CS Forum: Manon Kok, Delft University of Technology "Probabilistic modelling for sensor fusion with inertial measurements"
Probabilistic modelling for sensor fusion with inertial measurements
Assistant Professor Manon Kok
Delft University of Technology
In recent years, inertial sensors have undergone major developments. The quality of their measurements has improved while their cost has decreased, leading to an increase in availability. They can be found in stand-alone sensor units, so-called inertial measurement units, but are nowadays also present in for instance any modern smartphone, in Wii controllers and in virtual reality headsets.
The term inertial sensor refers to the combination of accelerometers and gyroscopes. They measure the external specific force and the angular velocity, respectively. Integration of their measurements provides information about the sensor's position and orientation. However, the position and orientation estimates obtained by simple integration suffer from drift and are therefore only accurate on a short time scale. In order to improve these estimates, we combine the inertial sensors with additional sensors and models. To combine these different sources of information, also called sensor fusion, we make use of probabilistic models to take the uncertainty of the different sources of information into account.
In this talk, I will discuss some of the work that I have done on the topic. First, I will discuss our approach to inertial human body motion capture, where we use data from multiple inertial sensors placed on the human body to estimate the body's position and orientation. Second, I’ll discuss our work on combining inertial sensors with time of arrival measurements from an ultrawideband (UWB) system. We model the UWB measurements using a tailored heavy-tailed asymmetric distribution. This distribution naturally handles the possibility of measurement delays due to multipath and non-line-of-sight conditions while not allowing for the possibility of measurements arriving early, i.e. traveling faster than the speed of light.
Manon Kok is Assistant Professor at the Delft Center for Systems and Control at the Delft University of Technology in the Netherlands. She received her PhD from the Automatic Control group at Linköping University, Sweden in 2017. In 2017 / 2018, she worked as a Research Associate in the Machine Learning Group of the Computational and Biological Learning Lab at the University of Cambridge. Her research interests are in probabilistic modelling for sensor fusion and signal processing. She has a specific interest in sensor fusion using inertial sensors and magnetometers for human motion capture and for indoor localisation.
CS forum is a seminar series arranged at the CS department. The talks are intended for presentations of postdoctoral level researchers and professors, both for visiting and CS-department-based researchers.