Modeling and Simulation of FLC-based Navigation Algorithm for Small Gas Pipeline Inspection Robot

Zhao, Wen; Kamezaki, Mitsuhiro; Yoshida, Kento; Konno, Minoru; Onuki, Akihiko; Sugano, Shigeki

doi:10.1109/aim.2018.8452416

Cited by 10 publications

(10 citation statements)

References 15 publications

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“…Type-1 FLC, triangular and trapezoidal membership functions, is used to avoid the robot from turning over [113]. Also, [114] used a charge-coupled device (CCD) camera and image processing for locating elbow or junction and navigation using FLC. In [115], a two-mode controller consisting of a proportional-integral-derivative (PID) controller for controlling the actuators and an FLC for setting the output of sensors such as speed, angle of climbing, and the rate of this angle was used.…”

Section: Fuzzy Logic Controllermentioning

confidence: 99%

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Localization, Mapping, Navigation, and Inspection Methods in In-Pipe Robots: A Review

Kazeminasab¹,

Sadeghi

Janfaza

et al. 2021

IEEE Access

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Section: Fuzzy Logic Controllermentioning

confidence: 99%

“… A-KAZE Feature Extraction [169].  Non-straight Configuration Detection [79] [22] [114].  Visual Simultaneous Localization and Mapping (VSLAM) [53].…”

Section: Localization Ultrasonic Sensormentioning

confidence: 99%

Localization, Mapping, Navigation, and Inspection Methods in In-Pipe Robots: A Review

Kazeminasab¹,

Sadeghi

Janfaza

et al. 2021

IEEE Access

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“…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)

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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.

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“…Despite these limitations, common robot sensing has been used in pipes. 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].…”

Section: Introductionmentioning

confidence: 99%

Acoustic Echo Sensing for Robot Localization in Buried Pipe Networks

Worley¹,

Yu²,

Horoshenkov³

et al. 2023

Preprint

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<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>

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Modeling and Simulation of FLC-based Navigation Algorithm for Small Gas Pipeline Inspection Robot

Cited by 10 publications

References 15 publications

Localization, Mapping, Navigation, and Inspection Methods in In-Pipe Robots: A Review

Localization, Mapping, Navigation, and Inspection Methods in In-Pipe Robots: A Review

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

Acoustic Echo Sensing for Robot Localization in Buried Pipe Networks

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