Abstract:
A global indoor localization system based on the radio frequency identification (RFID) technology. A reader, installed on the robot, measures the received signal strength indication (RSSI) and the phase shift of UHF-RFID signals coming from a set of passive tags deployed on the ceiling of the environment. The position of the tags in the environment is only roughly known at the beginning. Exploiting the complementary features of RSSI and phase-shift information in RFID signals. a multi hypothesis extended and unscented Kalman filter is proposed to localize the robot and to simultaneously improve the initial estimate on the tag coordinates. The simulative and experimental results are reported to illustrate the effectiveness of the proposed approach. THE localization of mobile robots using radio frequency identification (RFID) has received a considerable attention in the last few years see among many others. In many cases, the localization system is realized by installing a reader on the robot and by providing the environment with a certain number of tags placed in known position. In particular, when using passive tags, a list of appealing features can be pointed out: tags are cheap, virtually maintenance free, and can be univocally identified by the reader, bypassing the well-known data association problem. RFID data used for localization vary from a binary information the tag detection to a more complete set of information, like received signal strength indication RSSI or phase shift of the signal.