A sensor fusion framework for online sensor and algorithm selection

This paper presents a sensor fusion framework for selecting online the most reliable logical sensors and the most suitable algorithm for fusing sensor data in a robot platform. The framework is rule-based, employing the concept of using the simplest sensor fusion algorithm with the most reliable sensors. The framework is realized by implementing measures that were developed to quantify online sensor performance. Statistical, histogram, time series and graphical analyses demonstrate the advantages of this new framework.