An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation
Abstract The use of rubber-tapping robots capable of autonomous navigation in place of manual rubber-tapping is a growing trend, but the challenging multi-objective navigation task in forest environments impedes their autonomous operation. To tackle this issue, an autonomous navigation system with a...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-11-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-81084-9 |
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| _version_ | 1850216566214361088 |
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| author | Xirui Zhang Yongqi Liu Junxiao Liu Xuanli Chen Ruiwu Xu Weiqiang Ma Zhifu Zhang Shaohua Fu |
| author_facet | Xirui Zhang Yongqi Liu Junxiao Liu Xuanli Chen Ruiwu Xu Weiqiang Ma Zhifu Zhang Shaohua Fu |
| author_sort | Xirui Zhang |
| collection | DOAJ |
| description | Abstract The use of rubber-tapping robots capable of autonomous navigation in place of manual rubber-tapping is a growing trend, but the challenging multi-objective navigation task in forest environments impedes their autonomous operation. To tackle this issue, an autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation is designed. This navigation decision mechanism is comprised of obtaining coordinates of target points (OCTP), selecting the next coordinate (SNC), generating the additional coordinates (GAC), and optimizing the planned paths (OPP). By utilizing this mechanism, the robot can autonomously select the next target point based on its current position and the actual operating logic while navigating in the forest areas, adding additional coordinates during row or column changes, and planning and optimizing the path. The on-site experiments demonstrate that during autonomous navigation, the positioning accuracy is favorable and supports subsequent operations. The overall rationality of the planned path reaches 92.14%, further confirming its effectiveness. |
| format | Article |
| id | doaj-art-c127d1eb6b53430abb09575fea1d80f0 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-c127d1eb6b53430abb09575fea1d80f02025-08-20T02:08:15ZengNature PortfolioScientific Reports2045-23222024-11-0114111910.1038/s41598-024-81084-9An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigationXirui Zhang0Yongqi Liu1Junxiao Liu2Xuanli Chen3Ruiwu Xu4Weiqiang Ma5Zhifu Zhang6Shaohua Fu7School of Mechanical and Electrical Engineering, Hainan UniversitySchool of Mechanical and Electrical Engineering, Hainan UniversitySchool of Mechanical and Electrical Engineering, Hainan UniversitySchool of Mechanical and Electrical Engineering, Hainan UniversitySchool of Information and Communication Engineering, Hainan UniversitySchool of Mechanical and Electrical Engineering, Hainan UniversitySchool of Mechanical and Electrical Engineering, Hainan UniversitySchool of Information and Communication Engineering, Hainan UniversityAbstract The use of rubber-tapping robots capable of autonomous navigation in place of manual rubber-tapping is a growing trend, but the challenging multi-objective navigation task in forest environments impedes their autonomous operation. To tackle this issue, an autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation is designed. This navigation decision mechanism is comprised of obtaining coordinates of target points (OCTP), selecting the next coordinate (SNC), generating the additional coordinates (GAC), and optimizing the planned paths (OPP). By utilizing this mechanism, the robot can autonomously select the next target point based on its current position and the actual operating logic while navigating in the forest areas, adding additional coordinates during row or column changes, and planning and optimizing the path. The on-site experiments demonstrate that during autonomous navigation, the positioning accuracy is favorable and supports subsequent operations. The overall rationality of the planned path reaches 92.14%, further confirming its effectiveness.https://doi.org/10.1038/s41598-024-81084-9Rubber-tapping robotAutonomous navigation systemMulti-objective navigationNavigation decision mechanism |
| spellingShingle | Xirui Zhang Yongqi Liu Junxiao Liu Xuanli Chen Ruiwu Xu Weiqiang Ma Zhifu Zhang Shaohua Fu An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation Scientific Reports Rubber-tapping robot Autonomous navigation system Multi-objective navigation Navigation decision mechanism |
| title | An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation |
| title_full | An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation |
| title_fullStr | An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation |
| title_full_unstemmed | An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation |
| title_short | An autonomous navigation system with a trajectory prediction-based decision mechanism for rubber forest navigation |
| title_sort | autonomous navigation system with a trajectory prediction based decision mechanism for rubber forest navigation |
| topic | Rubber-tapping robot Autonomous navigation system Multi-objective navigation Navigation decision mechanism |
| url | https://doi.org/10.1038/s41598-024-81084-9 |
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