Accelerated LiDAR data processing algorithm for self-driving cars on the heterogeneous computing platform | |
Li, Wei2; Liang, Jun2; Zhang, Yunquan2; Jia, Haipeng1; Xiao, Lin2; Li, Qing2 | |
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. |
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