Accelerated LiDAR data processing algorithm for self-driving cars on the heterogeneous computing platform

doi:10.1049/iet-cdt.2019.0166

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Accelerated LiDAR data processing algorithm for self-driving cars on the heterogeneous computing platform
	Li, Wei 2; Liang, Jun 2; Zhang, Yunquan 2; Jia, Haipeng 1; Xiao, Lin 2; Li, Qing 2
刊名	IET COMPUTERS AND DIGITAL TECHNIQUES
	2020-09-01
卷号	14 期号:5 页码:201-209
关键词	feature extraction optical radar optimisation optical information processing traffic engineering computing mobile robots automobiles accelerated LiDAR data processing algorithm self-driving cars heterogeneous computing platform optimisation NVIDIA Tegra X2 computing platform feature extraction obstacle clustering
ISSN号	1751-8601
DOI	10.1049/iet-cdt.2019.0166
英文摘要	In recent years, light detection and ranging (LiDAR) has been widely used in the field of self-driving cars, and the LiDAR data processing algorithm is the core algorithm used for environment perception in self-driving cars. At the same time, the real-time performance of the LiDAR data processing algorithm is highly demanding in self-driving cars. The LiDAR point cloud is characterised by its high density and uneven distribution, which poses a severe challenge in the implementation and optimisation of data processing algorithms. In view of the distribution characteristics of LiDAR data and the characteristics of the data processing algorithm, this study completes the implementation and optimisation of the LiDAR data processing algorithm on an NVIDIA Tegra X2 computing platform and greatly improves the real-time performance of LiDAR data processing algorithms. The experimental results show that compared with an Intel (R) Core (TM) i7 industrial personal computer, the optimised algorithm improves feature extraction by nearly 4.5 times, obstacle clustering by nearly 3.5 times, and the performance of the whole algorithm by 2.3 times.
资助项目	National Natural Science Foundation of China[61502036] ; General Project of Scientific Research Project of the Beijing Education Committee[KM201811417006] ; General Project of Scientific Research Project of the Beijing Education Committee[KM201611417015]
WOS研究方向	Computer Science
语种	英语
出版者	INST ENGINEERING TECHNOLOGY-IET
WOS记录号	WOS:000566558900003
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/15774]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Liang, Jun
作者单位	1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing, Peoples R China 2.Beijing Union Univ, Beijing Key Lab Informat Serv Engn, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Li, Wei,Liang, Jun,Zhang, Yunquan,et al. Accelerated LiDAR data processing algorithm for self-driving cars on the heterogeneous computing platform[J]. IET COMPUTERS AND DIGITAL TECHNIQUES,2020,14(5):201-209.
APA	Li, Wei,Liang, Jun,Zhang, Yunquan,Jia, Haipeng,Xiao, Lin,&Li, Qing.(2020).Accelerated LiDAR data processing algorithm for self-driving cars on the heterogeneous computing platform.IET COMPUTERS AND DIGITAL TECHNIQUES,14(5),201-209.
MLA	Li, Wei,et al."Accelerated LiDAR data processing algorithm for self-driving cars on the heterogeneous computing platform".IET COMPUTERS AND DIGITAL TECHNIQUES 14.5(2020):201-209.