Nathan Bartlett
Teaching
MCHA6100
This course deepens students’ knowledge in Bayesian estimation. The course covers several data fusion techniques, including the topic of data association, advanced system identification, filtering versus smoothing, sensor modelling and calibration, robot mapping and map types, robot localisation, and simultaneous localisation and mapping (SLAM). I was fortunate to present my research and expertise in SLAM, further aiding in the students’ understanding in the importance of Bayesian estimation and probability theory.
MCHA2000
This course teaches the fundamentals of modelling and simulating mechatronic systems. Systems analysed in this course have interacting mechanical translation, mechanical rotation, electrical, and fluid components.
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MCHA6100
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