三维激光雷达-相机间外参的高效标定方法
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TP242TH74

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国家重点研发计划(2017YFB1301002)、国家自然科学基金(U1813222)、河北省自然科学基金(E2017202270)项目资助


High efficient extrinsic parameter calibration method of 3D LiDARcamera system
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    摘要:

    在自动驾驶、移动机器人等领域,激光雷达与相机是常用的传感器,融合这两者的信息首先应该标定两者间的外参。本文在考虑平面移动机器人运动特点的基础上提出两阶段外参标定方法,在尽可能少的人为干预下实现快速标定。第一阶段,在机器人运动过程中同时估算激光里程计和视觉里程计,提取平移、旋转两种运动信息以修改的Kabsch算法初步估计外参中的旋转矩阵;第二阶段,以箱体三面相交组成的三面体作为标识物,优化点云中三面体边的投影点和图像中对应三面体边的距离,从而得到精确的外参。此两阶段方法效率高、无需专业设备,在少量人工干预下即可实现外参标定。最后,实验结果表明,在3个坐标轴上的平均误差仅为367、111、078 mm,在典型移动计算平台上相应的平均标定时间仅需约635 ms。

    Abstract:

    3D LiDARs and cameras are commonly used in the fields of autonomous vehicles, mobile robots and etc. To fuse the complementary information of both, extrinsic calibration is the prerequisite and foundation. Based on the motion characteristics of planar mobile robot, a twostage extrinsic parameter calibration method is proposed in this paper, which can quickly calibrate the extrinsic parameters with the manual intervention as little as possible. In the first stage, the LiDAR odometry and visual odometry are simultaneously estimated in the robot motion process. Then with the extracted translations and rotations, a coarse estimation of the relative rotation is found by using modified Kabsch algorithm.In the second stage, the trihedron formed by three planes of a box is utilized as the marker.Precise extrinsic parameters are obtained by optimizing the distances of projections of points on trihedron edges in the point cloud to corresponding trihedron edges in the image. This efficient algorithm features just less manual intervention for the calibration without any specialized equipments.Finally, the experiment results show that the mean errors on three coordinate axes are only 367, 111 and 078 mm, and the corresponding mean calibration time on the typical mobile computing platform is only about 635 ms.

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刘今越,唐旭,贾晓辉,杨冬,李铁军.三维激光雷达-相机间外参的高效标定方法[J].仪器仪表学报,2019,40(11):64-72

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  • 在线发布日期: 2022-01-08
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