Authors:
Lukas Rosenbauer
1
;
Johannes Maier
1
;
Daniel Gerber
1
;
Anthony Stein
2
and
Jörg Hähner
3
Affiliations:
1
BSH Hausgeräte GmbH, Im Gewerbepark B35, Regensburg, Germany
;
2
Artificial Intelligence in Agricultural Engineering, University of Hohenheim, Garbenstr. 9, Stuttgart, Germany
;
3
Organic Computing Group, University of Augsburg, Am Technologiezentrum 8, Augsburg, Germany
Keyword(s):
Automation, Optimization, Bio-inspired Computation, Intelligent Computing, Genetic Algorithm, Calibration, Signal Processing, Human Machine Interface.
Abstract:
Touch interfaces are human machine interface (HMI) that can be found in a wide range of products ranging from mobile phones over cars to home appliances. Many of these HMIs measure digital signals which are used to detect touch events. These signals are processed using filters in order to decide whether there is a touch event or not. The filterchain must be functional even if the signal contains heavy noise. Thus a precise calibration of the individual filters is necessary. We employ a genetic algorithm (GA) to choose the filter parameters automatically. We evaluate our approach in a series of experiments which includes simulated as well as real data. We additionally compare our GA with manually calibrated parameters and thereby show the superiority of our method in terms of the accuracy of the calibration provided. A cost-intensive manual calibration can thus be avoided.