417/fr.2022050
     PDF    Publisher    Bibtex source
  3. Kubelka, V., Dandurand, P., Babin, P., Giguère, P., & Pomerleau, F. (2020). Radio propagation models for differential GNSS based on dense point clouds. Journal of Field Robotics. https://doi.org/10.1002/rob.21988
     Publisher    Bibtex source
  4. Kubelka, V., Reinstein, M., & Svoboda, T. (2016). Improving multimodal data fusion for mobile robots by trajectory smoothing. Robotics and Autonomous Systems, 84, 88–96.
     Bibtex source
  5. Kubelka, V., Oswald, L., Pomerleau, F., Colas, F., Svoboda, T., & Reinstein, M. (2015). Robust data fusion of multimodal sensory information for mobile robots. Journal of Field Robotics, 32(4), 447–473.
     Bibtex source
  6. Simanek, J., Reinstein, M., & Kubelka, V. (2015). Evaluation of the EKF-based estimation architectures for data fusion in mobile robots. IEEE/ASME Transactions on Mechatronics, 20(2), 985–990.
     Bibtex source
  7. Simanek, J., Kubelka, V., & Reinstein, M. (2015). Improving multi-modal data fusion by anomaly detection. Autonomous Robots, 39(2), 139–154.
     Bibtex source

Conference Articles

  1. Vaidis, M., Dubois, W., Guénette, A., Laconte, J., Kubelka, V., & Pomerleau, F. (2023). Extrinsic calibration for highly accurate trajectories reconstruction. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). https://arxiv.org/abs/2210.01048
     Publisher    Bibtex source
  2. Kubelka, V., Vaidis, M., & Pomerleau, F. (2022). Gravity-constrained point cloud registration. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 4873–4879. https://doi.org/10.1109/IROS47612.2022.9981916
     Publisher    Bibtex source
  3. Vaidis, M., Giguère, P., Pomerleau, F., & Kubelka, V. (2021). Accurate outdoor ground truth based on total stations. 2021 18th Conference on Robots and Vision (CRV). https://arxiv.org/abs/2104.14396
     PDF    Publisher    Bibtex source
  4. Deschênes, S.-P., Baril, D., Kubelka, V., Giguère, P., & Pomerleau, F. (2021). Lidar Scan Registration Robust to Extreme Motions. 2021 18th Conference on Robots and Vision (CRV). https://doi.org/10.1109/CRV52889.2021.00014
     PDF    Publisher    Bibtex source
  5. Baril, D., Grondin, V., Deschenes, S., Laconte, J., Vaidis, M., Kubelka, V., Gallant, A., Giguere, P., & Pomerleau, F. (2020). Evaluation of Skid-Steering Kinematic Models for Subarctic Environments. 2020 17th Conference on Computer and Robot Vision (CRV), 198–205. https://doi.org/10.1109/CRV50864.2020.00034 Best Robotic Vision Paper Award!
     PDF    Publisher    Bibtex source
  6. Rouček, T., Pecka, M., Cizek, P., Petricek, T., Bayer, J., Salansky, V., Hert, D., Petrlik, M., Baca, T., Spurny, V., Pomerleau, F., Kubelka, V., Faigl, J., Zimmermann, K., Saska, M., Svoboda, T., & Krajnik, T. (2019). DARPA Subterranean Challenge: Multi-robotic exploration of underground environments. Proceeding of the Modelling and Simulation for Autonomous System Workshop (MESAS).
     Bibtex source
  7. Dandurand, P., Babin, P., Kubelka, V., Giguère, P., & Pomerleau, F. (2019). Predicting GNSS satellite visibility from dense point clouds. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics.
     PDF    Bibtex source
  8. Babin, P., Dandurand, P., Kubelka, V., Giguère, P., & Pomerleau, F. (2019). Large-scale 3D Mapping of Subarctic Forests. Proceedings of the Conference on Field and Service Robotics (FSR). Springer Tracts in Advanced Robotics.
     PDF    Slides    Bibtex source
  9. Jirku, M., Kubelka, V., & Reinstein, M. (2016). WiFi localization in 3D. 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 4551–4557.
     Bibtex source
  10. Kruijff-Korbayová, I., Freda, L., Gianni, M., Ntouskos, V., Hlaváč, V., Kubelka, V., Zimmermann, E., Surmann, H., Dulic, K., Rottner, W., & others. (2016). Deployment of ground and aerial robots in earthquake-struck amatrice in italy (brief report). 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 278–279.
     Bibtex source
  11. Kubelka, V., & Reinstein, M. (2014). Combining Complementary Motion Estimation Approaches to Increase Reliability in Urban Search & Rescue Missions. International Workshop on Modelling and Simulation for Autonomous Systems, 347–356.
     Bibtex source
  12. Reinstein, M., Kubelka, V., & Zimmermann, K. (2013). Terrain adaptive odometry for mobile skid-steer robots. 2013 IEEE International Conference on Robotics and Automation, 4706–4711.
     Bibtex source
  13. Kubelka, V., & Reinstein, M. (2012). Complementary filtering approach to orientation estimation using inertial sensors only. 2012 IEEE International Conference on Robotics and Automation, 599–605.
     Bibtex source

Miscellaneous

  1. Deschênes, S.-P., Baril, D., Kubelka, V., Giguère, P., & Pomerleau, F. (2023). Lidar Scan Registration Robust to Extreme Motions. Colloque REPARTI, Université Laval.
     Bibtex source
  2. Vaidis, M., Dubois, W., Guénette, A., Laconte, J., Kubelka, V., & Pomerleau, F. (2023). Extrinsic calibration for highly accurate trajectories reconstruction. Colloque REPARTI, Université Laval.
     Bibtex source
  3. Vaidis, M., Laconte, J., Kubelka, V., & Pomerleau, F. (2020). Improving the Iterative Closest Point Algorithm using Lie Algebra. In IROS 2020 Workshop - Bringing geometric methods to robot learning, optimization and control. https://doi.org/10.1109/CRV52889.2021.00012
     Bibtex source