Pose Estimation of Mobile Robots Using Floor-Installed RFID Tags

Pose estimation of mobile robots is an important issue for many industrial applications. The paper presents an inexpensive solution for pose estimation of mobile robots in indoor environments. Pose estimation is realized by interpreting the received signal strength indicator (RSSI) of RFID tags, which are integrated in the floor and detected by the reader. The paper presents two algorithms for fusing RFID signal strength measurements with odometry based on Kalman filtering. The paper presents experimental results with a Mecanum based omnidirectional mobile robot on a NaviFloor○ ​​​​​​​R installation, which includes passive HF RFID tags. The experiments show that the proposed algorithms provide a better performance compared to the same algorithms which consider the detection of the tags only.

[1]  Christof Röhrig,et al.  Constrained Kalman filtering for indoor localization of transport vehicles using floor-installed HF RFID transponders , 2015, 2015 IEEE International Conference on RFID (RFID).

[2]  Yu Liu,et al.  Resource Management with RFID Technology in Automatic Warehouse System , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  G. Hoblos,et al.  State estimation under nonlinear state inequality constraints. A tracking application , 2008, 2008 16th Mediterranean Conference on Control and Automation.

[4]  Axel Steinhage,et al.  SensFloor® and NaviFloor®: Large-Area Sensor Systems beneath Your Feet , 2011 .

[5]  R. Curry Estimation and Control with Quantized Measurements , 1970 .

[6]  Jian Mi,et al.  Performance analysis of mobile robot self-localization based on different configurations of RFID system , 2015, 2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).

[7]  Shigeki Sugano,et al.  Pose estimation of a mobile robot on a lattice of RFID tags , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Jian Mi,et al.  Low cost design of HF-band RFID system for mobile robot self-localization based on multiple readers and tags , 2015, 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[9]  Francesco Martinelli,et al.  A Passive UHF-RFID System for the Localization of an Indoor Autonomous Vehicle , 2012, IEEE Transactions on Industrial Electronics.

[10]  Andre Heller,et al.  Global Localization and Position Tracking of Automatic Guided Vehicles using passive RFID Technology , 2014, ISR 2014.

[11]  D. Simon Kalman filtering with state constraints: a survey of linear and nonlinear algorithms , 2010 .

[12]  Francesco Martinelli,et al.  Constrained and quantized Kalman filtering for an RFID robot localization problem , 2010, Auton. Robots.

[13]  Eric Guizzo,et al.  Three Engineers, Hundreds of Robots, One Warehouse , 2008, IEEE Spectrum.

[14]  Cristian Secchi,et al.  An Inertial/RFID Based Localization Method for Autonomous Lawnmowers , 2012, SyRoCo.