Novel Online Optimized Control for Underwater Pipe-Cleaning Robots
Due to the particularity of the jacket structure of offshore platforms and the complexity of the marine environment, there have been few effective localization and autonomous control methods for underwater robots that are designed for cleaning tasks. To improve this situation, a fusion bat algorithm...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/12/4279 |
| _version_ | 1827714449817993216 |
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| author | Yanhu Chen Siyue Liu Jinchang Fan Canjun Yang |
| author_facet | Yanhu Chen Siyue Liu Jinchang Fan Canjun Yang |
| author_sort | Yanhu Chen |
| collection | DOAJ |
| description | Due to the particularity of the jacket structure of offshore platforms and the complexity of the marine environment, there have been few effective localization and autonomous control methods for underwater robots that are designed for cleaning tasks. To improve this situation, a fusion bat algorithm (BA) online optimized fuzzy control method using vision localization was developed based on the constraints of the underwater operational environment. Vision localization was achieved based on images from a catadioptric panoramic imaging system. The features of the pipe edge and the boundary of the area covered by biofouling were obtained by image processing and feature extraction. The feature point chosen as the “highest” point of the boundary was calculated by projection transformation to generate the reference path. The specialized fuzzy controller was designed to drive the robot to track the reference path, and an improved bat algorithm with dynamic inertia weight and differential evolution method was developed to optimize the scale factors of the fuzzy controller online. The control method was simulated and further implemented on an underwater pipe-cleaning robot (UPCR), and the results indicate its rationality and validity. |
| first_indexed | 2024-03-10T18:58:52Z |
| format | Article |
| id | doaj.art-fbebff7876364507a9cb0e6dbf5c77fe |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T18:58:52Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-fbebff7876364507a9cb0e6dbf5c77fe2023-11-20T04:37:22ZengMDPI AGApplied Sciences2076-34172020-06-011012427910.3390/app10124279Novel Online Optimized Control for Underwater Pipe-Cleaning RobotsYanhu Chen0Siyue Liu1Jinchang Fan2Canjun Yang3The State Key Laboratory of Fluid Power and Mechatronic systems, Zhejiang University, Hangzhou 310027, ChinaThe State Key Laboratory of Fluid Power and Mechatronic systems, Zhejiang University, Hangzhou 310027, ChinaThe State Key Laboratory of Fluid Power and Mechatronic systems, Zhejiang University, Hangzhou 310027, ChinaThe State Key Laboratory of Fluid Power and Mechatronic systems, Zhejiang University, Hangzhou 310027, ChinaDue to the particularity of the jacket structure of offshore platforms and the complexity of the marine environment, there have been few effective localization and autonomous control methods for underwater robots that are designed for cleaning tasks. To improve this situation, a fusion bat algorithm (BA) online optimized fuzzy control method using vision localization was developed based on the constraints of the underwater operational environment. Vision localization was achieved based on images from a catadioptric panoramic imaging system. The features of the pipe edge and the boundary of the area covered by biofouling were obtained by image processing and feature extraction. The feature point chosen as the “highest” point of the boundary was calculated by projection transformation to generate the reference path. The specialized fuzzy controller was designed to drive the robot to track the reference path, and an improved bat algorithm with dynamic inertia weight and differential evolution method was developed to optimize the scale factors of the fuzzy controller online. The control method was simulated and further implemented on an underwater pipe-cleaning robot (UPCR), and the results indicate its rationality and validity.https://www.mdpi.com/2076-3417/10/12/4279underwater robotautomationvision localizationfuzzy controlbat algorithm |
| spellingShingle | Yanhu Chen Siyue Liu Jinchang Fan Canjun Yang Novel Online Optimized Control for Underwater Pipe-Cleaning Robots Applied Sciences underwater robot automation vision localization fuzzy control bat algorithm |
| title | Novel Online Optimized Control for Underwater Pipe-Cleaning Robots |
| title_full | Novel Online Optimized Control for Underwater Pipe-Cleaning Robots |
| title_fullStr | Novel Online Optimized Control for Underwater Pipe-Cleaning Robots |
| title_full_unstemmed | Novel Online Optimized Control for Underwater Pipe-Cleaning Robots |
| title_short | Novel Online Optimized Control for Underwater Pipe-Cleaning Robots |
| title_sort | novel online optimized control for underwater pipe cleaning robots |
| topic | underwater robot automation vision localization fuzzy control bat algorithm |
| url | https://www.mdpi.com/2076-3417/10/12/4279 |
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