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A Platform for Teaching Sensor Fusion Using a Smartphone
Linköping University.
Linköping University.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.ORCID iD: 0000-0002-4634-7240
Linköping University.
2017 (English)In: International journal of engineering education, ISSN 0949-149X, Vol. 33, no 2B, p. 781-789Article in journal (Refereed) Published
Abstract [en]

A platform for sensor fusion consisting of a standard smartphone equipped with the specially developed Sensor Fusion appis presented. The platform enables real-time streaming of data over WiFi to a computer where signal processingalgorithms, e.g., the Kalman filter, can be developed and executed in a Matlab framework. The platform is an excellenttool for educational purposes and enables learning activities where methods based on advanced theory can be implementedand evaluated at low cost. The article describes the app and a laboratory exercise developed around these new technologicalpossibilities. The laboratory session is part of a course in sensor fusion, a signal processing continuation course focused onmultiple sensor signal applications, where the goal is to give the students hands on experience of the subject. This is done byestimating the orientation of the smartphone, which can be easily visualized and also compared to the built-in filters in thesmartphone. The filter can accept any combination of sensor data from accelerometers, gyroscopes, and magnetometers toexemplify their importance. This way different tunings and tricks of important methods are easily demonstrated andevaluated on-line. The presented framework facilitates this in a way previously impossible.

Place, publisher, year, edition, pages
2017. Vol. 33, no 2B, p. 781-789
Keywords [en]
electrical engineering education, student experiments, sensor fusion, inertial sensors, Kalman filter
National Category
Signal Processing Control Engineering Pedagogical Work
Identifiers
URN: urn:nbn:se:uu:diva-335217OAI: oai:DiVA.org:uu-335217DiVA, id: diva2:1161949
Available from: 2017-12-01 Created: 2017-12-01 Last updated: 2017-12-02

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