Localization of RFID Tags by a Moving Robot, via Phase Unwrapping and Non-Linear Optimization

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

doi:10.1109/jrfid.2019.2936969

Cited by 53 publications

(11 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the inherent 2π ambiguity of phase measurements as well as the unknown offset term due to the transponders and the reader and antenna components make the implementation of phase-based positioning algorithms rather challenging [30]. To address this problem, phase unwrapping techniques can be adopted if multiple readings with a proper spatial sampling are collected [31]. In [32], robot localisation is achieved through a multi-hypothesis Extended Kalman Filter (EKF) which combines the data from odometry sensors with the phase of the signals backscattered by the reference tags.…”

Section: Introductionmentioning

confidence: 99%

Ranging-Free UHF-RFID Robot Positioning Through Phase Measurements of Passive Tags

Magnago

Palopoli

Buffi

et al. 2020

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

The phase of signals backscattered by Ultra High Frequency (UHF) Radio Frequency Identification (RFID) tags is generally more insensitive to multipath propagation than Received Signal Strength Indicator (RSSI). However, signal phase measurements are inherently ambiguous and could be further affected by unknown phase offsets added by the transponders. As a result, the localisation of an agent by using only signal phase measurements looks infeasible. In this paper, it is shown instead that the design of a dynamic position estimator (e.g. a Kalman filter) based only on signal phase measurement is actually possible. To this end, the necessary conditions to ensure theoretical local nonlinear observability are firstly demonstrated. However, a system that is locally observable guarantees convergence of the localisation algorithm only if the actual initial agent position is approximately known a priori. Therefore, the second part of the analysis covers the global observability, which ensures convergence starting from any initial condition in the state space. It is important to emphasise that complete observability holds only in theory. In fact, measurement uncertainty may greatly affect position estimation convergence. The validity of the analysis and the practicality of this localisation approach are further confirmed by numerical simulations based on an Unscented Kalman Filter (UKF).

show abstract

Section: Introductionmentioning

confidence: 99%

Ranging-Free UHF-RFID Robot Positioning Through Phase Measurements of Passive Tags

Magnago

Palopoli

Buffi

et al. 2020

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

show abstract

“…As an alternative, the phase samples can be assembled in a phasor sequence [36], [37] and then employed as an input of the localization algorithm. In both methods, multiple readings with a proper spatial sampling must be available [38]. Furthermore, the offset term φ 0 should be correctly measured to derive the distance information from (2), leading to time-consuming calibration procedures.…”

Section: Uhf Rfid Systemsmentioning

confidence: 99%

A Survey on Indoor Vehicle Localization Through RFID Technology

2021

View full text Add to dashboard Cite

This paper presents a state-of-the-art analysis on the methods suitable for vehicle indoor localization and exploiting the RFID (Radio Frequency IDentification) technology. The survey describes three main categories of vehicle localization systems: (i) solutions exploiting only the RFID technology, (ii) sensor-fusion techniques combining data from RFID systems and proprioceptive sensors, and (iii) sensorfusion techniques combing RFID data with those of other exteroceptive sensors in addition to the RFID system itself. For each method, implementation and methodological details are discussed, by highlighting the applied RFID technology, namely passive HF-RFID, passive UHF-RFID, or any other RFID system. Also, the employed RFID parameters, i.e., tag EPC, RSSI or backscattered phase, are discussed. The survey focuses on the achievable localization performance, also accounting for infrastructure-deployment costs together with complexity and maintenance overhead. Positioning, tracking, navigation and simultaneous localization and mapping (SLAM) issues are here considered. The analysis highlights pros and cons of each method, together with the main challenges and perspectives of RFID-based solutions for vehicle localization.

show abstract

“…The method median error of this method is 24 cm, in an indoor office environment with six targeted tags. In [49], the authors propose a phase unwrapping approach together with a Non-Linear Optimization algorithm, named as Phase ReLock. The robot moves over a planar trajectory measured through a laser-based system, on a plane parallel to the plane the tag lies on.…”

Section: Related Workmentioning

confidence: 99%

Robot-Based Indoor Positioning of UHF-RFID Tags: The SAR Method With Multiple Trajectories

Bernardini

Buffi

Fontanelli

et al. 2021

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

This paper presents the application of the Synthetic Aperture Radar (SAR) localization method for indoor positioning of UHF-RFID tags when the robot-mounted reader antenna moves alongside multiple trajectories. By properly combining the phase data associated to a set of multiple paths, the synthetic apertures along the main directions enlarge and then the localization accuracy may improve. Besides, during consecutive inventory rounds, several tag position estimates are available and they can be profitably combined to minimize the localization uncertainty. Different combination approaches are investigated to determine the best choice to improve the localization performance. The method capabilities are discussed through a numerical analysis, by considering different configurations of the multiple apertures and different sources of measurement uncertainty. Finally, the proposed localization method is validated through an experimental analysis carried out with commercial RFID hardware and a robotic wheeled walker, in an indoor scenario, by employing different types of tags. The knowledge of the reader/robot trajectory required by the SAR method is here achieved with an optical system.

show abstract

Localization of RFID Tags by a Moving Robot, via Phase Unwrapping and Non-Linear Optimization

Cited by 53 publications

References 30 publications

Ranging-Free UHF-RFID Robot Positioning Through Phase Measurements of Passive Tags

Ranging-Free UHF-RFID Robot Positioning Through Phase Measurements of Passive Tags

A Survey on Indoor Vehicle Localization Through RFID Technology

Robot-Based Indoor Positioning of UHF-RFID Tags: The SAR Method With Multiple Trajectories

Contact Info

Product

Resources

About