Micro-Inertial-Aided High-Precision Positioning Method for Small-Diameter PIG Navigation

Guan, Lei; Xu, Xu; Gao, Yanbin; Liu, Fanming; Rong, Hanxiao; Wang, Meng; Noureldin, Aboelmagd

doi:10.5772/intechopen.80343

Cited by 8 publications

(8 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, a binary measurement z t is made, equal to L if the robot detects that it is in a link, and equal to N if it detects that it is at a node. This kind of measurement can be made using visual [21], [22], [23], [24], [25], acoustic [26], [4], or inertial [27], [28] sensing, as has been demonstrated in previous work. This binary measurement contains no other information about the link or node it has detected, and represents the minimal measurement of this type that could be made.…”

Section: Motion and Measurement Definitionmentioning

confidence: 99%

Robust Efficient Localization of Robots in Pipe Networks using a Particle Filter for Hybrid Metric-Topological Space

Worley

Anderson

2021

2021 European Conference on Mobile Robots (ECMR)

View full text Add to dashboard Cite

Water distribution and drainage pipe inspection and maintenance is costly, and could be improved by using robots to locate faults from within the pipes. Robot localization is critical in this operation, but is challenging due to the constraints of the pipe environment. An efficient, robust algorithm is needed for localization using limited sensors. A novel particle filter algorithm is proposed for localization, which estimates the robot's position in a hybrid metric-topological state space, allowing efficient computation and relocalization. The algorithm is demonstrated in simulation at a large scale, considering substantial uncertainty in motion, measurements, and the map of the environment, showing an improvement over a benchmark algorithm developed for this application.

show abstract

Section: Motion and Measurement Definitionmentioning

confidence: 99%

Robust Efficient Localization of Robots in Pipe Networks using a Particle Filter for Hybrid Metric-Topological Space

Worley

Anderson

2021

2021 European Conference on Mobile Robots (ECMR)

View full text Add to dashboard Cite

show abstract

“…To improve the surveying precision of the intelligent PIG and avoid the problems of the non-inertial-based PIG surveying technology, the inertial sensors are the best choice to remedy these problems [ 61 ]. The inertial base intelligent PIG surveying technology was originally developed by Hanna P.L.…”

Section: Pig Surveying Technologiesmentioning

confidence: 99%

A Comprehensive Review of Micro-Inertial Measurement Unit Based Intelligent PIG Multi-Sensor Fusion Technologies for Small-Diameter Pipeline Surveying

et al. 2020

Self Cite

View full text Add to dashboard Cite

It is of great importance for pipeline systems to be is efficient, cost-effective and safe during the transportation of the liquids and gases. However, underground pipelines often experience leaks due to corrosion, human destruction or theft, long-term Earth movement, natural disasters and so on. Leakage or explosion of the operating pipeline usually cause great economical loss, environmental pollution or even a threat to citizens, especially when these accidents occur in human-concentrated urban areas. Therefore, the surveying of the routed pipeline is of vital importance for the Pipeline Integrated Management (PIM). In this paper, a comprehensive review of the Micro-Inertial Measurement Unit (MIMU)-based intelligent Pipeline Inspection Gauge (PIG) multi-sensor fusion technologies for the transport of liquids and gases purposed for small-diameter pipeline (D<30cm) surveying is demonstrated. Firstly, four types of typical small-diameter intelligent PIGs and their corresponding pipeline-defects inspection technologies and defects-positioning technologies are investigated according to the various pipeline defects inspection and localization principles. Secondly, the multi-sensor fused pipeline surveying technologies are classified into two main categories, the non-inertial-based and the MIMU-based intelligent PIG surveying technology. Moreover, five schematic diagrams of the MIMU fused intelligent PIG fusion technology is also surveyed and analyzed with details. Thirdly, the potential research directions and challenges of the popular intelligent PIG surveying techniques by multi-sensor fusion system are further presented with details. Finally, the review is comprehensively concluded and demonstrated.

show abstract

“…Vision has been used for odometry and mapping [5] and for detecting features such as corners and junctions using shadows [6], [7], light [8], projected laser arrays [9], and depth images [10]. These features can also be detected with inertial sensing [11], [12] and scanning rangefinders [13]. While effective, cameras and rangefinders in the pipe environment can only observe nearby features so loop-closure measurements will be infrequent.…”

Section: Introductionmentioning

confidence: 99%

Acoustic Echo Sensing for Robot Localization in Buried Pipe Networks

Worley¹,

Yu²,

Horoshenkov³

et al. 2023

Preprint

View full text Add to dashboard Cite

<p>The abstract of this pre-print paper is: Robot localization in buried pipes presents a number of challenges, including the unavailability of methods such as a global positioning system, and the limited perspective of sensors such as vision. This paper addresses these challenges by using acoustic sensing, where signals sent by robots propagate long distances and around corners in the pipe environment, and can be used to estimate the distance to reflective features. It is shown that the reverberant environment causes a number of echoes which contain useful information. A novel algorithm for using this information in pose-graph optimization is proposed, and is shown to be necessary in comparison to a naive approach. The algorithm is demonstrated to be accurate and robust by measuring the error rate, which is the proportion of estimate error that was greater than a target threshold of 0.5 metres. The median error rate was 0 for measurement uncertainty 2.5 times larger than that found experimentally, and for motion uncertainty 4 times that which could be tolerated by an idealised loop-closure approach used for comparison. This work is the foundation for new data fusion methods for robot localization in buried pipes.</p>

show abstract

Micro-Inertial-Aided High-Precision Positioning Method for Small-Diameter PIG Navigation

Cited by 8 publications

References 17 publications

Robust Efficient Localization of Robots in Pipe Networks using a Particle Filter for Hybrid Metric-Topological Space

Robust Efficient Localization of Robots in Pipe Networks using a Particle Filter for Hybrid Metric-Topological Space

A Comprehensive Review of Micro-Inertial Measurement Unit Based Intelligent PIG Multi-Sensor Fusion Technologies for Small-Diameter Pipeline Surveying

Acoustic Echo Sensing for Robot Localization in Buried Pipe Networks

Contact Info

Product

Resources

About