基于图优化的多相机系统高精度自主定位方法
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摘要
多相机系统的自主定位技术是通过多个相机对空间中的特征点进行观测而恢复出系统自身的空间位姿,借助多相机的大视场克服复杂现场环境影响,提高测量精度。针对多相机系统结构复杂、位姿恢复难度大、耗时长的问题,提出一种使用基于图优化模型的自主定位方法。在求解高效透视n点定位问题得到近似估计位姿的基础上,借助图优化框架对多相机系统与空间控制点的观测问题进行建模,进而将位姿恢复问题等价为最小化重投影误差非线性优化问题。借助近景摄影三坐标测量系统(VSTARS)搭建的控制场和直线导轨搭建的多相机系统,测量和模拟实验结果表明,该方法具有较高的测量精度和较快的运行速度。
The autonomous positioning technology of a multi-camera system can restore the spatial position and pose of the system by using the multiple cameras to observe the feature points in space,which can overcome the influence of the complicated environment and improve the precision of measurement by using the large field of view of multiple cameras.Aiming at the problem of the complex structure of a multi-camera system,posture recovery is rather difficult and time-consuming,a self-positioning method based on the graphic optimization model is proposed.On the basis of solving the efficient perspective-n-point-positioning problem to obtain the approximate position and pose of a multi-camera system,agraph optimization framework is used to model the observation problem of the multi-camera system and the spatial control points.Thus,the problem of the position and pose recovery is equivalent to the problem of the minimization reprojection error nonlinear optimization.Using a control field build by a video-simultaneous triangulation and resection system(VSTARS)and a multi-camera system build by a linear guideway,the results of the measurement and simulation experiment show that this method possesses a high measurement accuracy and a fast running speed.
The autonomous positioning technology of a multi-camera system can restore the spatial position and pose of the system by using the multiple cameras to observe the feature points in space,which can overcome the influence of the complicated environment and improve the precision of measurement by using the large field of view of multiple cameras.Aiming at the problem of the complex structure of a multi-camera system,posture recovery is rather difficult and time-consuming,a self-positioning method based on the graphic optimization model is proposed.On the basis of solving the efficient perspective-n-point-positioning problem to obtain the approximate position and pose of a multi-camera system,agraph optimization framework is used to model the observation problem of the multi-camera system and the spatial control points.Thus,the problem of the position and pose recovery is equivalent to the problem of the minimization reprojection error nonlinear optimization.Using a control field build by a video-simultaneous triangulation and resection system(VSTARS)and a multi-camera system build by a linear guideway,the results of the measurement and simulation experiment show that this method possesses a high measurement accuracy and a fast running speed.
引文
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[15]Zhang N,Chang L,Xu X P.Research on thetechnology of three-dimensional reconstruction basedon machine vision[J].Laser &OptoelectronicsProgress,2012,49(5):051001.张宁,常雷,徐熙平.基于机器视觉的三维重建技术研究[J].激光与光电子学进展,2012,49(5):051001.
[16]Huang G P, Qin G Q,Lu C J. Testing andapplication of the digital close-range photogrammetryfor the large scale 3D measurement V-STARS[J].Journal of Astronautic Metrology and Measurement,2009,29(2):5-9,22.黄桂平,钦桂勤,卢成静.数字近景摄影大尺寸三坐标测量系统V-STARS的测试与应用[J].宇航计测技术,2009,29(2):5-9,22.
[2]Liu K.An overview of indoor vision positioning andnavigation[J].Heilongjiang Science and TechnologyInformation,2017(8):7.刘康.室内视觉定位与导航综述[J].黑龙江科技信息,2017(8):7.
[3]Qu L,Wang K R,Chen L L,et al.Fast roaddetection based on RGBD images and convolutionalneural network[J].Acta Optica Sinica,2017,37(10):1010003.曲磊,王康如,陈利利,等.基于RGBD图像和卷积神经网络的快速道路检测[J].光学学报,2017,37(10):1010003.
[4]Chen P,Wang C X.IEPnP:an iterative camera poseestimation algorithm based on EPnP[J].Acta OpticaSinica,2018,38(4):0411001.陈鹏,王晨骁.IEPnP:一种基于EPnP的相机位姿迭代估计算法[J].光学学报,2018,38(4):0411001.
[5]Shi S D,Yang L H,Lin J R,et al.Omnidirectionalangle constraint based dynamic six-degree-of-freedommeasurement for spacecraft rendezvous and dockingsimulation[J]. Measurement Science andTechnology,2017,29(4):045005.
[6]Zhao T Y,Guo L,Zhang L C.A new algorithm ofspatial positioning based on mono-vision[J].Journalof Northwestern Polytechnical University,2009,27(1):47-51.赵天云,郭雷,张利川.基于单目视觉的空间定位算法[J].西北工业大学学报,2009,27(1):47-51.
[7]Di H W,Chai Y,Li K.A fast binocular vision stereomatching algorithm[J].Acta Optica Sinica,2009,29(8):2180-2184.狄红卫,柴颖,李逵.一种快速双目视觉立体匹配算法[J].光学学报,2009,29(8):2180-2184.
[8]Urban S,Wursthorn S,Leitloff J,et al.Multicolbundle adjustment:a generic method for poseestimation, simultaneous self-calibration andreconstruction for arbitrary multi-camera systems[J].International Journal of Computer Vision,2017,121(2):234-252.
[9]Zhu H J,Xu X B,Zhou J L.Fisheye image matchingbased on rotation matrix under spherical perspectiveprojection[J].Acta Optica Sinica,2013,33(2):0215001.祝海江,徐晓波,周靖林.基于球面透视投影旋转矩阵的鱼眼图像匹配[J].光学学报,2013,33(2):0215001.
[10]Cui C G,Yang X F.Interior penalty rule basedevolutionary algorithm for constrained optimization[J].Journal of Software,2015,26(7):1688-1699.崔承刚,杨晓飞.基于内部罚函数的进化算法求解约束优化问题[J].软件学报,2015,26(7):1688-1699.
[11]Liang M J, Min H Q,Luo R H.Graph-basedSLAM:a survey[J].Robot,2013,35(4):500-512.梁明杰,闵华清,罗荣华.基于图优化的同时定位与地图创建综述[J].机器人,2013,35(4):500-512.
[12]Zhu J G,Yu Z J.The principles and methods ofvisual measurement[M].Beijing:China MachinePress,2012:78-94.邾继贵,于之靖.视觉测量原理与方法[M].北京:机械工业出版社,2012:78-94.
[13]Lu F,Milios E E.Optimal global pose estimation forconsistent sensor data registration[C]∥Proceedingsof 1995IEEE International Conference on Roboticsand Automation,1995,1:93-100.
[14]Gao X,Zhang T,et al.Visual SLAM fourteenlectures:from theory to practice[M].Beijing:Electronic Industry Press,2017:245-269.高翔,张涛,等.视觉SLAM十四讲:从理论到实践[M].北京:电子工业出版社,2017:245-269.
[15]Zhang N,Chang L,Xu X P.Research on thetechnology of three-dimensional reconstruction basedon machine vision[J].Laser &OptoelectronicsProgress,2012,49(5):051001.张宁,常雷,徐熙平.基于机器视觉的三维重建技术研究[J].激光与光电子学进展,2012,49(5):051001.
[16]Huang G P, Qin G Q,Lu C J. Testing andapplication of the digital close-range photogrammetryfor the large scale 3D measurement V-STARS[J].Journal of Astronautic Metrology and Measurement,2009,29(2):5-9,22.黄桂平,钦桂勤,卢成静.数字近景摄影大尺寸三坐标测量系统V-STARS的测试与应用[J].宇航计测技术,2009,29(2):5-9,22.
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