Constrained Kalman filtering for indoor localization of transport vehicles using floor-installed HF RFID transponders

Abstract

Localization of transport vehicles is an important issue for many intralogistics applications. The paper presents an inexpensive solution for indoor localization of vehicles. Global localization is realized by detection of RFID transponders, which are integrated in the floor. The paper presents a novel algorithm for fusing RFID readings with odometry using Constraint Kalman filtering. The paper presents experimental results with a Mecanum based omnidirectional vehicle on a NaviFloor ® installation, which includes passive HF RFID transponders. The experiments show that the proposed Constraint Kalman filter provides a similar localization accuracy compared to a Particle filter but with much lower computational expense.

Room mapping system using RFID and mobile robots

“…Many of the existing studies are based on the use of the RSSI (received signal strength index) method [22], [23]. This is sometimes extended with methods related to odometry and the use of EKF filtering to increase the accuracy of position estimation [24]. There are also original solutions based, for example, on the phase measurement of the signal reflected from the transponder and carrying the information read from the transponder [25].…”