Tim Pfeifer

Developing robust localization algorithms that dynamically adapt to unforeseen conditions.

Just after defending my PhD, I joined the RTLS department of Siemens AG to develop robust indoor localization systems. This move to industry allows me to apply my experience in robust and adaptive state estimation to real-world applications.

During the wonderful time at the Chair of Automation Technology at the Chemnitz University of Technology, I had the opportunity to develop several approaches for robust sensor fusion. If you are interested in specific algorithms, please have a look at my publications here.

One important lesson from my time in academia is that the assumption of Gaussian measurement errors is problematic. Non-Gaussian errors occur almost everywhere – when using satellite navigation, radio-based localization, or vision sensors. If we don’t account for them, any autonomous system can fail dramatically.

Leveraging my expertise in nonlinear optimization, maximum likelihood methods, and Bayesian inference, I continue develop probabilistically plausible algorithms that can effectively adapt to unforeseen conditions. By enhancing the robustness of autonomous systems, my work contributes to improving their overall performance and reliability.

Please feel free to write me a mail.