Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot
A row-following system based on machine vision for a picking robot was designed in our previous study. However, the visual perception could not provide reliable information during headland turning according to the test results. A complete navigation system for a picking robot working in an orchard n...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/9/5/103 |
| _version_ | 1827692291091857408 |
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| author | Peichen Huang Lixue Zhu Zhigang Zhang Chenyu Yang |
| author_facet | Peichen Huang Lixue Zhu Zhigang Zhang Chenyu Yang |
| author_sort | Peichen Huang |
| collection | DOAJ |
| description | A row-following system based on machine vision for a picking robot was designed in our previous study. However, the visual perception could not provide reliable information during headland turning according to the test results. A complete navigation system for a picking robot working in an orchard needs to support accurate row following and headland turning. To fill this gap, a headland turning method for an autonomous picking robot was developed in this paper. Three steps were executed during headland turning. First, row end was detected based on machine vision. Second, the deviation was further reduced before turning using the designed fast posture adjustment algorithm based on satellite information. Third, a curve path tracking controller was developed for turning control. During the MATLAB simulation and experimental test, different controllers were developed and compared with the designed method. The results show that the designed turning method enabled the robot to converge to the path more quickly and remain on the path with lower radial errors, which eventually led to reductions in time, space, and deviation during headland turning. |
| first_indexed | 2024-03-10T11:19:16Z |
| format | Article |
| id | doaj.art-a1265c05f2e343b9b3b514d579bdf877 |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-10T11:19:16Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-a1265c05f2e343b9b3b514d579bdf8772023-11-21T20:11:58ZengMDPI AGMachines2075-17022021-05-019510310.3390/machines9050103Row End Detection and Headland Turning Control for an Autonomous Banana-Picking RobotPeichen Huang0Lixue Zhu1Zhigang Zhang2Chenyu Yang3College of Automation, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, ChinaCollege of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, ChinaKey Laboratory of Key Technology on Agricultural Machine and Equipment, Ministry of Education, South China Agricultural University, Guangzhou 510642, ChinaCollege of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, ChinaA row-following system based on machine vision for a picking robot was designed in our previous study. However, the visual perception could not provide reliable information during headland turning according to the test results. A complete navigation system for a picking robot working in an orchard needs to support accurate row following and headland turning. To fill this gap, a headland turning method for an autonomous picking robot was developed in this paper. Three steps were executed during headland turning. First, row end was detected based on machine vision. Second, the deviation was further reduced before turning using the designed fast posture adjustment algorithm based on satellite information. Third, a curve path tracking controller was developed for turning control. During the MATLAB simulation and experimental test, different controllers were developed and compared with the designed method. The results show that the designed turning method enabled the robot to converge to the path more quickly and remain on the path with lower radial errors, which eventually led to reductions in time, space, and deviation during headland turning.https://www.mdpi.com/2075-1702/9/5/103row end detectionturning controlheadlandpicking robot |
| spellingShingle | Peichen Huang Lixue Zhu Zhigang Zhang Chenyu Yang Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot Machines row end detection turning control headland picking robot |
| title | Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot |
| title_full | Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot |
| title_fullStr | Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot |
| title_full_unstemmed | Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot |
| title_short | Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot |
| title_sort | row end detection and headland turning control for an autonomous banana picking robot |
| topic | row end detection turning control headland picking robot |
| url | https://www.mdpi.com/2075-1702/9/5/103 |
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