Trajectory Planning of a Moving Robot Empowers 3D Localization of RFID Tags With a Single Antenna

Tzitzis, Anastasios; Megalou, Spyros; Siachalou, Stavroula; Tsardoulias, Emmanouil; Filotheou, Alexandros; Yioultsis, Traianos V.; Dimitriou, Antonis G.

doi:10.1109/jrfid.2020.3000332

Cited by 30 publications

(7 citation statements)

References 34 publications

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“…In [31], the authors have put forth a novel technique for localizing 3D RFID tags that involves driving the motion of an antenna coupled to a mobile robot along non-straight paths. Results show a 35 cm mean error in a case where tags are positioned on several vertical planes.…”

Section: State Of the Artmentioning

confidence: 99%

“…Robot motion followed curved paths inside an office scenario moving around some tags displaced at the center of the environments and facing several tags mounted on the office walls. Figure [31] 34.8 cm (28.2 cm) Work in [32] 20.27 cm (26.0 cm) Work in [33] 13.0 cm (6.3 cm) PF-KU 1.15 cm (0.1 cm) PF-KW 1.17 cm (0.3 cm) 12 shows the acquired motions of the antennas and the tags' positions.…”

Section: Experimental Datasetmentioning

confidence: 99%

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A UHF Passive RFID Tag Position Estimation Approach Exploiting Mobile Robots: Phase-Only 3D Multilateration Particle Filters With No Unwrapping

Tripicchio,

D’Avella,

Unetti

et al. 2024

IEEE Access

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Radio-frequency identification is one of the Internet of Things' most promising technologies and has been recently used in combination with mobile robots for logistics in business and retail applications. This manuscript deals with the localization of passive UHF RFID tags within industrial environments employing receiving antennas mounted on a mobile robot by using multilateration techniques that exploit narrowband phase-delay measurements. Two distinct Particle Filter approaches are presented to solve the 3D multilateration problem online and take advantage of a synthetic aperture created by the motion of the robot in the environment. One of the methods can operate in the presence of acquisition jumps since it does not rely on an unwrapping technique. Experimental results show promising performance concerning the recent literature. Moreover, the presented approach enables robust estimations concerning signal loss due to communication disturbances in noisy environments, typical of the industrial setting.

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Section: State Of the Artmentioning

confidence: 99%

Section: Experimental Datasetmentioning

confidence: 99%

A UHF Passive RFID Tag Position Estimation Approach Exploiting Mobile Robots: Phase-Only 3D Multilateration Particle Filters With No Unwrapping

Tripicchio,

D’Avella,

Unetti

et al. 2024

IEEE Access

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“…The latter is typically solved through the employment of the Phase Difference of Arrival (PDoA) [ 29 ]. Indeed, unwrapping techniques [ 30 ] or phasor use [ 31 ] can face and solve the phase ambiguity issue.…”

Section: Related Workmentioning

confidence: 99%

Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach †

Shamsfakhr

Motroni

Palopoli

et al. 2021

Sensors

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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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“…This kind of approaches is effective even if has to fight with the limited allowed range of RFID frequency dictated by Federal Communications Commission (FCC) regulations, which motivates the interesting approach proposed in [4]. Another possible solution is the one based on measurements taken from different positions, whose relative displacement must be known [5], [6], [7]. The ambiguity in phase measurements can This work is licensed under a Creative Commons Attribution 4.0 License.…”

Section: Introductionmentioning

confidence: 99%

Robust Simultaneous Localization and Mapping Using Range and Bearing Estimation of Radio Ultra High Frequency Identification Tags

Romanelli

Martinelli

Giampaolo

2023

IEEE Trans. Contr. Syst. Technol.

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In this article, we consider an indoor simultaneous localization and mapping (SLAM) problem for a mobile robot measuring the phase of the signal backscattered by a set of passive radio ultra high frequency identification (ID) tags, deployed in unknown position on the ceiling of the environment. The solution approach is based on the introduction, for each radio frequency identification (RFID) tag observed, of a multihypothesis extended Kalman filter (MHEKF) which, based on the measured phases and on the wheel encoder readings, provides an estimate of the range and of the bearing of the observed tag with respect to the robot. This information is then used in an extended Kalman filter (EKF) solving the SLAM problem. Since an effective range and bearing estimate is available only after some steps, a resilient module is added to the algorithm to evaluate the reliability of the position estimate of each observed tag. As shown through numerical and experimental results, this makes the proposed approach robust with respect to several kinds of unmodeled disturbances, like multipath effects or even the unexpected change of the position of a tag.

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Trajectory Planning of a Moving Robot Empowers 3D Localization of RFID Tags With a Single Antenna

Cited by 30 publications

References 34 publications

A UHF Passive RFID Tag Position Estimation Approach Exploiting Mobile Robots: Phase-Only 3D Multilateration Particle Filters With No Unwrapping

A UHF Passive RFID Tag Position Estimation Approach Exploiting Mobile Robots: Phase-Only 3D Multilateration Particle Filters With No Unwrapping

Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach †

Robust Simultaneous Localization and Mapping Using Range and Bearing Estimation of Radio Ultra High Frequency Identification Tags

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