Time Synchronization and Space Registration of Roadside LiDAR and Camera

被引:5
|
作者
Wang, Chuan [1 ]
Liu, Shijie [2 ,3 ]
Wang, Xiaoyan [4 ]
Lan, Xiaowei [3 ,5 ]
机构
[1] Shandong High Speed Grp Co Ltd, Jinan 250098, Peoples R China
[2] Shandong Univ, Sch Microelect, Jinan 250101, Peoples R China
[3] Shandong Univ, Suzhou Res Inst, Suzhou 215000, Peoples R China
[4] Shandong Acad Transportat Sci, Jinan 250357, Peoples R China
[5] Lanzhou Jiaotong Univ, Sch Transportat, Lanzhou 730070, Peoples R China
基金
中国国家自然科学基金;
关键词
camera; frequency self-matching; joint calibration; LiDAR; space synchronization; CALIBRATION;
D O I
10.3390/electronics12030537
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The sensing system consisting of Light Detection and Ranging (LiDAR) and a camera provides complementary information about the surrounding environment. To take full advantage of multi-source data provided by different sensors, an accurate fusion of multi-source sensor information is needed. Time synchronization and space registration are the key technologies that affect the fusion accuracy of multi-source sensors. Due to the difference in data acquisition frequency and deviation in startup time between LiDAR and the camera, asynchronous data acquisition between LiDAR and camera is easy to occur, which has a significant influence on subsequent data fusion. Therefore, a time synchronization method of multi-source sensors based on frequency self-matching is developed in this paper. Without changing the sensor frequency, the sensor data are processed to obtain the same number of data frames and set the same ID number, so that the LiDAR and camera data correspond one by one. Finally, data frames are merged into new data packets to realize time synchronization between LiDAR and camera. Based on time synchronization, to achieve spatial synchronization, a nonlinear optimization algorithm of joint calibration parameters is used, which can effectively reduce the reprojection error in the process of sensor spatial registration. The accuracy of the proposed time synchronization method is 99.86% and the space registration accuracy is 99.79%, which is better than the calibration method of the Matlab calibration toolbox.
引用
收藏
页数:14
相关论文
共 50 条
  • [11] PSNet: LiDAR and Camera Registration Using Parallel Subnetworks
    Wu, Yi
    Zhu, Ming
    Liang, Ji
    IEEE ACCESS, 2022, 10 : 70553 - 70561
  • [12] A Transformer Approach for Camera-to-LIDAR Data Registration
    Wang, Ju
    Tang, Yong
    Dasari, Venkat R.
    Geerhart, Billy
    Rapp, Brian
    Wang, Peng
    Chen, Wei-Bang
    Watts, Isaac
    2024 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION FOR DATA SCIENCE, IRI 2024, 2024, : 326 - 330
  • [13] Automatic Calibration and Registration of Lidar and Stereo Camera without Calibration Objects
    John, Vijay
    Long, Qian
    Liu, Zheng
    Mita, Seiichi
    2015 IEEE INTERNATIONAL CONFERENCE ON VEHICULAR ELECTRONICS AND SAFETY (ICVES), 2015, : 231 - 237
  • [14] CFNet: LiDAR-Camera Registration Using Calibration Flow Network
    Lv, Xudong
    Wang, Shuo
    Ye, Dong
    SENSORS, 2021, 21 (23)
  • [15] Sensor Fusion and Registration of Lidar and Stereo Camera without Calibration Objects
    John, Vijay
    Long, Qian
    Xu, Yuquan
    Liu, Zheng
    Mita, Seiichi
    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2017, E100A (02) : 499 - 509
  • [16] Real-Time Queue Length Detection with Roadside LiDAR Data
    Wu, Jianqing
    Xu, Hao
    Zhang, Yongsheng
    Tian, Yuan
    Song, Xiuguang
    SENSORS, 2020, 20 (08)
  • [17] Enhancing Aerial Camera-LiDAR Registration through Combined LiDAR Feature Layers and Graph Neural Networks
    Leahy, Jennifer
    Jabari, Shabnam
    45TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOL XLVIII-M-4, CSRS 2024, 2024, : 25 - 31
  • [18] Real-Time Point Cloud Clustering Algorithm Based on Roadside LiDAR
    Wu, Jianqing
    Zhuang, Xucai
    Tian, Yuan
    Cheng, Zhiheng
    Liu, Shijie
    IEEE SENSORS JOURNAL, 2024, 24 (07) : 10608 - 10619
  • [19] Parallel Registration and Time Synchronization Algorithm for Radar system
    Wu Zemin
    Lei, Zhang
    Ren Shujie
    2010 6TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS NETWORKING AND MOBILE COMPUTING (WICOM), 2010,
  • [20] Improve Radar Sensing Performance of Multiple Roadside Units Cooperation via Space Registration
    Jiang, Wangjun
    Wei, Zhiqing
    Li, Bin
    Feng, Zhiyong
    Fang, Zixi
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (10) : 10975 - 10990