Thomas Wiedemann

Hi,
I am an external PhD student. While I am enrolled at Örebro University, I am working for the German Aerospace Center (DLR) at the Institute of Communications and Navigation close to Munich. Previously, I received my bachelor and master degree from the Technical University of Munich at the department of mechanical engineering.

My current research and PhD is focused on Mobile Robot Olfaction. Within this field I am particularly interested in an exploration strategy for a multi-robot system with the goal to find unknown gas sources or leaks. To this end, I am making use of a model-based approach where a partial differential equation serves as a physical model for gas dispersion. Besides, I am interested in Sparse Bayesian Learning techniques to incorporate prior assumptions about the unknown gas source distribution.

Contact

Thomas Wiedemann

AASS Research Centre
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Phone +49 8153 28 4214
thomas.wiedemann@dlr.de

Publications

Journal Articles

[1]	T. Wiedemann, A. J. Lilienthal and D. Shutin. Analysis of Model Mismatch Effects for a Model-based Gas Source Localization Strategy Incorporating Advection Knowledge. Sensors, 19(3), 2019 [ BibTeX \| DiVA \| PDF ]
[2]	T. Wiedemann, D. Shutin and A. J. Lilienthal. Model-based gas source localization strategy for a cooperative multi-robot system-A probabilistic approach and experimental validation incorporating physical knowledge and model uncertainties. Robotics and Autonomous Systems, 118:66-79, 2019 [ BibTeX \| DiVA \| PDF ]
[3]	V. Hernandez Bennetts, K. Kamarudin, T. Wiedemann, T. P. Kucner, S. L. Somisetty and A. J. Lilienthal. Multi-Domain Airflow Modeling and Ventilation Characterization Using Mobile Robots, Stationary Sensors and Machine Learning. Sensors, 19(5), 2019 [ BibTeX \| DiVA \| PDF ]

Refereed Conference and Workshop Articles

[1]	T. Wiedemann, M. Schaab, J. M. Gomez, D. Shutin, M. Scheibe and A. J. Lilienthal. Gas Source Localization Based on Binary Sensing with a UAV. In 2022 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) 2022 [ BibTeX \| DiVA ]
[2]	T. Wiedemann, D. Shutin and A. Lilienthal. Experimental Validation of Domain Knowledge Assisted Robotic Exploration and Source Localization. In 2021 IEEE International Conference on Autonomous Systems (ICAS) 2021 [ BibTeX \| DiVA \| PDF ]
[3]	T. Wiedemann, D. Shutin, V. Hernandez Bennetts, E. Schaffernicht and A. Lilienthal. Bayesian Gas Source Localization and Exploration with a Multi-Robot System Using Partial Differential Equation Based Modeling. In 2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN 2017) : Proceedings, pages 122-124, 2017 [ BibTeX \| DiVA ]
[4]	T. Wiedemann, C. Manss, D. Shutin, A. Lilienthal, V. Karolj and A. Viseras. Probabilistic modeling of gas diffusion with partial differential equations for multi-robot exploration and gas source localization. In 2017 European Conference on Mobile Robots (ECMR) 2017 [ BibTeX \| DiVA ]

Theses

[1]	T. Wiedemann. Domain Knowledge Assisted Robotic Exploration and Source Localization. Örebro University, School of Science and Technology, Ph.D. Thesis, 2020 [ BibTeX \| DiVA \| PDF ]

Find the complete BibTeX record here.