Fast Bidirectional Motion Planning for Self-Driving General N-Trailers Vehicle Maneuvering in Narrow Space
Self-driving General N-trailers (GNT) vehicles are one of the future solutions to build intelligent factory due to its flexibility and large load. Maneuvering of GNT vehicle to its destination requires accurate and robust motion planning. But the narrow operating environment causes nonlinear nonconv...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Open Journal of Intelligent Transportation Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10347483/ |
| _version_ | 1797372182529048576 |
|---|---|
| author | Hanyang Zhuang Qiyue Shen Yeqiang Qian Wei Yuan Chunxiang Wang Ming Yang |
| author_facet | Hanyang Zhuang Qiyue Shen Yeqiang Qian Wei Yuan Chunxiang Wang Ming Yang |
| author_sort | Hanyang Zhuang |
| collection | DOAJ |
| description | Self-driving General N-trailers (GNT) vehicles are one of the future solutions to build intelligent factory due to its flexibility and large load. Maneuvering of GNT vehicle to its destination requires accurate and robust motion planning. But the narrow operating environment causes nonlinear nonconvex constraints which are challenging. Furthermore, the nonholonomic constraints in GNT kinematics elevate the complexity in state space. Therefore, motion planning of GNT vehicle maneuvering in narrow space within a reasonable time and high success rate is a critical problem. This paper proposes a fast bidirectional motion planning algorithm to generate trajectories for GNT vehicles to maneuver in a narrow space. A coarse-to-fine motion planning paradigm has been proposed to balance the robustness and time. In the coarse step, an initial guess is generated through a bidirectional-sampled closed-loop Rapidly-exploring Random Tree, and a spatial-temporal safety corridor has been constructed to convert nonlinear nonconvex constraints to linear convex constraints. In the fine step, an optimal control problem is defined accordingly and solved to obtain feasible trajectory. Four different scenarios have been conducted with forward and reverse GNT vehicle maneuvering in a narrow environment. The results show that the proposed method outperforms state-of-the-art sampling-based and optimization-based motion planning methods. |
| first_indexed | 2024-03-08T18:32:11Z |
| format | Article |
| id | doaj.art-da0159cf9edf4f8e86be207b53a2dc28 |
| institution | Directory Open Access Journal |
| issn | 2687-7813 |
| language | English |
| last_indexed | 2024-03-08T18:32:11Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Intelligent Transportation Systems |
| spelling | doaj.art-da0159cf9edf4f8e86be207b53a2dc282023-12-30T00:04:46ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132023-01-01498999910.1109/OJITS.2023.334017410347483Fast Bidirectional Motion Planning for Self-Driving General N-Trailers Vehicle Maneuvering in Narrow SpaceHanyang Zhuang0https://orcid.org/0000-0001-6668-9523Qiyue Shen1Yeqiang Qian2https://orcid.org/0000-0003-0831-8702Wei Yuan3https://orcid.org/0000-0003-4880-844XChunxiang Wang4https://orcid.org/0000-0002-6885-6740Ming Yang5https://orcid.org/0000-0002-8679-9137University of Michigan – Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Automation, Shanghai Jiao Tong University, Shanghai, ChinaUniversity of Michigan – Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, ChinaUniversity of Michigan – Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Automation, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Automation, Shanghai Jiao Tong University, Shanghai, ChinaSelf-driving General N-trailers (GNT) vehicles are one of the future solutions to build intelligent factory due to its flexibility and large load. Maneuvering of GNT vehicle to its destination requires accurate and robust motion planning. But the narrow operating environment causes nonlinear nonconvex constraints which are challenging. Furthermore, the nonholonomic constraints in GNT kinematics elevate the complexity in state space. Therefore, motion planning of GNT vehicle maneuvering in narrow space within a reasonable time and high success rate is a critical problem. This paper proposes a fast bidirectional motion planning algorithm to generate trajectories for GNT vehicles to maneuver in a narrow space. A coarse-to-fine motion planning paradigm has been proposed to balance the robustness and time. In the coarse step, an initial guess is generated through a bidirectional-sampled closed-loop Rapidly-exploring Random Tree, and a spatial-temporal safety corridor has been constructed to convert nonlinear nonconvex constraints to linear convex constraints. In the fine step, an optimal control problem is defined accordingly and solved to obtain feasible trajectory. Four different scenarios have been conducted with forward and reverse GNT vehicle maneuvering in a narrow environment. The results show that the proposed method outperforms state-of-the-art sampling-based and optimization-based motion planning methods.https://ieeexplore.ieee.org/document/10347483/Intelligent transportation systemtractor-trailermotion planninglogistics |
| spellingShingle | Hanyang Zhuang Qiyue Shen Yeqiang Qian Wei Yuan Chunxiang Wang Ming Yang Fast Bidirectional Motion Planning for Self-Driving General N-Trailers Vehicle Maneuvering in Narrow Space IEEE Open Journal of Intelligent Transportation Systems Intelligent transportation system tractor-trailer motion planning logistics |
| title | Fast Bidirectional Motion Planning for Self-Driving General N-Trailers Vehicle Maneuvering in Narrow Space |
| title_full | Fast Bidirectional Motion Planning for Self-Driving General N-Trailers Vehicle Maneuvering in Narrow Space |
| title_fullStr | Fast Bidirectional Motion Planning for Self-Driving General N-Trailers Vehicle Maneuvering in Narrow Space |
| title_full_unstemmed | Fast Bidirectional Motion Planning for Self-Driving General N-Trailers Vehicle Maneuvering in Narrow Space |
| title_short | Fast Bidirectional Motion Planning for Self-Driving General N-Trailers Vehicle Maneuvering in Narrow Space |
| title_sort | fast bidirectional motion planning for self driving general n trailers vehicle maneuvering in narrow space |
| topic | Intelligent transportation system tractor-trailer motion planning logistics |
| url | https://ieeexplore.ieee.org/document/10347483/ |
| work_keys_str_mv | AT hanyangzhuang fastbidirectionalmotionplanningforselfdrivinggeneralntrailersvehiclemaneuveringinnarrowspace AT qiyueshen fastbidirectionalmotionplanningforselfdrivinggeneralntrailersvehiclemaneuveringinnarrowspace AT yeqiangqian fastbidirectionalmotionplanningforselfdrivinggeneralntrailersvehiclemaneuveringinnarrowspace AT weiyuan fastbidirectionalmotionplanningforselfdrivinggeneralntrailersvehiclemaneuveringinnarrowspace AT chunxiangwang fastbidirectionalmotionplanningforselfdrivinggeneralntrailersvehiclemaneuveringinnarrowspace AT mingyang fastbidirectionalmotionplanningforselfdrivinggeneralntrailersvehiclemaneuveringinnarrowspace |