Abstract / truncated to 115 words (read the full abstract)

The level of automation in our society is ever increasing. Technologies like self-driving cars, virtual reality, and fully autonomous robots, which all were unimaginable a few decades ago, are realizable today, and will become standard consumer products in the future. These technologies depend upon autonomous localization and situation awareness where careful processing of sensory data is required. To increase efficiency, robustness and reliability, appropriate models for these data are needed. In this thesis, such models are analyzed within three different application areas, namely (1) magnetic localization, (2) extended target tracking, and (3) autonomous learning from raw pixel information. Magnetic localization is based on one or more magnetometers measuring the induced magnetic field from magnetic objects. ... toggle 8 keywords

localization magnetic tracking extended target tracking signal processing machine learning gaussian processes deep dynamical model discretization


Wahlström, Niklas
Linköping University
Publication Year
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Nov. 30, 2015

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