Measurement error analysis and accuracy enhancement of 2D vision system for robotic drilling

Robotic drilling for aircraft structures demands higher accuracy on industrial robots than their traditional applications. Positioning error measurement and compensation based on 2D vision system is a cost-effective way to improve the positioning accuracy in robotic drilling. In this paper, we first discuss the principle of error measurement and compensation with a 2D vision system for robotic drilling and the determination of tool center point of the vision system so that the Abbe errors are eliminated in the measurement process. Measurement errors due to nonideal measurement conditions, i.e. nonperpendicularity of the camera optical axis to the workpiece surface and incorrect object distance, are mathematically modeled and experimentally verified. A method utilizing four laser displacement sensors is proposed to ensure perpendicularity of the camera optical axis to the workpiece surface and correct object distance in the measurement process, and hence to achieve high accuracy in 2D vision-based measurement. Experiments performed on a robotic drilling system show that the 2D vision system can achieve an accuracy of approximately 0.1 mm with the proposed method.     

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。     

Machine vision based path planning for a robotic golf club head welding system

A path planning method based on machine vision techniques is constructed for a golf-club head robotic welding system. This system uses 3D machine vision techniques to recognize the weldseam and generates a welding path for the robot. The location of the weldseam is discovered by applying a Sobel mask to the captured data. A Laplace mask is also useful to filter out the noise points due to the scatter light refraction of tack-welding spots. The weldseam is then replenished and smoothed out by a B-spline curve fitting. The task frame of the weldseam is computed by finding the tangent, normal, and bi-normal of the curve. The robotic welding path is obtained by further rotations and translation along the axes of the task frame according to the requirement of the welding attitude. The developed machine vision technique and the mathematic framework pertaining to the generation of a welding task frame can readily be used for various three-dimensional welding tasks.     

Neuromorphic vision based control for the precise positioning of robotic drilling systems

The manufacturing industry is currently witnessing a paradigm shift with the unprecedented adoption of industrial robots, and machine vision is a key perception technology that enables these robots to perform precise operations in unstructured environments. However, the sensitivity of conventional vision sensors to lighting conditions and high-speed motion sets a limitation on the reliability and work-rate of production lines. Neuromorphic vision is a recent technology with the potential to address the challenges of conventional vision with its high temporal resolution, low latency, and wide dynamic range. In this paper and for the first time, we propose a novel neuromorphic vision based controller for robotic machining applications to enable faster and more reliable operation, and present a complete robotic system capable of performing drilling tasks with sub-millimeter accuracy. Our proposed system localizes the target workpiece in 3D using two perception stages that we developed specifically for the asynchronous output of neuromorphic cameras. The first stage performs multi-view reconstruction for an initial estimate of the workpiece’s pose, and the second stage refines this estimate for a local region of the workpiece using circular hole detection. The robot then precisely positions the drilling end-effector and drills the target holes on the workpiece using a combined position-based and image-based visual servoing approach. The proposed solution is validated experimentally for drilling nutplate holes on workpieces placed arbitrarily in an unstructured environment with uncontrolled lighting. Experimental results prove the effectiveness of our solution with maximum positional errors of less than 0.2 mm, and demonstrate that the use of neuromorphic vision overcomes the lighting and speed limitations of conventional cameras. The findings of this paper identify neuromorphic vision as a promising technology that can expedite and robustify robotic manufacturing processes in line with the requirements of the fourth industrial revolution.     

一种基于单目视觉的实时人机测距系统研究

为获取视觉交互系统中人机距离信息, 利用单摄像头检测人脸特征区域、完成人脸与摄像机距离测量。首先通过改进的AdaBoost算法快速检测并定位特征区域, 其次利用系统约束条件、摄像机标定原理和面积映射关系推导像距测量方程, 完成距离测量。通过规定距离实验, 证明了像距测量方程的可行性。复杂环境实验表明系统在复杂背景下有较好的鲁棒性, 但不同光照会影响测量精度。系统适应性实验验证了对多名待测者的普遍适用性, 但佩戴眼镜会影响测量的精度和实时性。测距系统在有效量程内有较高精度, 处理速度约为5 fps, 满足精度与实时性要求。     

Recognition of quadratic surface of revolution using a robotic vision system

Reverse engineering using 3D scanners has been gaining increasing popularity. One challenging task that remains is to recognize the geometric feature from the cloud data scanned. In this study, a robotic vision system is used to recognize quadratic surfaces of revolution on an object.The top-view image of an object is used to detect the surface boundary by loop analysis technique. The boundary of a single surface is extracted according to the 2D loop of that surface. The robot then projects laser lines through the principal axes of the loop to get the sectional curves. The surface is recognized by a curve-fitting method based on the characteristics of these curves.This study provides a simple and faster method to detect the manufacture features on an object that contains quadratic surfaces. The data structure can be output in IGES format for re-design or rapid manufacture of the object.     

扶正器测试系统研究与实现

根据扶正器结构与测量需求,设计实现了扶正器综合测试系统.系统综合利用了管道压力、光电和应变测量等多种手段,完成了扶正器在旋转过程中的推力、转速、推出偏差角的测量,从而为扶正器的检验与校正提供了有力手段.     

基于opencv的单目视觉测量系统的研究

_{介绍一种基于机器视觉的测量工件宽度的新方法,在开源计算机视觉库OpenCV的支持下,设计并实现一种对工件宽度进行动态实时测量的系统。为了降低其它光的影响,在CCD镜头下面固定一块红光滤光片,系统通过采集经红光线激光器投射的工件图像,对图像进行二值化、截取感兴趣区域、轮廓提取等处理,最后实现工件宽度的自动测量。对不同尺寸的工件进行了自动测量实验,实验结果表明,采用的测量方法在实际工件测量中是可用的,整个测量过程用时在100ms左右,最大相对误差不超过1.5%。}     

Maintaining a common co-ordinate system for a group of robots based on vision

This work presents a novel approach to the problem of establishing and maintaining a common co-ordinate system for a group of robots. A camera system mounted on top of a robot and vision algorithms are used to calculate the relative position of each surrounding robot. The watched movement of each robot is compared to the reported movement which is sent over some communication link. From this comparison a co-ordinate transformation is calculated. The algorithm was tested in simulation and is at the moment being implemented on a real robot system. Preliminary results of real world experiments are being presented.     

用于单目视觉的路径失真矫正系统设计与实现

针对单目视觉机器人产生的路径图像失真问题,分析了产生失真的原因及常用的矫正方式,提出了一种可以通过快速标定来解决路径图像畸变失真问题的方法。将待矫正图像的纵向与横向像素序列分别与标定板进行分析对比,纵向上采用非均匀行采样原理,通过单张标定照找到特征采样行,使采样后图像与实际道路相对无畸变;横向上采用线性伸缩矫正算法,结合适当的插值运算,达到横向矫正。该方法避免了要多次测量外部标定数据及内部传感器参数,在运算量上与实用性上取得了较好的平衡。在此基础上,介绍了如何利用Matlab工具箱快速设计实现图像矫正系统,并且通过数据对比证明了该系统具有一定的准确与便捷性,在工程上具有较高的价值。     

A robust navigation system for robotic wheelchairs

A landmark based navigation system for robotic wheelchairs is developed. The proposed navigation system is robust in the localization procedure which is the major problem in robotic navigation systems. Every landmark is composed of a segment of metallic path and a radio-frequency identification (RFID) tag. The odometry information is used for localization, which is corrected on-line every time the robotic wheelchair is over a landmark. A topological map is generated using such landmarks to compute the shortest path. A technique to generate the topological map for this navigation system and an obstacle avoidance strategy are also developed.     

Development of CAM system based on industrial robotic servo controller without using robot language

This paper describes the development of a robotic CAM system for an articulated industrial robot RV1A from the view point of robotic servo controller. It is defined here that the CAM system includes an important function which allows an industrial robot to move along cutter location data (CL data) consisting of position and orientation components. In addition, the developed CAM system has a high applicability to other industrial robots whose servo systems are technically opened to end-users. The developed robotic CAM system works as a straightforward interface between a general CAD/CAM and an industrial robot. At the present stage, the relationship between CAD/CAM and industrial robots is not well established compared to NC machine tools that are widely spread in manufacturing industries. The CAM systems for NC machine tools are already established, however, the CAM system for industrial robots has not been sufficiently considered and developed yet. A teaching pendant is generally used to obtain position and orientation data of the arm tip before an industrial robot works. Here, in order to enhance the relationship between a conventional CAD/CAM system and an industrial robot, a simple and straightforward CAM system without using any robot language is developed and implemented. The basic design of the robotic CAM system and the experimental results are presented in this paper.     

视觉导航中的单目摄像机标定改进算法

在基于单目视觉的智能车自主导航系统中,摄像机标定是智能车实现安全准确视觉导航的前提和关键。研究摄像机理想模型和实际模型,提出一种改进的标定方法。结合线性模型和非线性模型的优点,在求解摄像机内外参数的过程中,先采用线性模型标定摄像机的一部分参数,进一步考虑简化畸变模型,将非线性方程组转化为线性方程组迭代求解,最终获得摄像机全部参数。该方法既保证了标定精度,又简化了复杂的摄像机实际模型。实验结果表明该方法能满足视觉导航要求。     

Development of multiple robotic fish cooperation platform

This article presents the development of a multiple robotic fish cooperation platform, which is established by employing a group of radio-controlled, multi-link fish-like robots. This work is inspired by the observation from nature that the capability of one single fish is limited, as in order to survive the atrocious circumstances in the sea, fish often swim in schools. The analogical situations occur in the robotic fish case. In engineering applications, most missions are so complex that they must be accomplished by effective cooperation of multiple fish robots. The platform presented in this article, as a novel test bed for multiple robotic fish cooperation, can be applied to different types of complex tasks. More importantly, it provides a good platform to test and verify all kinds of algorithms and strategies for cooperation of multiple underwater mobile robots. We use two cooperative tasks as examples to heuristically demonstrate the performance of this platform.     

Evolution of a vision system by genetic algorithm

This paper proposes a framework for a genetic algorithm applied to determine and construct an organ, especially the neural network of a virtual creature. The vision system of the creature is a result of genetic evolution, and we are trying to realize this on the computer. We examine how the visual organ of the animal is evolved under a special environment (e.g., the specialized visual organ of an animal to catch a moving insect), and how many variations of neural networks exist. We also think it is possible to generalize the method to an automatic generation of various kinds of visual recognition system by adding various kinds of evolution any directions. This work was presented, in part, at the Second International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1997     

移动机器人前向单目视觉的建模研究

为了实现目标对象的快速、精确识别,对移动机器人前向单目视觉进行了建模.首先,给出了前向单目视觉成像模型,包括软、硬件设计,并结合目标特征属性得到目标中心在图像上的坐标;然后,通过视觉标定模型实现前向单目视觉的目标定位,得到目标对象在机器人体坐标系中的坐标;最后,利用参数估计的方法计算真实检测结果与理想检测结果的误差分布模型的参数,得到前向单目视觉的观测模型.实验结果表明,前向单目视觉模型建立精确,且实时性好.     

互感器检定仿真实训软件系统的设计与实现

现有互感器检定培训模式均采用实际操作的方式,存在周期长、工作效率低、有安全隐患等问题,本文开发了一套仿真培训软件系统,该系统集培训、仿真和实训为一体,学员可利用系统进行培训、考试、仿真接线和设备认知,通过系统性的学习和训练,最终掌握互感器检定技术。     

PD with sliding mode control for trajectory tracking of robotic system

Good tracking performance is very important for trajectory tracking control of robotic systems. In this paper, a new model-free control law, called PD with sliding mode control law or PD–SMC in short, is proposed for trajectory tracking control of multi-degree-of-freedom linear translational robotic systems. The new control law takes the advantages of the simplicity and easy design of PD control and the robustness of SMC to model uncertainty and parameter fluctuation, and avoid the requirements for known knowledge of the system dynamics associated with SMC. The proposed control has the features of linear control provided by PD control and nonlinear control contributed by SMC. In the proposed PD–SMC, PD control is used to stabilize the controlled system, while SMC is used to compensate the disturbance and uncertainty and reduce tracking errors dramatically. The stability analysis is conducted for the proposed PD–SMC law, and some guidelines for the selection of control parameters for PD–SMC are provided. Simulation results prove the effectiveness and robustness of the proposed PD–SMC. It is also shown that PD–SMC can achieve very good tracking performances compared to PD control under the uncertainties and varying load conditions.     

一种与模型无关的全向视觉系统标定方法

传统的全向视觉系统标定方法假设研究对象满足单视点成像模型且全向反射镜面各向同性,而在实际应用中上述假设往往并不成立,这会对标定精度带来很大的影响。针对全向视觉系统成像特点设计了一种新的与模型无关的标定方法,不需要研究对象满足上述约束,适用于对各种折反射式全向视觉系统的标定,具有较高的精度。将其应用于NuBot足球机器人全向视觉系统的标定后,较大地提高了机器人基于全向视觉的自定位精度,验证了标定方法的有效性和实用性。