汽车工程 ›› 2022, Vol. 44 ›› Issue (2): 215-224.doi: 10.19562/j.chinasae.qcgc.2022.02.008

所属专题: 智能网联汽车技术专题-感知&HMI&测评2022年

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自动驾驶多传感器融合的时间校准方法研究

张晶威1,3,刘铁军1,2,3,李仁刚1,3,刘丹1,3(),詹景麟1,3,阚宏伟1,2,3   

  1. 1.浪潮集团有限公司,高效能服务器与存储技术国家重点实验室,北京  100085
    2.广东浪潮智慧计算技术有限公司,广州  510627
    3.浪潮(北京)电子信息产业有限公司,北京  100085
  • 收稿日期:2021-10-27 修回日期:2021-12-08 出版日期:2022-02-25 发布日期:2022-02-24
  • 通讯作者: 刘丹 E-mail:bj_liudan@163.com
  • 基金资助:
    广东省重点研发计划(2033811500013)

A Temporal Calibration Method for Multi-Sensor Fusion of Autonomous Vehicles

Jingwei Zhang1,3,Tiejun Liu1,2,3,Rengang Li1,3,Dan Liu1,3(),Jinglin Zhan1,3,Hongwei Kan1,2,3   

  1. 1.Laboratory of High-End Server & Storage Technology,Inspur Group Co. ,Ltd. ,Beijing  100085
    2.Guangdong Inspur Intelligent Computing Technology Co. ,Ltd,Guangzhou  510627
    3.Inspur (Beijing) Electronic Information Industry Co. ,Ltd. ,Beijing  100085
  • Received:2021-10-27 Revised:2021-12-08 Online:2022-02-25 Published:2022-02-24
  • Contact: Dan Liu E-mail:bj_liudan@163.com

摘要:

针对自动驾驶感知域系统的激光雷达、图像传感器、惯性测量单元3种传感器数据融合的时基校准问题,利用机械式激光雷达自身特征设计校准设备、系统及实验方法。基于激光雷达的触发事件和车载图像传感器感知特征,实现两种传感器时基在线标定,并通过示波器测量校验证明该方法的有效性。利用激光雷达扫描频率与触发事件时间差相互关联的特征,将激光雷达与惯性测量单元的标定系统结合,对激光雷达与惯性测量单元时基进行标定,并通过惯性测量单元标定实验证明方法有效性。

关键词: 自动驾驶, 传感器融合, 时间校准

Abstract:

For the temporal calibration of data fusion of Lidar, image sensor and inertial measurement unit (IMU) in the perception system of autonomous vehicles, the calibration equipment, system and test method are designed by using the characteristics of Lidar. Based on the trigger case of Lidar and the sensing characteristics of on-board image sensor, the on-line temporal calibration of the two sensors is realized, and the effectiveness of this method is verified by oscilloscope measurement. Based on the correlation between Lidar scanning frequency and trigger case time difference, the time base of Lidar and inertial measurement unit is calibrated by combining the calibration system of Lidar and inertial measurement unit, and the effectiveness of the method is proved by the inertial measurement unit calibration test.

Key words: autonomous vehicles, multi-sensor fusion, temporal calibration