Machine learning approach to self-localization of mobile robots using RFID tag

Abstract

This paper proposes a method for the self-localization of a mobile robot using a passive radio frequency identification (RFID) system and support vector machines (SVMs). Using the SVM, we do not need to perform any complicated tasks for measuring the geometric position of each RFID tags to produce a look-up table as used by conventional self-localization methods. Moreover, the method works even when several malfunctioning tags are included. The performance and accuracy of the method are confirmed by our simulation test, and we conclude that the method shows almost the same performance as that of a look-up table.