RF-SLAM: UHF-RFID Based Simultaneous Tags Mapping and Robot Localization Algorithm for Smart Warehouse Position Service

Chong Wu, Zeyu Gong, Bo Tao, Ke Tan, Zhenfeng Gu, Zhou-Ping Yin

Abstract: In this article, we propose an RFID-based simultaneous localization and mapping (RF-SLAM) method that allows us, for the first time, to estimate the robot's position and the tags’ 3D position in the warehouse environment simultaneously without any reference tags and external sensors, using only COTS RFID device. RF-SLAM is designed to transform the RFID measurement into the relative tag position constraint and use a corresponding graph based model to solve the SLAM problem. Specifically, a multiantenna-based relative localization method using phase measurement and odometer data in a short time is proposed as the front end. The back end is a novel graph model based on the relative tags position constraint and odometer constraint. Experiments in different types of warehouses show the localization accuracy of robot and tags’ 3D position is about 5 cm and 10 cm, respectively. The experimental results in a more challenging and actual environment are still competitive.