Using UHF-RFID Signals for Robot Localization Inside Pipelines

Gunatilake, Amal; Thiyagarajan, Karthick; Kodagoda, Sarath; Piyathilaka, Lasitha; Darji, Poojaben

doi:10.36227/techrxiv.14658795

Cited by 6 publications

(8 citation statements)

References 20 publications

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“…It can be analogously similar to a stereo camera system. UHF-RFID Tag type A and B discussed in [31] has been used to conduct experiments. An industry standard infrared laser distance sensor with 80m range, and 1mm accuracy has been used as the robot's location ground truth.…”

Section: A Development Of An In-pipe Robotic Prototype For Slammentioning

confidence: 99%

“…Performance of the proposed algorithm was compared with industry standard, commonly used encoder odometry based robot localization (OD) and also with the Gaussian process combined particle filter based two antenna model localization method (GPPF2) we have proposed in our preliminary research work [31], [32].…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Unlike RFID localization in outdoor or indoor applications, the highest peak of signal intensity is not always referring to the most likely location of the RFID tag [29], [30]. The pipe surface behaves like a waveguide causing the signal inside to bounce leading to various peaks and ripple effects in the signal strength [31], [32]. Furthermore, commercial off-the-shelf (COTS) RFID readers offer erratic measurements, only capable of accurately localizing the RFID tag within a square meter area [33], making the process difficult and unique.…”

Section: Introductionmentioning

confidence: 99%

“…The Gaussian process combined particle filter localization methodology using UHF-RFID signals has been proposed in our previous research [31], [32], [34], and it takes advantage of both Received Signal Strength Indicator (RSSI) and Phase data values to improve accuracy. It works well with known RFID distribution maps (RFID tag locations are known), and it has millimetre-level accuracy when using known RFID distribution maps.…”

Section: Introductionmentioning

confidence: 99%

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Battery-Free UHF-RFID Sensors-Based SLAM for In-Pipe Robot Perception

2022

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Water utilities across the globe are concerned with the inspection and replacement of buried metallic water pipes due to corrosion-related structural damages. Internal pipe linings are commonly used as a renewal method to improve structural strength as they are regarded to be a less expensive alternative to costly and time-consuming pipe replacements. However, linings are also prone to failure as well. Therefore, water authorities regularly monitor lining performance, where defect evolution over a long period of time is an important parameter to note. It requires an accurate in-pipe robot localization technology. In this article, we propose a novel method for in-pipe robot localization and tag mapping that uses battery-free UHF-RFID sensor wireless signals. It utilizes a signal mapping approach in combination with a tailored posegraph simultaneous localization and mapping algorithm. Evaluation results of a field-extracted pipe sample from Sydney Water's distribution network show the proposed approach is capable of localizing the robot within 2.5cm accuracy in a 50m equivalent pipe with an unknown UHF-RFID distribution. The proposed approach outperformed other reported similar work in the literature.

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Section: A Development Of An In-pipe Robotic Prototype For Slammentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Battery-Free UHF-RFID Sensors-Based SLAM for In-Pipe Robot Perception

2022

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“…The 1D odometry measures the robot's distance from its starting location. Underground pipe robots are an example [8]. In this circumstance, it is crucial to know the robot's longitudinal position to determine where to begin the pipe examination and to locate defects.…”

Section: Introductionmentioning

confidence: 99%

Deep Learned Ground Penetrating Radar Subsurface Features for Robot Localization

Wickramanayake¹,

Thiyagarajan²,

Kodagoda³

2022

Preprint

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<p>Sensors help robots perceive their environment and localize themselves. Determining a robot’s location requires a range of sensing systems. Depending on accuracy criteria and navigation conditions, robot localization sensors can differ. Common sensors for robot localization include encoders, GPS, cameras, LIDARs, and IMUs. Traditional sensors are not capable enough in changing environments and uneven terrain. In this paper, we propose a method based on deep learning to use the subsurface features obtained through a Ground Penetrating Radar (GPR) to estimate the odometry of a robot. This proposed method does not rely on visual features or the distance gathered from wheel encoders. The proposed approach was evaluated on a publicly available dataset, and the evaluation results show that the proposed method can be used for robot localization without the need for odometry from wheel encoders.</p>

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

2021

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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 UHF-RFID 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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Using UHF-RFID Signals for Robot Localization Inside Pipelines

Cited by 6 publications

References 20 publications

Battery-Free UHF-RFID Sensors-Based SLAM for In-Pipe Robot Perception

Battery-Free UHF-RFID Sensors-Based SLAM for In-Pipe Robot Perception

Deep Learned Ground Penetrating Radar Subsurface Features for Robot Localization

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

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