University of Alcalá
|Type of Publication:||JCR Journal||Keywords:||WiFi and Ultrasound robot navigation system; WiFi signal strength localization system; Partially Observable Markov Decision Process|
This paper presents an automatic training method based on the Baum?Welch algorithm (also known as EM algorithm) and a robust low-level controller. The method has been applied to the indoor autonomous navigation of a surveillance robot that utilizes a WiFi+Ultrasound Partially Observable Markov Decision Process (POMDP). This method uses a robust local navigation system to automatically provide some WiFi+Ultrasound maps. These maps could be employed within probabilistic global robot localization systems. These systems use a priori probabilistic map in order to estimate the global robot position. The method has been tested in a real environment using two commercial Pioneer 2AT robotic platforms in the premises of the Department of Electronics at the University of Alcalá. Some experimental results and conclusions are presented.
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