Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach ††
1
Department of Industrial Engineering, University of Trento, 38123 Trento, Italy
2
Department of Information Engineering, University of Pisa, 56122 Pisa, Italy
3
Department of Engineering and Computer Science, University of Trento, 38123 Trento, Italy
4
Department of Energy, Systems, Territory and Constructions Engineering, University of Pisa, 56122 Pisa, Italy
*
Author to whom correspondence should be addressed.
†
This paper is an extended version of a conference paper published in 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, Rome, Italy, 7–9 June 2021.
‡
Current address: Department of Industrial Engineering, University of Trento, Via Sommarive, 9, 38123 Povo, Italy.
Academic Editor: Carlo Massaroni
Sensors 2021, 21(3), 717; https://doi.org/10.3390/s21030717
Received: 23 December 2020 / Revised: 17 January 2021 / Accepted: 19 January 2021 / Published: 21 January 2021
(This article belongs to the Special Issue Selected papers from the 2020 IEEE International Worshop on Metrology for Industry 4.0 and IoT)
Autonomous vehicles enable the development of smart warehouses and smart factories with an increased visibility, flexibility and efficiency. Thus, effective and affordable localisation methods for indoor vehicles are attracting interest to implement real-time applications. This paper presents an Extended Kalman Smoother design to both localise a mobile agent and reconstruct its entire trajectory through a sensor-fusion employing the UHF-RFID passive technology. Extensive simulations are carried out by considering the smoother optimal-window length and the effect of missing measurements from reference tags. Monte Carlo simulations are conducted for different vehicle trajectories and for different linear and angular velocities to evaluate the method accuracy. Then, an experimental analysis with a unicycle wheeled robot is performed in real indoor scenario, showing a position and orientation root mean square errors of 15 cm, and 0.2 rad, respectively.
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MDPI and ACS Style
Shamsfakhr, F.; Motroni, A.; Palopoli, L.; Buffi, A.; Nepa, P.; Fontanelli, D. Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach †. Sensors 2021, 21, 717. https://doi.org/10.3390/s21030717
AMA Style
Shamsfakhr F, Motroni A, Palopoli L, Buffi A, Nepa P, Fontanelli D. Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach †. Sensors. 2021; 21(3):717. https://doi.org/10.3390/s21030717
Chicago/Turabian StyleShamsfakhr, Farhad; Motroni, Andrea; Palopoli, Luigi; Buffi, Alice; Nepa, Paolo; Fontanelli, Daniele. 2021. "Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach †" Sensors 21, no. 3: 717. https://doi.org/10.3390/s21030717
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