Route planning of mobile robot based on improved RRT star and TEB algorithm
Abstract This paper presents a fusion algorithm based on the enhanced RRT* TEB algorithm. The enhanced RRT* algorithm is utilized for generating an optimal global path. Firstly, proposing an adaptive sampling function and extending node bias to accelerate global path generation and mitigate local op...
| Hlavní autoři: | , , , , |
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| Médium: | Článek |
| Jazyk: | English |
| Vydáno: |
Nature Portfolio
2024-04-01
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| Edice: | Scientific Reports |
| Témata: | |
| On-line přístup: | https://doi.org/10.1038/s41598-024-59413-9 |
| _version_ | 1827277160231993344 |
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| author | Xiong Yin Wentao Dong Xiaoming Wang Yongxiang Yu Daojin Yao |
| author_facet | Xiong Yin Wentao Dong Xiaoming Wang Yongxiang Yu Daojin Yao |
| author_sort | Xiong Yin |
| collection | DOAJ |
| description | Abstract This paper presents a fusion algorithm based on the enhanced RRT* TEB algorithm. The enhanced RRT* algorithm is utilized for generating an optimal global path. Firstly, proposing an adaptive sampling function and extending node bias to accelerate global path generation and mitigate local optimality. Secondly, eliminating path redundancy to minimize path length. Thirdly, imposing constraints on the turning angle of the path to enhance path smoothness. Conducting kinematic modeling of the mobile robot and optimizing the TEB algorithm to align the trajectory with the mobile robot's kinematics. The integration of these two algorithms culminates in the development of a fusion algorithm. Simulation and experimental results demonstrate that, in contrast to the traditional RRT* algorithm, the enhanced RRT* algorithm achieves a 5.8% reduction in path length and a 62.5% decrease in the number of turning points. Utilizing the fusion algorithm for path planning, the mobile robot generates a superior, seamlessly smooth global path, adept at circumventing obstacles. Furthermore, the local trajectory meticulously conforms to the kinematic constraints of the mobile robot. |
| first_indexed | 2024-04-24T07:16:16Z |
| format | Article |
| id | doaj.art-6613eb2e6b8b49bead0bd67522a6b44d |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-24T07:16:16Z |
| publishDate | 2024-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-6613eb2e6b8b49bead0bd67522a6b44d2024-04-21T11:17:37ZengNature PortfolioScientific Reports2045-23222024-04-0114111410.1038/s41598-024-59413-9Route planning of mobile robot based on improved RRT star and TEB algorithmXiong Yin0Wentao Dong1Xiaoming Wang2Yongxiang Yu3Daojin Yao4School of Electrical and Automation Engineering, East China Jiaotong UniversitySchool of Electrical and Automation Engineering, East China Jiaotong UniversitySchool of Electrical and Automation Engineering, East China Jiaotong UniversitySchool of Electrical and Automation Engineering, East China Jiaotong UniversitySchool of Electrical and Automation Engineering, East China Jiaotong UniversityAbstract This paper presents a fusion algorithm based on the enhanced RRT* TEB algorithm. The enhanced RRT* algorithm is utilized for generating an optimal global path. Firstly, proposing an adaptive sampling function and extending node bias to accelerate global path generation and mitigate local optimality. Secondly, eliminating path redundancy to minimize path length. Thirdly, imposing constraints on the turning angle of the path to enhance path smoothness. Conducting kinematic modeling of the mobile robot and optimizing the TEB algorithm to align the trajectory with the mobile robot's kinematics. The integration of these two algorithms culminates in the development of a fusion algorithm. Simulation and experimental results demonstrate that, in contrast to the traditional RRT* algorithm, the enhanced RRT* algorithm achieves a 5.8% reduction in path length and a 62.5% decrease in the number of turning points. Utilizing the fusion algorithm for path planning, the mobile robot generates a superior, seamlessly smooth global path, adept at circumventing obstacles. Furthermore, the local trajectory meticulously conforms to the kinematic constraints of the mobile robot.https://doi.org/10.1038/s41598-024-59413-9RRT* algorithmTEB algorithmPath planningAGVKinematic |
| spellingShingle | Xiong Yin Wentao Dong Xiaoming Wang Yongxiang Yu Daojin Yao Route planning of mobile robot based on improved RRT star and TEB algorithm Scientific Reports RRT* algorithm TEB algorithm Path planning AGV Kinematic |
| title | Route planning of mobile robot based on improved RRT star and TEB algorithm |
| title_full | Route planning of mobile robot based on improved RRT star and TEB algorithm |
| title_fullStr | Route planning of mobile robot based on improved RRT star and TEB algorithm |
| title_full_unstemmed | Route planning of mobile robot based on improved RRT star and TEB algorithm |
| title_short | Route planning of mobile robot based on improved RRT star and TEB algorithm |
| title_sort | route planning of mobile robot based on improved rrt star and teb algorithm |
| topic | RRT* algorithm TEB algorithm Path planning AGV Kinematic |
| url | https://doi.org/10.1038/s41598-024-59413-9 |
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