Lecture on basic principles, requirements, and methods of sensor data processing. Since data are more often gathered by networked sensor systems, this lecture places particular emphasis on distributed sensor data fusion methods that can be applied in sensor networks.

Seminar on data analysis, time-to-failure prediction, and anomaly detection for predictive maintenance in industrial process automation. 

AMS lab projects on current, research-related areas like mobile robotics, sensor data fusion, navigation and planning, and optimization and control.

Lecture on the foundational principles and algorithms of mobile robotics, utilizing a flipped classroom approach. The course emphasizes a conceptual understanding of mobile robotics while introducing relevant mathematical underpinnings.