Autonomous weld seam identification and localisation using eye-in-hand stereo vision for robotic arc welding

One of the main difficulties in using robotic welding in low to medium volume manufacturing or repair work is the time taken to programme the robot to weld a new part. It is often cheaper and more efficient to weld the parts manually. This paper presents a method for the automatic identification and location of welding seams for robotic welding using computer vision. The use of computer vision in welding faces some difficult challenges such as poor contrast, textureless images, reflections and imperfections on the surface of the steel such as scratches. The methods developed in the paper enables the robust identification of narrow weld seams for ferrous materials combined with reliable image matching and triangulation through the use of 2D homography. The proposed algorithms are validated through experiments using an industrial welding robot in a workshop environment. The results show that this method can provide a 3D Cartesian accuracy of within ±1 mm which is acceptable in most robotic arc welding applications.     

激光视觉传感器对不连续焊缝的识别

船舶制造中,为了对小格子船舱中排水孔形成的不连续焊缝进行跟踪,在机器人上安装视觉传感器提取排水孔的起点、终点特征信号。介绍了图像的采集方法和图像处理过程。对含有焊缝信息的图片先进行去噪预处理,再进行阈值分割,求取连通区与面积;细化图像,提取出激光线条的骨架;然后再进行霍夫变换,提取特征直线;最后求得两直线的交点,即焊缝的特征点,从而识别排水孔和焊缝。在模拟船舱结构的工件上进行不连续焊缝跟踪实验,实现了不连续焊缝的识别。     

基于不确定逼近的机械手自适应鲁棒预测控制

针对具有参数不确定性和未知外部干扰的机械手轨迹跟踪问题提出了一种多输入多输出自适应鲁棒预测控制方法. 首先根据机械手模型设计非线性鲁棒预测控制律, 并在控制律中引入监督控制项; 然后利用函数逼近的方法逼近控制律中因模型不确定性以及外部干扰引起的未知项. 理论证明了所设计的控制律能够使机械手无静差跟踪期望的关节角轨迹. 仿真验证了本文设计方法的有效性.     

A robust weld seam recognition method under heavy noise based on structured-light vision

Structured-light vision systems are widely used in robotic welding. The key to improving the robotic visual servo performance and weld quality is the weld seam recognition accuracy. Common detection algorithms are likely to be disturbed by the noise of spatter and arc during the welding process. In this paper, a weld seam recognition algorithm is proposed based on structured light vision to overcome this challenge. The core of this method is fully utilizing information of previous frames to process the current frame, which can make weld seam extraction both more robust and effective. The algorithm can be divided into three steps: initial laser center line recognition, online laser center line detection, and weld feature extraction. A Laplacian of Gaussian filter is used for recognizing the laser center line in the first frame. Afterwards, an algorithm based on the NURBS-snake model detects the laser center line online in a dynamic region of interest (abbreviated ROI). The center line obtained from first step is set as the initial contour of the NURBS-snake model. Using the line obtained from the previous step, feature points are determined by segmentation and straight-line fitting, while the position of the weld seam can be calculated according to the feature points. The accuracy, efficiency and robustness of the recognition algorithm are verified by experiments.     

基于RSSI的WSN吞吐量自适应优化策略

基于MicaZ型节点参数分别建立了ARQ技术和FEC技术的吞吐量模型,分析并仿真了各参数对吞吐量的影响,得出ARQ技术的最优数据帧长和FEC技术的最优BCH码,进而提出了一种基于RSSI测距技术的吞吐量自适应优化策略,以适应无线传感器网络(WSN)中动态变化的网络拓扑。该策略依据RSSI测距技术测量节点间的通信距离,自适应地为数据包选择最优的差错控制策略来提高WSN的吞吐量。仿真结果表明,在吞吐量和动态范围方面,该策略整体上优于单纯的ARQ或者FEC方案。     

经济型焊缝跟踪视觉传感器的研制

利用普通的焊接护目镜玻璃制作了熔池图像视觉传感器,在304#不锈钢等离子弧焊缝跟踪试验中获得的图像是足够清晰的,能够清楚地看到接缝和焊接熔池.在工厂车间里进行的试验证明:这种低成本的视觉传感器可以用于304#不锈钢的等离子弧焊接过程的实时焊缝跟踪和控制.     

Computer vision technology for seam tracking in robotic GTAW and GMAW

Due to ever increasing demand in precision in robotic welding automation and its inherent technical difficulties, seam tracking has become the research hotspot. This paper introduces the research in application of computer vision technology for real-time seam tracking in robotic gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW). The key aspect in using vision techniques to track welding seams is to acquire clear real-time weld images and to process them accurately. This is directly related to the precision of seam tracking. In order to further improve the accuracy of seam tracking, in this paper, a set of special vision system has been designed firstly, which can acquire clear and steady real-time weld images. By analyzing the features of weld images, a new and improved edge detection algorithm was proposed to detect the edges in weld images, and more accurately extract the seam and pool characteristic parameters. The image processing precision was verified through the experiments. Results showed that the precision of this vision based tracking technology can be controlled to be within ±0.17 mm and ±0.3 mm in robotic GTAW and GMAW, respectively.     

Real-time seam tracking for robotic laser welding using trajectory-based control

In this paper a real-time seam tracking algorithm is proposed that can cope with the accuracy demands of robotic laser welding. A trajectory-based control architecture is presented, which had to be developed for this seam tracking algorithm. Cartesian locations (position and orientation) are added to the robot trajectory during the robot motion. In this way, sensor information obtained during the robot motion is used to generate the robot trajectory while moving. Experiments have been performed to prove the tracking capabilities of the seam tracking algorithm.     

A vision system based on a laser range-finder applied to robotic fruit harvesting

This paper describes a laser-based computer vision system used for automatic fruit recognition. It is based on an infrared laser range-finder sensor that provides range and reflectance images and is designed to detect spherical objects in non-structured environments. Image analysis algorithms integrate both range and reflectance information to generate four characteristic primitives which give evidence of the existence of spherical objects. The output of this vision system includes 3D position, radius and surface reflectivity of each spherical object. It has been applied to the AGRIBOT orange harvesting robot, where it has obtained good fruit detection rates and unlikely false detections.     

基于虚拟正交试验的磁感应测速线圈参数优化

为提高磁感应线圈传感器测量弹丸高速运动的动态响应性能,研究了磁感应测速线圈系统特性与线圈几何参数之间的关系.根据正交试验设计的方法,基于Ansoft仿真软件,计算出不同几何参数下线圈特性的输出,并最终确定了一组用相对最优的线圈几何参数.实验测试结果表明:优化后的磁感应线圈提高了线圈输出的信噪比和输出灵敏度,有利于提高测速精度.     

视觉引导的旋转对称激光三角传感器快速测量方法

针对激光测距仪在对目标扫描测量过程中速度较慢的问题,提出一种视觉引导的测量方法。该方法在获取目标边缘的基础上,利用改进的前沿推进技术(AFT)方法,通过计算待测点与内外边界的距离系数,控制整体网格的疏密程度,得到适应的物体几何结构的三角网格。以三角网格的节点坐标作为对激光的视觉引导测量点,利用高精度步进电机控制激光三角传感器移动到指定坐标,获取深度数据,最终完成对目标的重建。实验结果表明:该视觉引导方法避免逐点扫描,至少提高40%以上测量效率。该方法重建效果较好,达到了快速测量和精确重建的要求。     

Modeling of a scanning laser range sensor for robotic applications

The geometric and noise modeling of a scanning range sensor is described. The parameters of the model are determined from data collected during the calibration of the real sensor. The models are shown to predict range scan results which accurately match those of the real sensor.     

基于粒子群算法的混合无线传感网覆盖优化

为优化混合传感网络覆盖性能,基于粒子群算法提出一种优化策略,并通过引进扰动因子,有效地避免了算法陷入早熟陷阱,加速了算法收敛。通过仿真实验,验证了该优化算法能够有效地提高网络覆盖性能,并与最新的算法进行了比较。     

A novel seam extraction and path planning method for robotic welding of medium-thickness plate structural parts based on 3D vision

Currently, the robotic welding of medium-thickness plate structural parts has become a common welding application. With the rapid development of automation technology and robotics, the traditional teaching-playback mode and the off-line programming mode cannot meet the automation demand of welding robots. To realize automatic seam extraction and path planning for robotic welding of medium-thickness plate structural parts without programming and teaching, we use three models of medium-thickness plate structural parts as the research objects to propose a novel seam extraction and path planning method for robotic welding of medium-thickness plate structural parts based on 3D vision. Firstly, a set of improved RANSAC multiplanes fitting algorithms is proposed to accurately obtain the position of the intersection lines between the intersecting planes of the point cloud model. On this basis, we combine the geometric features of three models to propose the specific welding seam extraction methods respectively. Then, according to the spatial structure of the welding seams and the welding process, we carry out the welding path planning. Finally, a welding pose planning method based on the dihedral structure is proposed. Experiment results show that the proposed method can well realize the welding seam extraction, welding path and posture planning of medium-thickness plate structural parts without programming and teaching.     

基于视觉传感器的障碍物检测

针对移动机器人双目视觉障碍物检测的实时性和准确性两大难题,提出了一种适用于室内复杂背景的障碍物检测方法。通过Retinex图像增强操作消除环境光照不均匀的影响;运用扫描线种子填充算法分割图像中的路面、背景和障碍物;通过二值化处理、边缘检测提取障碍物的轮廓信息和位置信息。在AS-RE轮式机器人平台上进行实验,实验结果表明,机器人能够在室内环境中稳定地实现自主避障功能,验证了提出的双目视觉障碍物检测算法的可行性。     

基于颜色曲线分析的快速焊缝条纹提取方法

针对彩色图像中焊缝条纹提取问题,提出一种基于颜色曲线分析的彩色图像分割方法。该方法首先将原始彩色图像转换到YUV颜色空间,对V通道进行颜色曲线分析,得到一个合适的二值化阈值;接着利用该阈值对V通道图像进行二值化,经形态学去噪和合并离散块处理,得到图像分割模板;最后将其运用到原始图像上,实现对原始彩色图像的焊缝条纹提取。将该方法应用到彩色图像焊缝条纹提取中,对于800×600的彩色图像,平均处理时间约0.3 s,与人工标注结果比较,提取框重叠比例70%以上的占90%,验证了该方法的高效性和准确性。     

加速度传感器壳体结构参数优化

合理的结构参数组合可提高加速度传感器壳体结构的固有频率,保证传感器在振动环境下输出信号稳定.通过建立竖直薄板力学模型,确定影响加速度传感器壳体固有频率的结构因素.基于响应面法思想,利用试验设计的方法,以加速度传感器壳体固有频率为指标,各结构参数为因素,设计二次回归正交旋转组合试验.通过ABAQUS 6.10软件建立各组试验结构参数组合下的分析模型并提取固有频率,最终确定使固有频率维持在较高水平的结构参数组合区间.通过对优化后参数进行验证性试验,表明优化后区间随机结构参数组合下加速度传感器壳体固有频率能够达到10 kHz以上.     

Multiposture leg tracking for temporarily vision restricted environments based on fusion of laser and radar sensor data

Leg tracking is an established field in mobile robotics and machine vision in general. These algorithms, however, only distinguish the scene between leg and nonleg detections. In application fields like firefighting, where people tend to choose squatting or crouching over standing postures, those methods will inevitably fail. Further, tracking based on a single sensor system may reduce the overall reliability if brought to outdoor or complex environments with limited vision on the target objectives. Therefore, we extend our recent work to a multiposture detection system based on laser and radar sensors, that are fused to allow for maximal reliability and accuracy in scenarios as complex as indoor firefighting with vastly limited vision. The proposed tracking pipeline is trained and extensively validated on a new data set. We show that the radar tracker reaches state-of-the-art performance, and that laser and fusion tracker outperform recent methods.     

Predictive seam tracking with iteratively learned feedforward compensation for high-precision robotic laser welding

In this paper, a novel architecture for robotic seam tracking using an industrial robot and off-the-shelf sensors is proposed to compensate the residual errors that are commonly observed in high-precision robotic laser welding due to the nonlinearity of a seam and the fast path drifts along a robot path. Our experiments demonstrate that the robot system can track both linear and nonlinear long seams at a high speed of 100 mm/s with TCP offset-error within ±0.1 mm using the proposed method.     

基于磁传感器的道路车辆参数检测系统

介绍了一种新型的道路车辆参数检测系统的原理、设计方案和实验结果。该系统利用磁通传感器取代传统地埋线圈作为检测元件、以单片机为核心构成信号处理电路,能够同时检测多车道道路上车辆的流量、车速,能够对超速、闻红灯等车辆的车牌进行拍照并定时向中控室上传测量信息。实验结果显示：本系统对道路车辆占有率的测量精度与超速检测准确率可达98％以上,优于地埋线圈式系统的检测效果,且安装更加方便。