Abstract
Pipeline robot are widely used since pipelines require to be inspected regularly for leakages caused by natural disaster, etc. Most robots which rely heavily on manual operation are incapable of self-navigation in pipe. Moreover incorrect operations would degrade the efficiency, and sometimes damage the robots especially when they pass through elbows or junctions. Some robots can realize navigation based on multi-sensor such as position sensitive detector and laser sensor, but navigation performance for such robots will be greatly influenced by the performance of these sensors, and space to install large number of sensors is limited. In this study, we propose an approach of pipeline robot's navigation based on fuzzy logic control (FLC) algorithm for passing through elbows or T-junctions. A CCD camera installed on the robot is used for locating region of interest (ROI) in elbow or junction. Moreover, ROIs formed by reflection of robot's LED light and edge of pipe's dark hole are considered as input variables in the FLC system. By analyzing system outputs, we can control the robot's speed and yaw angle in real time. Compared with conventional studies on pipeline robot's navigation method, the proposed method can be more precise and faster by using FLC algorithm and analyzing ROI with fewer sensors. Finally, we conducted a simulation validation, and the results showed that the robot was capable of adapting to known pipe environments and realizing navigation in straight part, elbow, and junction of pipe.
| Original language | English |
|---|---|
| Title of host publication | AIM 2018 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 912-917 |
| Number of pages | 6 |
| Volume | 2018-July |
| ISBN (Print) | 9781538618547 |
| DOIs | |
| Publication status | Published - 2018 Aug 30 |
| Event | 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2018 - Auckland, New Zealand Duration: 2018 Jul 9 → 2018 Jul 12 |
Other
| Other | 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2018 |
|---|---|
| Country | New Zealand |
| City | Auckland |
| Period | 18/7/9 → 18/7/12 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Computer Science Applications
- Software
Cite this
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.
AIM 2018 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Vol. 2018-July Institute of Electrical and Electronics Engineers Inc., 2018. p. 912-917 8452416.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Modeling and simulation of FLC-based navigation algorithm for small gas pipeline inspection robot
AU - Zhao, Wen
AU - Kamezaki, Mitsuhiro
AU - Yoshida, Kento
AU - Konno, Minoru
AU - Onuki, Akihiko
AU - Sugano, Shigeki
PY - 2018/8/30
Y1 - 2018/8/30
N2 - Pipeline robot are widely used since pipelines require to be inspected regularly for leakages caused by natural disaster, etc. Most robots which rely heavily on manual operation are incapable of self-navigation in pipe. Moreover incorrect operations would degrade the efficiency, and sometimes damage the robots especially when they pass through elbows or junctions. Some robots can realize navigation based on multi-sensor such as position sensitive detector and laser sensor, but navigation performance for such robots will be greatly influenced by the performance of these sensors, and space to install large number of sensors is limited. In this study, we propose an approach of pipeline robot's navigation based on fuzzy logic control (FLC) algorithm for passing through elbows or T-junctions. A CCD camera installed on the robot is used for locating region of interest (ROI) in elbow or junction. Moreover, ROIs formed by reflection of robot's LED light and edge of pipe's dark hole are considered as input variables in the FLC system. By analyzing system outputs, we can control the robot's speed and yaw angle in real time. Compared with conventional studies on pipeline robot's navigation method, the proposed method can be more precise and faster by using FLC algorithm and analyzing ROI with fewer sensors. Finally, we conducted a simulation validation, and the results showed that the robot was capable of adapting to known pipe environments and realizing navigation in straight part, elbow, and junction of pipe.
AB - Pipeline robot are widely used since pipelines require to be inspected regularly for leakages caused by natural disaster, etc. Most robots which rely heavily on manual operation are incapable of self-navigation in pipe. Moreover incorrect operations would degrade the efficiency, and sometimes damage the robots especially when they pass through elbows or junctions. Some robots can realize navigation based on multi-sensor such as position sensitive detector and laser sensor, but navigation performance for such robots will be greatly influenced by the performance of these sensors, and space to install large number of sensors is limited. In this study, we propose an approach of pipeline robot's navigation based on fuzzy logic control (FLC) algorithm for passing through elbows or T-junctions. A CCD camera installed on the robot is used for locating region of interest (ROI) in elbow or junction. Moreover, ROIs formed by reflection of robot's LED light and edge of pipe's dark hole are considered as input variables in the FLC system. By analyzing system outputs, we can control the robot's speed and yaw angle in real time. Compared with conventional studies on pipeline robot's navigation method, the proposed method can be more precise and faster by using FLC algorithm and analyzing ROI with fewer sensors. Finally, we conducted a simulation validation, and the results showed that the robot was capable of adapting to known pipe environments and realizing navigation in straight part, elbow, and junction of pipe.
UR - http://www.scopus.com/inward/record.url?scp=85053876786&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85053876786&partnerID=8YFLogxK
U2 - 10.1109/AIM.2018.8452416
DO - 10.1109/AIM.2018.8452416
M3 - Conference contribution
SN - 9781538618547
VL - 2018-July
SP - 912
EP - 917
BT - AIM 2018 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics
PB - Institute of Electrical and Electronics Engineers Inc.
ER -