题名 | Search-Based Online Trajectory Planning for Car-Like Robots in Highly Dynamic Environments |
作者 | |
通讯作者 | Max Q.-H. Meng |
DOI | |
发表日期 | 2021
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会议名称 | IEEE International Conference on Robotics and Automation
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ISSN | 1050-4729
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EISSN | 2577-087X
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ISBN | 978-1-7281-9078-5
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会议录名称 | |
卷号 | 2021-May
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页码 | 8151-8157
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会议日期 | 2021.5.31-2021.6.4
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会议地点 | Xi'an, China
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出版地 | 345 E 47TH ST, NEW YORK, NY 10017 USA
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出版者 | |
摘要 | This paper presents a search-based partial motion planner for generating feasible trajectories of car-like robots in highly dynamic environments. The planner searches for smooth, safe, and near-time-optimal trajectories by exploring a state graph built on motion primitives. To enable fast online planning, we propose an efficient path searching algorithm based on the aggregation and pruning of motion primitives. We then propose a fast collision checking algorithm that takes into account the motions of moving obstacles. The algorithm linearizes relative motions between the robot and obstacles, and then checks collisions by calculating a point-line distance. Benefiting from the fast searching and collision checking algorithms, the planner can effectively explore the state-time space to generate near-time-optimal solutions. Experiments show that the proposed method can generate feasible trajectories within milliseconds while maintaining a higher success rate than up-to-date methods, which significantly demonstrates its advantages. |
关键词 | |
学校署名 | 通讯
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语种 | 英语
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相关链接 | [来源记录] |
收录类别 | |
资助项目 | Hong Kong RGC GRF[14200618]
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WOS研究方向 | Automation & Control Systems
; Robotics
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WOS类目 | Automation & Control Systems
; Robotics
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WOS记录号 | WOS:000771405401096
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EI入藏号 | 20220911738589
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EI主题词 | Automobiles
; Motion planning
; Robot programming
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EI分类号 | Automobiles:662.1
; Computer Programming:723.1
; Robotics:731.5
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来源库 | 人工提交
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全文链接 | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9560852 |
引用统计 |
被引频次[WOS]:10
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成果类型 | 会议论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/257578 |
专题 | 南方科技大学 工学院_电子与电气工程系 |
作者单位 | 1.The Chinese University of Hong Kong 2.Southern University of Science and Technology, Shenzhen, China 3.Shenzhen Research Institute of the Chinese University of Hong Kong, Shenzhen, China |
通讯作者单位 | 南方科技大学 |
推荐引用方式 GB/T 7714 |
Jiahui Lin,Tong Zhou,Delong Zhu,et al. Search-Based Online Trajectory Planning for Car-Like Robots in Highly Dynamic Environments[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2021:8151-8157.
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条目包含的文件 | 条目无相关文件。 |
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