基于交叉矢量的视觉-激光测距系统结构参数标定
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TP242 TP391 TH74

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上海市科技兴农项目(202202080012F01164)、中国博士后科学基金(2021M702078)项目资助


Structural parameter calibration of the Cam-LiDAR system based on cross vector
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    摘要:

    视觉与三维激光测距组成的测量系统是运动估计与环境建模的主要传感设备。 为了实现测量系统感知数据坐标系的 统一,提出了一种基于空间向量自组合的视觉与三维激光测距系统结构参数标定方法。 主要包括 3 个方面:1)利用平面标定法 求解摄像机内部参数及摄像机坐标系下平面靶标的法向量,利用迭代拟合算法求解激光雷达坐标系下平面靶标的法向量,并构 建两个坐标系下的平面靶标法向量集合;2)根据向量之间夹角大小在平面靶标法向量集合中自主选取交叉向量,建立结构参 数标定目标函数;3)利用非线性优化算法求解最小二乘问题,获得外部参数的最优估计。 通过仿真与实际标定实验验证了方法 的有效性和准确性。 实验结果表明:该方法的反向投影误差小于 30 mm(3σ),满足高精度三维测量的同时还具有高的标定效 率。 所提方法满足传感器融合测量精度的要求。

    Abstract:

    The measurement system consisted of vision and 3D laser ranging is the main sensing device for motion estimation and environment modeling. To realize the unification of the sensing data coordinate system of the measurement system, a method for calibrating the structural parameters of the vision and 3D laser ranging system based on the self-combination of space vectors is proposed in this article. It mainly includes three aspects: 1) The plane calibration method is used to solve the internal parameters of the camera and the normal vector of the plane target in the camera coordinate system and the plane iterative fitting algorithm is utilized to solve the normal vector of the plane target in the LiDAR coordinate system. The plane target normal vector set is established under two coordinate systems. 2) According to the angle between the vectors, the cross vector is independently selected in the plane target normal vector combination, and the structural parameter calibration parameters are established to solve the objective function, and the calibration objective function of structure parameters is established. 3) The nonlinear optimization algorithm is used to solve the least-squares problem and obtain the optimal estimation of external parameters. The effectiveness and accuracy of the method are evaluated by simulation and actual calibration experiments. Results show that the error between the image object-side projection and the 3D point cloud of this method is less than 30 mm (3σ), which not only satisfies high-precision 3D measurement but also has a high calibration efficiency. It meets the requirements of accurate measurement of sensor fusion measurement.

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李云辉,修贤超,苗中华,崔家山.基于交叉矢量的视觉-激光测距系统结构参数标定[J].仪器仪表学报,2022,43(10):185-194

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  • 在线发布日期: 2023-02-06
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