MOTOMAN-SV3XL机器人手眼视觉立体定位系统

分析了基于恒定旋转矩阵的机器人视觉立体定位方法原理,提出利用机器人控制命令参数直接获取恒定旋矩阵的方法,该方法大大简化了摄像机内外参数的标定过程。设计了MOTOMAN-SV3XL机器人手眼视觉控制系统,制了相应的控制软件,进行了大量的实验研究,并取得了良好的效果。     

Integrated remote control of the process capability and the accuracy of vision calibration

This study aims at jointly controlling two critical process parameters from a remote site, of which include the process capability of robotic assembly operations and the accuracy of vision calibration. The process capability is regarded as the indication of robot positioning accuracy. When the robot is driven by the vision camera, the process capability becomes mainly dependent on the calibration accuracy of vision-guided robot system. Even though newly commissioned, high precision assembly robots typically display excellent positioning accuracies under normal working conditions, the imperfect mathematical conversion of vision coordinates into robot coordinates imparts the accuracy problems. In this study, a novel vision calibration method is proposed that effectively rectifies the inherent complications associated with lens distortions. Our analysis shows that the degree of lens distortion appears very differently along the vision field of view. Because of this non-uniform distortion, a single mathematical equation for vision calibration is deemed ineffective. The proposed methodology significantly improves the positioning accuracy, which can be performed over the network from a remote site. This is better suited for today?s global manufacturing companies, where fast product cycles and geographically distributed production lines dictate more efficient and effective quality control strategies.     

Camera calibration issues in robot calibration with eye-on-hand configuration

One of the possible methods for accurate, fast, low-cost and automated robot calibration is to employ a single camera rigidly mounted to the robot end-effector together with a single camera calibration board. The end-effector pose is measured by calibration of the camera at every robot measurement configuration. This paper contends that, with several modifications, Tsai's radial alignment constraint (RAC) camera calibration method can be made a fast and sufficiently accurate pose measurement technique. This paper focuses on speed, accuracy and cost enhancement of RAC-based camera calibration. A fast RAC-based algorithm is proposed, which cuts the computation time of Tsai's original algorithm by about a 5: 1 ratio while keeping its accuracy within the tolerances required for a successful robot calibration. A low-cost method for estimation of the ratio of scale factors of the camera/vision system is also proposed. This method does not require a precision vertical micrometer stage to provide non-coplanar calibration points data for camera calibration. Finally, the phenomenon of perspective projection distortion of circular camera calibration points is fully analyzed and error compensation methods are proposed.     

基于眼固定安装方式的机器人定位系统

研发了基于眼固定安装方式的机器人定位系统,提出了一种方便有效的手眼标定方法。通过最小二乘法求解手眼坐标的变换关系,再根据工作台平面与摄像机成像模型的约束关系,求解出目标物体的三维位姿,并最终实现了机械手的精确定位。     

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。     

室内移动机器人视觉里程计研究

研究了一种精度较高的视觉里程计实现方法。首先采用计算量小、精度高的SURF算法提取特征点,并采用最近邻向量匹配法进行特征点匹配;采用RANSAC算法求得帧间摄像机坐标系的转换矩阵;提出了一种视觉里程计标定方法,并通过该方法得到机器人起始点坐标系下的位移信息,保证了机器人有自身姿态变化时的定位的准确性;圆轨迹实验验证了视觉里程计算法的可行性。     

基于多视定位算法的多摄像机标定

针对多摄像机系统标定,提出一种基于多视定位算法的标定方法,标定过程只需一块可自由移动的平面模板即可,利用约束优化思想,将各摄像机坐标系转换到参考摄像机坐标系下,从而得到摄像机之间相对位置关系。标定操作过程简单,易于实现。实验结果表明,该方法是一种有效的多摄像机标定方法。     

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。     

Virtual manipulator-based binocular stereo vision positioning system and errors modelling

There is a bottleneck of mobile robots positioning technologies for uncertain goals in complex field environment. Owing to the disturbance of the environment, the objects are hard to be located precisely by robot manipulator. Aiming at the positioning problem, binocular stereo vision system and positioning principle of the picking manipulator in virtual environment (VE) were proposed and expatiated upon; in addition, the manipulator positioning model was built in VE, and the manipulator positioning simulation system was developed by Microsoft Visual C++ 6.0; and the binocular stereo vision system platform with a three-coordinate guideway positioning was constructed for test; what’s more the error sources of vision positioning system was analyzed, and the camera system error was established; the mathematical model of experimental error and the camera calibration matching error were also found; with the developed robot manipulator positioning simulation software and vision system hardware, an experimental platform of positioning system was constructed, and using the platform, the stereo vision data was mapped to the manipulator and was guiding the accurate positioning in VE. Finally, experiment of positioning error compensation was carried out. Results of simulation in VE and the experiment showed that the vision positioning method was feasible for positioning in the field environment; it can be applied to control robot operation and to correct the positioning errors in real-time, especially to the long-range precision modelling and error compensation of robots.     

足球机器人全局视觉系统的快速标定方法

针对足球机器人全局视觉系统的特殊应用场景,提出了一种基于两步法简化标定模型的快速有效标定算法。利用近似欧拉角旋转矩阵建立摄像机标定模型,确定需要求取的摄像机内外参数,借助场地上现有的一些标志点作为靶标,对模型的相关参数进行分步求取初始值,并利用L-M优化算法对摄像机内外参数进行分步优化求取精确值。通过实验分别从标定误差和机器人动作实现效率两个方面与其他标定算法进行对比,验证了该算法具有较高的标定精度。实验表明,本算法的优点在于不用借助专门的标定靶标,即可快速有效完成相机标定,标定精度可达1mm,且标定过程简单易实现。     

结构光视觉引导的焊接机器人系统自标定技术

为实现结构光视觉引导的焊接机器人系统的标定,解决现有标定方法复杂,标定靶标制作要求高等缺点,提出一种基于主动视觉的自标定方法。该标定方法对场景中3个特征点取像,通过精确控制焊接机器人进行5次平移运动,标定摄像机内参数和手眼矩阵旋转部分;通过进行2次带旋转运动,结合激光条在特征点平面的参数方程,标定手眼矩阵平移部分和结构光平面在摄像机坐标系下的平面方程;并针对不同焊枪长度进行修正。在以Denso机器人为主体构建的结构光视觉引导的焊接机器人系统上的测试结果稳定,定位精度可达到±0.93 mm。该标定方法简单,特征选取容易,对焊接机器人系统在实际工业现场的使用有重要意义。     

Development of a monocular vision system for robotic drilling

Robotic drilling for aerospace structures demands a high positioning accuracy of the robot, which is usually achieved through error measurement and compensation. In this paper, we report the development of a practical monocular vision system for measurement of the relative error between the drill tool center point （TCP） and the reference hole. First, the principle of relative error measurement with the vision system is explained, followed by a detailed discussion on the hardware components, software components, and system integration. The elliptical contour extraction algorithm is presented for accurate and robust reference hole detection. System calibration is of key importance to the measurement accuracy of a vision system. A new method is proposed for the simultaneous calibration of camera internal parameters and hand-eye relationship with a dedicated calibration board. Extensive measurement experiments have been performed on a robotic drilling system. Experimental results show that the measurement accuracy of the developed vision system is higher than 0.15 mm, which meets the requirement of robotic drilling for aircraft structures.     

一种基于拟全方位视觉的移动机器人自运动融合估计方法

基于地平面假设的移动机器人单路视觉运动估计存在鲁棒性和环境适应性较差、精度较低等缺 点,针对这一问题,本文首先介绍了拟全方位视觉系统的构成,并结合该视觉系统的特点给出了一种基于两 步运动的摄像头平行位姿参数标定方法．然后据此提出了一种基于拟全方位视觉的自主移动机器人自运动融 合估计方法．该方法能够借助机器人的非完整运动约束、地平面运行假设以及运动估计参数之间的相容性测 度等多种因素,对拟全方位视觉系统中的各路视觉估计进行性能综合评价;最终依据评价结果融合确定出具 有较高可信度和较强鲁棒性的运动估计参数．实验结果从鲁棒性、精度以及实时性等方面验证了本算法的有 效性．     

一种实用的手眼视觉系统定位方法

深入研究了机器人手眼视觉系统的立体定位问题。首先,重新将手眼问题公式化,得到一个新的系统模型;然后,在此基础上提出了一种实用有效的标定方法。其核心思想是直接将图像坐标映射到机器人基坐标系中,把系统参数作为一个整体来获取,而不必分别计算摄像机内部的每一个参数。与原方法相比,本方法可随意改变末端姿态定位,即定位时摄像机对目标取像的姿态不受任何约束。实验表明,该方法操作方便、实现简单、定位精度高。这一方法的提出克服了原方法的局限性,大大推广了手眼视觉系统的应用范围。     

简便高精度的机器人手眼视觉标定方法

对摄像机成像模型进行了分析,论述了机器人手眼系统标定原理。在此基础上,不改变机器人的外臂与基坐标系的旋转关系,设计了一种机器人手眼视觉的标定方法,与传统的方法比较,它不需要预先标定摄像机的内外参数。实验证明:该方法具有算法方便快捷、实验过程简单易行,且精度高等优点,可用于机器人进行运动目标定位与跟踪。     

A vision-based fast base frame calibration method for coordinated mobile manipulators

The mobile manipulators (MMs) have been increasingly adopted for machining large and complex components. In order to ensure the machining efficiency and quality, the MMs usually need to cooperate with each other. However, due to the low motion accuracy of the mobile platform, the relative pose accuracy between the coordinated MMs are difficult to guarantee, so an effective calibration method is needed to on-line obtain the relative pose of the MMs. For this purpose, a vision-based fast base frame calibration method is proposed in this paper, which can quickly and accurately obtain the relative pose between the coordinated MMs. The method only needs to add a camera and a marker, and then a frame network of the calibration system can be generated by installing the marker at three different positions. Based on the Perspective-n-Points principle and the robot forward kinematics, the transformation matrix of the marker frame with respect to the camera frame and the robot base frame can be determined by simply obtaining the images of the marker at different positions and corresponding robot joint angles. Then, the relative pose between the base frames of coordinated MMs can be determined by the calibration equation established based on a frame closed chains. In addition, the calibration method is capable of real-time calculation by dividing the calibration process into off-line and on-line stages. Simulation and experimental results have verified the effectiveness of the proposed method.     

Calibration-free and model-independent method for high-DOF image-based visual servoing

This paper presents a novel method to improve the performance of high-DOF image base visual servoing (IBVS) with an uncalibrated camera. Firstly, analysis and comparison between point-based and moment-based features are carried out with respect to a 4-DOF positioning task. Then, an extended interaction matrix (IM) related to the digital image, and a Kalman filter (KF)-based estimation algorithm of the extended IM without calibration and IM model are proposed. Finally, the KF-based algorithm is extended to realize an approximation to decoupled control scheme. Experimental results conducted on an industrial robot show that our proposed methods can provide accurate estimation of IM, and achieve similar performance compared with traditional calibration-based method. Therefore, the proposed methods can be applied to any robot control system in variational environments, and can realize instant operation to planar object with complex and unknown shape at large displacement.     

Delta机器人传送带与视觉的标定方法

针对机器人在流水线上精确抓取的问题,提出了Delta机器人系统的标定.通过机器人末端执行器在传送带上移动,计算出机器人与传送带的比例因子与转化矩阵,从而得到传送带相对于机器人的位姿,再通过相机对传送带上的物体获取计算出相机与传送带之间的转化矩阵.最后由传送带作为中间媒介,计算出视觉与机器人的转换关系.这一标定过程为实物抓取打下了基础.     

Self-calibration of environmental camera for mobile robot navigation

An environmental camera is a camera embedded in a working environment to provide vision guidance to a mobile robot. In the setup of such robot systems, the relative position and orientation between the mobile robot and the environmental camera are parameters that must unavoidably be calibrated. Traditionally, because the configuration of the robot system is task-driven, these kinds of external parameters of the camera are measured separately and should be measured each time a task is to be performed. In this paper, a method is proposed for the robot system in which calibration of the environmental camera is rendered by the robot system itself on the spot after a system is set up. Specific kinds of motion patterns of the mobile robot, which are called test motions, have been explored for calibration. The calibration approach is based upon executing certain selected test motions on the mobile robot and then using the camera to observe the robot. According to a comparison of odometry and sensing data, the external parameters of the camera can be calibrated. Furthermore, an evaluation index (virtual sensing error) has been developed for the selection and optimization of test motions to obtain good calibration performance. All the test motion patterns are computed offline in advance and saved in a database, which greatly shorten the calibration time. Simulations and experiments verified the effectiveness of the proposed method.     

嵌入式移动机器人红外路标定位模块研究

针对室内环境移动机器人的自定位问题,提出一种嵌入式移动机器人红外路标定位模块。采用基于单应矩阵的初始标定算法和陒机初始标定方法,补偿由于实际使用中的安装误差所引起的定位偏差。实验结果表明,该模块易于嵌入式系统实现,定位模块位置精度可达厘米级别,角度定位精度雓于6°。