Simultaneous localization and mapping using a short-range passive RFID reader with sparse tags in large environments

The radio frequency identification (RFID) technology has been studied and used to solve the localization and mapping problems in which most of studies use long-range active or passive RFID systems with multiple readers and dense tags. In this paper, we propose to use a short-range passive RFID reader to accomplish extended Kalman filter (EKF) based simultaneous localization and mapping (SLAM) with sparse tags in large indoor environments. We demonstrate that it is feasible to accomplish SLAM with sufficient accuracy using only odometry and short-range RFID data. The simulation and experimental results demonstrate the feasibility of the proposed system.