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

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.