基于相机空间点约束的机器人工具标定方法

工具标定就是确定工具坐标系相对于机器人末端坐标系的变换矩阵,但传统的解决方案是通过人工示教点约束的方法,为此提出一种基于视觉相机空间的自动工具标定方法。在末端工具上增加特征点如圆环标志,利用相机建立机器人三维空间与相机二维空间之间的关系,通过自动的三维空间视觉定位,实现对圆环标志的中心点的点约束,视觉定位不需要相机的标定等繁琐过程。基于机器人的正运动学和相机空间点约束完成工具中心点(TCP)求解。重复实验的标定误差小于0.05 mm,实验的绝对定位误差小于0.1 mm,验证了基于相机空间定位的工具标定具有较高的可重复性以及可靠性。     

基于参考像面法的CCD摄像机标定新技术

摄像机标定是计算机视觉检测中必不可少的步骤.在现有的摄像机参数标定算法中,纯线性算法标定速度快,但标定精度不是很高;相反如采用非线性搜索算法,标定精度高,但存在标定速度慢以及会出现不收敛现象.通过对现有线性标定算法的研究,提出一种既考虑摄像机的径向和切向畸变,又能实现全线性化求解的全新标定算法--参考像面法.经验证该方法标定速度快、精度较高、算法健壮,适用于大型视觉系统多摄像机的快速标定.     

利用3D打印标定球的机械臂与RGB-D相机手眼标定方法

因为彩色镜头和深度镜头不在同一位置,并且深度图像测量精度差、分辨率低、没有颜色纹理信息,传统的手眼标定方法并不适用于RGB-D相机．本文提出一种利用简单低成本的3D打印球作为标定件对机械臂与RGB-D相机进行手眼标定的方法．本方法只需要测量标定件的3D位置信息,避免使用测量不便、精度稍差的姿态信息．文中给出了该方法的封闭解和迭代优化解．100组仿真结果表明,标定精度与RGB-D相机自身测量精度一致;封闭解不需要机械臂与相机时间同步;迭代优化解的标定精度略有提升,误差最大值和误差方差都很稳定．最后,在7自由度的KUKA ⅡWA机械臂和Kinect相机上做了手眼标定实验,结果与仿真实验一致．总之,本文方法简单可靠,可实现机械臂与RGB-D相机之间的快速部署手眼标定．     

Camera Calibration and Direct Reconstruction from Plane with Brackets

Camera calibration and 3D reconstruction are important issues in computer vision. Two applications of bracket algebra in these two issues are presented in this work. Firstly, a camera calibration method is proposed, which is from only distance ratios of object points. Thanks to the effective computations of brackets, this method does not need to set up any world coordinate system and thus can use the geometric information of irregular objects conveniently. Secondly, we represent the reconstruction solution of plane structure directly from four known control points and give some new and useful error analysis results. The solution based on brackets is concise and short, and the error analysis results can act as a theoretical guidance in practice. Simulations and experiments on real images validate our proposed camera calibration method, direct reconstruction solution and error analysis results. Yihong Wu received her Doctor of Science degree in Geometric Invariants and Applications from MMRC, Institute of Systems Science, Chinese Academy of Sciences, in 2001. From June 2001 to July 2003, she did her postdoctoral research in NLPR, Institute of Automation, Chinese Academy of Sciences. After then, she joined NLPR as an associate professor. Her research interests include polynomial elimination and applications, geometric invariant and applications, automated geometric theorem proving, camera calibration, camera pose determination, and 3D reconstruction etc. Zhanyi Hu received the B.S. Degree in Automation from the North China University of Technology in 1985, the Ph.D. Degree (Docteur d’Etat) in Computer Science from the University of Liege, Belgium, in Jan. 1993. Since 1993, he has been with the Institute of Automation, Chinese Academy of Sciences. From May 1997 to May 1998, he also acted as a visiting scholar of Chinese University of Hong Kong on invitation. Dr. Hu now is a Research Professor of Computer Vision, a member of the Executive Expert Committee of the Chinese National High Technology R&D Program, a deputy editor-in-chief for Chinese Journal of CAD and CG, and an associate editor for Journal of Computer Science and Technology. His current research interests include Camera Calibration, 3D Reconstruction, Feature Extraction, and Vision Guided Robot Navigation etc.     

Development of an innovative low-cost MARG sensors alignment and distortion compensation methodology for 3D scanning applications

Working in the low cost 3D scanner design domain, it would be very interesting to employ the inertial technologies because they could provide objects’ surface spatial data, recording their movements, and asking a very low cost in term of sensor investment. Unfortunately these technologies are characterized by distortion problems that normally do not allow to obtain satisfying measures for being employed for 3D scanning applications.This situation happens when working with Magnetic Angular Rate Gravity (MARG) sensor, on which many reports have been written to describe the methods used to suitably manage the data provided by the sensors in order to obtain an accurate orientation estimation; but only a few address the problem of calibration and distortion compensation. Furthermore, the proposed approaches usually involve both complex sensors models and accurate calibration facilities expensive from the workload, the computational and the economic points of view which compromise their possible employment in low-cost 3D scanning applications.In this paper, a novel approach for MARG sensors heading alignment and distortion compensation is proposed in order to increase the reliability of the information provided by the sensors and improve the process of attitude estimation, in order to get measurement quality level sufficient to be employable in 3D scanning applications.Both the effectivity and the reliability of the proposed approach are validated by some experimental results and the performances are evaluated considering the quality of the outcome provided by the same attitude estimation algorithm processing raw data and compensated data.     

基于OSG和OSDK的无人机标校系统设计及实现

通过对无人机标校过程中遇到的精度不高、稳定性较差、可操作性较低、易受环境因素干扰、专业标校软件缺失等问题进行分析,设计一套包含硬件及软件在内的无人机标校方案,硬件设计包含对机载应答机的指标设计、需求设计及选型,对无人机的指标设计、需求设计及选型,以及配套硬件设备的选型,设计一套可行性高,功能完整的无人机标校软件,设计部分主要包含三部分功能,分别为基于OSG三维建模的标校无人机飞行轨迹生成软件、基于大疆OSDK开发包开发的飞行轨迹导入并启动飞行任务软件、基于远控模块实现机载应答机参数设置的控制软件,并提出无人机标校中的主要技术指标参数,最终形成一套切实可行的无人机标校系统,增加无人机标校的可行性及可靠性,为无人机标校软件的开发及无人机标校实施打下基础。     

基于目标检测的机器人手眼标定方法

智能协作机器人依赖视觉系统感知未知环境中的动态工作空间定位目标,实现机械臂对目标对象的自主抓取回收作业。RGB-D相机可采集场景中的彩色图和深度图,获取视野内任意目标三维点云,辅助智能协作机器人感知周围环境。为获取抓取机器人与RGB-D相机坐标系之间的转换关系,提出基于yolov3目标检测神经网络的机器人手眼标定方法。将3D打印球作为标靶球夹持在机械手末端,使用改进的yolov3目标检测神经网络实时定位标定球的球心,计算机械手末端中心在相机坐标系下的3D位置,同时运用奇异值分解方法求解机器人与相机坐标系转换矩阵的最小二乘解。在6自由度UR5机械臂和Intel RealSense D415深度相机上的实验结果表明,该标定方法无需辅助设备,转换后的空间点位置误差在2 mm以内,能较好满足一般视觉伺服智能机器人的抓取作业要求。     

Analysis of Tsai calibration method using two- and three-dimensional calibration objects

Camera calibration is a fundamental process for both photogrammetric and computer vision. Since the arrival of the direct linear transformation method and its later revisions, new methods have been developed by several authors, such as: Tsai, Heikkilä and Zhang. Most of these have been based on the pinhole model, including distortion correction. Some of these methods, such as Tsai method, allow the use of two different techniques for determining calibration parameters: a non-coplanar calibration technique using three-dimensional (3D) calibration objects, and a coplanar technique that uses two-dimensional (2D) calibration objects. The calibration performed by observing a 3D calibration object has good accuracy, and produces very efficient results; however, the calibration object must be accurate enough and requires an elaborate configuration. In contrast, the use of 2D calibration objects yields less accurate results, is much more flexible, and does not require complex calibration objects that are costly to produce. This article compares these two different calibration procedures from the perspective of stereo measurement. Particular attention was focused on the accuracy of the calculated camera parameters, the reconstruction error in the computer image coordinates and in the world coordinate system and advanced image-processing techniques for subpixel detection during the comparison. The purpose of this work is to establish a basis and selection criteria for choosing one of these techniques for camera calibration, according to the accuracy required in each of the many applications using photogrammetric vision: robot calibration methods, trajectory generation algorithms, articulated measuring arm calibration, and photogrammetric systems.     

高精度标定和效验三维相位轮廓测量系统

为了提高三维相位轮廓测量系统的测量精度,提出了一种系统标定的理论模型,并且实验验证了其正确性。为了进一步验证系统精度,使用空间上随机放置的1个和2个轴承滚珠,通过对滚珠的测量和分析,验证了标定方法的有效性。这种三维相位轮廓测量系统的标定和效验方法为它的应用提供了新的技术方案。     

基于PnP问题求解的摄像机标定

三维人脸识别中,双目成象系统是初始工作中极为关键的一步.本文引入了PnP问题讨论双目成象系统中摄像机的标定算法.本文提出解出P4P问题的唯一解,即确定摄像机的标定,该方法简单快捷.最后本文给出具体标定过程.     

A study on automatic on-machine inspection system for 3D modeling and measurement of cutting tools

A 3D model of the maximum rotating envelope of a milling cutter with tool holder is required for Computer Aided Manufacturing (CAM) process design and machining simulation. The user may define the 3D model of the whole tool assembly in the tool library of CAM software. However, it is not convenient and reliable. Considering these problems, a new method based on single view 3D reconstruction algorithm has been proposed in previous research work, which is able to quickly reconstruct the 3D model of a cutter with tool holder while they are installed onto the spindle. As the extension of this work, this paper focuses on the recent progresses in order to improve the automation, accuracy, efficiency and reliability of tool modeling system. First, an improved flexible on-machine camera calibration procedure is proposed. The accurate motion of machine tool axis is used to calibrate the camera on machine tool instead of a physical calibration board. The whole procedure of calibration can be conducted automatically by running NC code. Therefore, the automation of vision system can be guaranteed. Second, the contour extraction module is improved by using a method of silhouette image composition. This method is applied to solve the problem of translucent and fuzzy cutter profile induced by motion blur. Third, the new algorithm for contour partitioning and classification are proposed, which is more reliable and robust. The reliability and accuracy of the vision system can be guaranteed. Finally, the vision system with an 8 mm lens and 1 mm extensions has been tested on different type of machine tool with smaller cutters. The average measurement accuracy is about 35 microns verified by comparison with a commercial tool setting system.     

基于双闭环结构的时栅转台自动标定系统设计

时栅转台精度的标定是时栅产业化过程中非常重要的一道工序,是时栅转台精度和可靠性体现。针对传统的标定系统采用激光干涉仪、光电自准直仪和金属多面体,人工操作效率低,可靠性差,提出用自制的数控控制箱结合嵌入式技术,开发了一种时栅转台自动标定系统。该系统以高精度的海德汉圆光栅RCN8510作为基准量仪,双微控制器与上位机为基础,形成双闭环控制结构,实现了实时在线误差修正与补偿。实验结果表明：采用双闭环控制系统时栅转台标定系统具有较高的稳定性,提高了时栅转台标定效率,时栅转台的精度达到2.4″。     

Segment Based Camera Calibration

The basic idea of calibrating a camera system in previous approaches is to determine camera parmeters by using a set of known 3D points as calibration reference.In this paper,we present a method of camera calibration in whih camera parameters are determined by a set of 3D lines.A set of constraints is derived on camea parameters in terms of perspective line mapping.Form these constraints,the same perspective transformation matrix as that for point mapping can be computed linearly.The minimum number of calibration lines is 6.This result generalizes that of Liu,Huang and Faugeras^[12] for camera location determination in which at least 8 line correspondences are required for linear computation of camera location.Since line segments in an image can be located easily and more accurately than points,the use of lines as calibration reference tends to ease the computation in inage preprocessing and to improve calibration accuracy.Experimental results on the calibration along with stereo reconstruction are reported.     

Revisiting Zhang's 1D calibration algorithm

In recent years, the camera calibration using 1D patterns has been studied and improved by researchers all over the world. However, the progress in that area has been mainly in the sense of reducing the restrictions to the 1D pattern movement. On the other hand, the method's accuracy still demands improvements. In the present paper, the original technique proposed by Zhang is revisited and we demonstrate that the method's accuracy can be significantly improved, simply by analyzing and reformulating the problem. The numerical conditioning can be improved if a simple data normalization is performed. Furthermore, a non-linear solution based on the Partitioned Levenberg-Marquardt algorithm is proposed. That solution takes advantage of the problem's particular structure to reduce the computational complexity of the original method and to improve the accuracy. Tests using both synthetic and real images demonstrate that the calibration method using 1D patterns can be applied in practice, with accuracy comparable to other already traditional methods.     

Constraints on general motions for camera calibration with one-dimensional objects

This paper focuses on two problems in camera calibration with one-dimensional (1D) objects: (a) to find out the general motion patterns well suited for solving the calibration problem, and (b) to improve the robustness and accuracy of the method. Firstly, a sufficient and necessary condition for the solvability of 1D calibration with general motions is proved. Then the special motion of tossing a 1D object is provided as an example to illustrate the correctness and feasibility of this condition. After that some practical issues on obtaining the solution are inspected. By avoiding singularities, the precision and robustness of the method are improved: the relative mean errors are reduced to less than 5% at the noise level of one pixel which surpasses the state-of-the-art methods of the same category.     

一种基于BP神经网络的扭矩传感器静态校准系统

常用的扭矩传感器校准装置大多为卧式串联结构,存在着结构刚度差、校准效率低、误差来源复杂等缺点。设计了一种立式筒状扭矩传感器校准系统,该系统有着形变量小、稳定性好、可靠性高的优点。在这种校准系统中,待校准扭矩传感器通过止口定位并采用螺钉固定,可以实现快速更换和校准。根据系统安装的同轴度、连接装置的情况等对误差来源进行了分析。由于校准时同轴度等参数无法测量,通过训练神经网络获得底部高精度扭矩传感器和待校准扭矩传感器所测扭矩之间的关系。实验结果表明,本文所设计扭矩传感器静态校准系统可以实现扭矩传感器的校准,精度可以达到0.05%FS。     

Quantifying the impact of uncertainty in embedded systems mapping for NoC based architectures

We describe a modeling framework to capture and account for uncertainty in design parameters in embedded systems. We then develop an uncertainty-aware solution to the problem of mapping in embedded systems that uses Network-on-Chip (NoC) based architecture platforms. The problem of mapping is formulated as a multi-objective - reliability, performance, and energy consumption - optimization problem. To solve this problem, we propose a solution based on the NSGA-II genetic algorithm and Monte Carlo simulation techniques. The solution is implemented as a computer-aid design tool that can generate robust 3D Pareto frontiers in the solution space formed by the design objectives of reliability, performance, and energy consumption. Comparison to several state-of-the-art models and solutions for the mapping problem, indicate that significant differences in the actual values of the design attribute of interest exist when one considers uncertainty in design parameters. For example, in the case of mapping with reliability as the only objective, 10% uncertainty in design parameters can lead to a 10.06% difference in MTTF estimation. In the case of mapping with execution time and energy consumption as objectives, the difference in 2D Pareto frontiers due to 10% uncertainty in design parameters can be up to 7.9%. These differences are important because they can mislead the overall optimization process of mapping toward suboptimal solution points. The DESUU-NOC tool that implements the proposed multi-objective mapping algorithm has as a main feature and contribution of this paper the ability to generate 3D Pareto frontiers comprised of robust solution points.     

Camera calibration with one-dimensional objects

Camera calibration has been studied extensively in computer vision and photogrammetry and the proposed techniques in the literature include those using 3D apparatus (two or three planes orthogonal to each other or a plane undergoing a pure translation, etc.), 2D objects (planar patterns undergoing unknown motions), and 0D features (self-calibration using unknown scene points). Yet, this paper proposes a new calibration technique using 1D objects (points aligned on a line), thus filling the missing dimension in calibration. In particular, we show that camera calibration is not possible with free-moving 1D objects, but can be solved if one point is fixed. A closed-form solution is developed if six or more observations of such a 1D object are made. For higher accuracy, a nonlinear technique based on the maximum likelihood criterion is then used to refine the estimate. Singularities have also been studied. Besides the theoretical aspect, the proposed technique is also important in practice especially when calibrating multiple cameras mounted apart from each other, where the calibration objects are required to be visible simultaneously.     

基于平面棋盘格标定板的三维空间标定新方法

在总结分析国内外摄像机标定技术研究的基础上,针对体育科研中使用三维立体 框架进行摄像机标定在标定范围、误差、便携性及时效性等方面存在的不足,提出了使用平面 棋盘格标定板进行三维空间标定的新方法。选取了5 m、10 m 和30 m 的拍摄距离,标定参照 物选用传统三维辐射式立体框架和自制二维平面棋盘格标定板,对标准1 m 长度的比例尺进行 三维重建,对两种标定方法进行了精度比较。此外还对标准1 m 板在测量空间的不同位置（测 量画面中间、边缘）进行了误差分布分析。实验结果表明,基于平面棋盘格标定板的摄像机空 间标定方法具有一定的优势,不论从使用方便性还是测量精度方面都克服了三维立体框架在使 用中的不足,理论上能够满足体育科研的需求。     

Film and television industry cloud exhibition design based on 3D imaging and virtual reality

The three-dimensional virtual scene can provide users with a visual three-dimensional virtual environment, with various multimedia channels such as sound, video, force feedback equipment, etc., to bring users a completely immersive interactive experience. This paper introduces 3D imaging and virtual reality technology in the film and television industry cloud exhibition, and develops a virtual display platform. First of all, this paper divides the registration into two processes: camera calibration and joint calibration of the camera and laser scanner based on the calibration results. Camera calibration can determine the plane model of the calibration board in the camera coordinate system, and the joint calibration uses the RANSAC algorithm to extract the point cloud of the plane model of the calibration board, and then optimizes the distance between the points in the plane model point cloud and the corresponding plane in the camera coordinate system Find the optimal transformation between the two sets of data, and then calculate the registration relationship between the point cloud and the image. Secondly, this article conducts a demand analysis of the film and television industry cloud exhibition platform based on virtual reality technology, including the business goals set by the platform, platform system analysis, overall design, and system operating environment and configuration requirements. This model provides a feasible solution for the visual interaction of the cloud exhibition design of the film and television industry.