An RFID-Based Mobile Robot Localization Method Combining Phase Difference and Readability

Tao, Bo; Wu, Haibing; Gong, Zeyu; Yin, Zhouping; Ding, Han

doi:10.1109/tase.2020.3006724

Cited by 60 publications

(31 citation statements)

References 25 publications

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“…What is more, the effect of infrastructure and localization algorithms on position accuracy, in RFID-based robot location systems, was investigated in [ 35 ]. In [ 36 ], a particle filter was employed to use the phase difference between two steps of the mobile robot for localization and tracking. This method is similar to the landmark-based method and requires a high density of tags.…”

Section: Related Workmentioning

confidence: 99%

Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals

Zhang

Gong

Liu

et al. 2021

Sensors

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State-of-the-art radio frequency identification (RFID)-based indoor autonomous vehicles localization methods are mostly based on received signal strength indicator (RSSI) measurements. However, the accuracy of these methods is not high enough for real-world scenarios. To overcome this problem, a novel dual-frequency phase difference of arrival (PDOA) ranging-based indoor autonomous vehicle localization and tracking scheme was developed. Firstly, the method gets the distance between the RFID reader and the tag by dual-frequency PDOA ranging. Then, a maximum likelihood estimation and semi-definite programming (SDP)-based localization algorithm is utilized to calculate the position of the autonomous vehicles, which can mitigate the multipath ranging error and obtain a more accurate positioning result. Finally, vehicle traveling information and the position achieved by RFID localization are fused with a Kalman filter (KF). The proposed method can work in a low-density tag deployment environment. Simulation experiment results showed that the proposed vehicle localization and tracking method achieves centimeter-level mean tracking accuracy.

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Section: Related Workmentioning

confidence: 99%

Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals

Zhang

Gong

Liu

et al. 2021

Sensors

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“…Obtaining distinct signal signatures from antennas for the same UHF-RFID sensor will significantly aid in localization, as we can multiply the unique data measurements for a specific location as the number of antennas increases. As some research indicates that signal interference between antennas can occur depending on the hardware used to trigger both antennas simultaneously to receive signals [18], we conducted another test to determine if our hardware exhibits any indication of such incidents. We collected data from each antenna separately by running inside the pipe, and then from both antennas simultaneously.…”

Section: Experiments and Resultsmentioning

confidence: 99%

Evaluation of Battery-free UHF-RFID Sensor Wireless Signals for In-pipe Robotic Applications

Gunatilake¹,

Thiyagarajan²,

Kodagoda³

2021

Preprint

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A reliable robotic localization method is required for comparing three-dimensional pipe maps obtained via laser scans at various times for accurately monitoring the evolution of internal pipe surface defects. Existing robotic localization methods have limitations when visual features vanish due to changes in the pipe environment or when encoder data becomes highly uncertain due to long-distance robotic traverses. To address this issue, we leverage battery-free ultra-high frequency radio frequency identification (UHF-RFID) sensors for transmitting wireless signals to a two-antenna reader integrated mobile robotic system. Although there are literature on the investigation of UHFRFID behaviors and their applications in indoor environments, analysis of the same for in-pipe scenarios was not well studied. In this paper, we evaluate the UHF-RFID sensor signals inside a field extracted pipeline. Firstly, we examine the UHF-RFID sensor signal patterns through repeated robotic scans. Secondly, we examine how the placement of UHF-RFID reader antennas affects the transmission of UHF-RFID sensor signals, as well as we study the effects of robotic traverse direction and speed on the UHF-RFID wireless signals. Finally, we examine whether identical UHF-RFID sensors generate the same pattern when placed in a pipeline. Overall, the experimental evaluation demonstrates that the use of two-antenna UHF-RFID readers can ameliorate the capabilities of robotic localization in the pipeline.

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“…Although some solutions rely on the combination of phase and amplitude measurements [ 26 , 33 ], phase-only measurements prove to be quite effective in indoor environments [ 21 ]. To account for the phase ambiguity, different filters were provided that are based on the fusion with wheel encoders, ranging from Unscented Kalman Filters (UKF) [ 37 ], Multi-Hypothesis EKF [ 32 ] and particle filters [ 35 ].…”

Section: Discussionmentioning

confidence: 99%

“…In [ 35 ], a particle filter was presented to track a mobile robot equipped with two rotary encoders and two RFID antennas facing to the floor. The algorithm exploits the PDoA gathered by an infrastructure of reference tags deployed on the floor.…”

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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An RFID-Based Mobile Robot Localization Method Combining Phase Difference and Readability

Cited by 60 publications

References 25 publications

Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals

Localization and Tracking of an Indoor Autonomous Vehicle Based on the Phase Difference of Passive UHF RFID Signals

Evaluation of Battery-free UHF-RFID Sensor Wireless Signals for In-pipe Robotic Applications

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

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