Self-localization of mobile robots with RFID system by using support vector machine

In recent years, RFID (radio frequency identification) system has become very popular in service industries, logistics and manufacturing, as it is an inexpensive and reliable device for automatic identification. Therefore, RFID system would be useful in a problem of mobile robot self-localization, if tags are distributed in the environment, and if the robot is equipped with a RFID reader to communicate with the tags. In this paper, we propose a novel method for learning-based localization with a RFID system by using support vector machine (SVM). In order to obtain various training data for SVM learning, a number of synthesized sensor data are generated from limited amount of real sensor data. We also propose a method that enables a user to easily place tags in effective locations. In experiments with a mobile robot, the performance of the proposed method is demonstrated.