中文版 | English
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
会议名称
IEEE International Conference on Robotics and Automation
ISSN
1050-4729
EISSN
2577-087X
ISBN
978-1-7281-9078-5
会议录名称
卷号
2021-May
页码
8151-8157
会议日期
2021.5.31-2021.6.4
会议地点
Xi'an, China
出版地
345 E 47TH ST, NEW YORK, NY 10017 USA
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
语种
英语
相关链接[来源记录]
收录类别
资助项目
Hong Kong RGC GRF[14200618]
WOS研究方向
Automation & Control Systems ; Robotics
WOS类目
Automation & Control Systems ; Robotics
WOS记录号
WOS:000771405401096
EI入藏号
20220911738589
EI主题词
Automobiles ; Motion planning ; Robot programming
EI分类号
Automobiles:662.1 ; Computer Programming:723.1 ; Robotics:731.5
来源库
人工提交
全文链接https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9560852
引用统计
被引频次[WOS]:10
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.
条目包含的文件
条目无相关文件。
个性服务
原文链接
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
导出为Excel格式
导出为Csv格式
Altmetrics Score
谷歌学术
谷歌学术中相似的文章
[Jiahui Lin]的文章
[Tong Zhou]的文章
[Delong Zhu]的文章
百度学术
百度学术中相似的文章
[Jiahui Lin]的文章
[Tong Zhou]的文章
[Delong Zhu]的文章
必应学术
必应学术中相似的文章
[Jiahui Lin]的文章
[Tong Zhou]的文章
[Delong Zhu]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
[发表评论/异议/意见]
暂无评论

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。