Publications

To get the most recent overview, you can also have a look at my Google Scholar profile.

Theses

1. T. Pfeifer (2023). Adaptive Estimation using Gaussian Mixtures PhD Thesis, Chemnitz University of Technology, URL
2. T. Pfeifer (2014) Entwicklung eines mobilen Funkortungssystems auf Basis interferometrischer Phasenmessungen Master Thesis, Chemnitz University of Technology
3. T. Pfeifer (2012) Mikrocontroller gesteuertes Maximum Power Point Tracking für Solaran-wendungen Bachelor Thesis, Chemnitz University of Technology

Journal Articles

1. Haggag, K.; Lange, S.; Pfeifer, T. & Protzel, P. (2022)
   A Credible and Robust Approach to Ego-Motion Estimation Using an Automotive Radar, Robotics and Automation Letters (RA-L), DOI: 10.1109/LRA.2022.3162644
2. Pfeifer, T.; Lange, S. & Protzel, P. (2021)
   Advancing Mixture Models for Least Squares Optimization, Robotics and Automation Letters (RA-L), DOI: 10.1109/LRA.2021.3067307
3. Wen, W.; Pfeifer, T.; Bai, X. & Hsu, L.-T. (2021)
   Factor graph optimization for GNSS/INS integration: A comparison with the extended Kalman filter, NAVIGATION, DOI: 10.1002/NAVI.421
4. Viehweger, C.; Keutel, T.; Kasper, L.; Pfeifer, T. & Kanoun, O. (2013)
   System design and energy management for indoor solar energy harvesting under consideration of spectral characteristics of solar cells, Int. Journal of Measurement Technologies and Instrumentation Engineering (IJMTIE)

Conference Papers

1. Pöschmann, J.; Pfeifer, T. & Protzel, P. (2021)
   Optimization based 3D Multi-Object Tracking using Camera and Radar Data, Proc. of Intelligent Vehicles Symposium (IV), DOI: 10.1109/IV48863.2021.9575636
2. Pöschmann, J.; Pfeifer, T. & Protzel, P. (2020)
   Factor Graph based 3D Multi-Object Tracking in Point Clouds, Proc. of Int. Conf. on Intelligent Robots and Systems (IROS), DOI: 10.1109/IROS45743.2020.9340932
3. Wen, W.; Pfeifer, T.; Bai, X. & Hsu, L.-T. (2020)
   GNSS/LiDAR Integration Aided by Self-Adaptive Gaussian Mixture Model in Urban Scenarios: An Approach Robust to Non-Gaussian Noise, Proc. of Position Location and Navigation Symposium (PLANS), DOI: 10.1109/PLANS46316.2020.9110157
4. Pfeifer, T. & Protzel, P. (2019)
   Expectation-Maximization for Adaptive Mixture Models in Graph Optimization, Proc. of Int. Conf. on Robotics and Automation (ICRA), DOI: 10.1109/ICRA.2019.8793601
5. Pfeifer, T. & Protzel, P. (2019)
   Incrementally Learned Mixture Models for GNSS Localization, Proc. of Intelligent Vehicles Symposium (IV), DOI: 10.1109/IVS.2019.8813847
6. Pfeifer, T. & Protzel, P. (2018)
   Robust Sensor Fusion with Self-tuning Mixture Models, Proc. of Int. Conf. on Intelligent Robots and Systems (IROS), DOI: 10.1109/IROS.2018.8594459
7. Pfeifer, T.; Lange, S. & Protzel, P. (2017)
   Dynamic Covariance Estimation – a Parameter Free Approach to Robust Sensor Fusion, Proc. of Int. Conf. on Multisensor Fusion and Integration for Intelligent Systems (MFI), DOI: 10.1109/MFI.2017.8170347
8. Pfeifer, T.; Weissig, P.; Lange, S. & Protzel, P. (2016)
   Robust Factor Graph Optimization – a Comparison for Sensor Fusion Applications, Proc. of Int. Conf. on Emerging Technologies and Factory Automation (ETFA), DOI: 10.1109/ETFA.2016.7733598
9. Reisdorf, P.; Pfeifer, T.; Breßler, J.; Bauer, S.; Weissig, P.; Lange, S.; Wanielik, G. & Protzel, P. (2016)
   The Problem of Comparable GNSS Results – an Approach for a Uniform Dataset with Low-Cost and Reference Data, Proc. of Int. Conf. on Advances in Vehicular Systems, Technologies and Applications (VEHICULAR)
10. Lange, S.; Wunschel, D.; Schubert, S.; Pfeifer, T.; Weissig, P.; Uhlig, A.; Truschzinski, M. & Protzel, P. (2016)
    Two Autonomous Robots for the DLR SpaceBot Cup – Lessons Learned from 60 Minutes on the Moon, Proc. of Int. Symposium on Robotics (ISR)
11. Viehweger, C.; Pfeifer, T.; Keutel, T. & Kanoun, O. (2013)
    Dual-DC/DC Strategy for Enhanced Efficiency in Solar Powered Energy Harvesting, Proc. of SENSOR Conf., DOI: 10.5162/SENSOR2013/C8.4