中文摘要：

针对机器人视觉系统外参数标定的问题，提出了基于单目视觉ORB-SLAM的差分GPS辅助相机外参数标定方法。分析了单目视觉ORB-SLAM和GPS（Global Position System）定位数据之间的相似关系，建立了相机外参数标定的非线性最小二乘模型。基于随机采样一致性（RANSAC），通过三点法求得模型的初始解。设计了Levenberg Marquardt（LM）迭代算法求解出最优解，从而得到了最优的相机相对位置和姿态参数。最后，对提出的方法进行仿真和跑车试验验证。结果表明：在试验半径为50m时，所设计标定方法的姿态标定精度可达0．1°，位置标定精度可达0．2％。该方法标定过程简单实用，不需要外界环境的先验信息和人工干预，具有很高的精度和显著的应用价值。

英文摘要：

An extrinsic parameter calibration method with differential GPS（Global Position System） assistant based on monocular visual ORB-SLAM（ORB-Simullaneous Location and Mapping） was pro- posed aimed at extrinsic parameter calibration problem of a robot vision system. Nonlinear least square models of extrinsic parameter calibration were established based on analyzing the similarity re- lationship between monocular visual ORB-SLAM and GPS positioning data. The initial solution of model was obtained by three-point method based on Random Sample Consensus （RANSAC）, and then an optimal solution was obtained by designing Levenberg-Marquardt （LM） iterative algorithm. Thus optimal relative position and pose parameters of a camera were obtained. Simulation and traffic-run- ning experimental verification was performed for proposed methods. The result indicates that when experimental radius was 50 m,the pose calibration precision of designed calibration method could reach O. 1° and position calibration precision could reach O. 2 ~. It concludes that the calibration process of the method is simple and practical. It does not need prior information of external environment and manual intervention, and has high precision and a significant application value.