基于单目视觉的GPS辅助相机外参数标定  

Calibration of camera extrinsic parameters based on monocular visual with GPS assistant

作　　者：吴修振[1] 刘刚[1] 于凤全 张源原 

机构地区：[1]海军航空工程学院控制工程系,山东烟台264001 [2]海军航空兵学院空中领航系,辽宁葫芦岛125000

出　　处：《光学精密工程》2017年第8期2252-2258,共7页Optics and Precision Engineering

基　　金：国家自然科学基金资助项目(No.61004002)

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。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.

关 键 词：相机标定 外参标定 ORB-SLAM 最小二乘模型 随机采样一致性 LM迭代 

分 类 号：V249.329[航空宇航科学与技术—飞行器设计] TP391[自动化与计算机技术—计算机应用技术]