Low level controller for a POMDP based on WiFi observations

This paper shows the results of a low level controller that has been applied to an autonomous robotic system using a WiFi-based Partially Observable Markov Decision Process (POMDP). These observations provide a clue for global robot localization from the first iteration of the POMDP algorithm. Due to the noise channel of WiFi measures, it becomes necessary to make observations at a well known location within the environment. Therefore, a robust local navigator is needed in order to place the robot in an optimal position for making the observation. The system has been tested with two Pioneer 2AT robots in the premises of the Department of Electronics at the University of Alcalá.