Stereo Vision Combined With Laser Profiling for Mapping of Pipeline Internal Defects

Gunatilake, Amal; Piyathilaka, Lasitha; Tran, Antony; Vishwanathan, Vinoth Kumar; Thiyagarajan, Karthick; Kodagoda, Sarath

doi:10.1109/jsen.2020.3040396

Cited by 48 publications

(20 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this work, we leveraged the mini-PIRO robotic tool [9] for integrating UHF-RFID reader antenna and signal processing unit. The UHF-RFID reader antenna was assembled by integrating the Thingmagic M6e Micro-LTE UHF 2 port RFID reader module with the embedded developer kit and two 915MHz General Purpose Panel RF Antennas in the 902MHz to 928MHz range with 5.5dB gain.…”

Section: System Description and Testbed Overviewmentioning

confidence: 99%

“…However, if the linings are not applied properly, they could deteriorate in the short-term, and in longterm, surface defects such as folds, wrinkles, bulges, and dimples can occur as a result of the pipe's adverse conditions. We have developed a mobile robotic system equipped with a laser profiler for three-dimensional (3D) mapping of water and wastewater pipeline internal surface defects [9], [10]. However, effective robot localization is required to track the evolution of surface defects over time by comparing 3D pipe maps acquired through robotic laser scans at various times.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Gunatilake¹,

Thiyagarajan²,

Kodagoda³

2021

Preprint

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: System Description and Testbed Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Gunatilake¹,

Thiyagarajan²,

Kodagoda³

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Common defects of liners are folds, bulges, wrinkles, dimples, thickness variations, etc. [9]- [12]. Post-application condition assessment of liners This work was supported by the University of Technology Sydney (UTS) through the Faculty of Engineering and Information Technology (FEIT) Tech Lab Blue Sky Research Grant.…”

Section: Introductionmentioning

confidence: 99%

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

2022

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…Within the task of measuring scalar fields, optimal sensor placement, or computing subsequent best, or subsequent most informative location(s) for sensor placement, is an important question to look at. This question has become especially relevant due to the modern advancements of robotic capabilities available to support sensing tasks [1], including underground measurements [2]- [6]. An approach that is classically used to solve such sensor placement problems is Bayesian Optimization and its extensions [7].…”

Section: Introductionmentioning

confidence: 99%

Gaussian Process As a Benchmark for Optimal Sensor Placement Strategy

Ulapane¹,

Thiyagarajan²,

Kodagoda³

2021

Preprint

Self Cite

View full text Add to dashboard Cite

<div> <div> <div> <p>Optimal sensor placement is an important problem to look at. This problem becomes all the more relevant nowadays due to advancements in infrastructure monitoring robotic technologies including underground sensing. While there are multiple ways to solve optimal sensor placement problems, one of the most generic methods available is Bayesian Optimization and its variants. In this paper, we present a simple benchmark- like formulation for exploiting Gaussian Process uncertainty for sensor placement to measure a scalar field. </p> </div> </div> </div>

show abstract

Stereo Vision Combined With Laser Profiling for Mapping of Pipeline Internal Defects

Cited by 48 publications

References 24 publications

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

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

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

Gaussian Process As a Benchmark for Optimal Sensor Placement Strategy

Contact Info

Product

Resources

About