基于宏微机器人的焊缝跟踪研究

提出了一种基于宏微运动机器人的焊缝跟踪方法．首先,通过若干点的简单示教获得焊缝位置信息,并通过拟合建立焊缝模型．在该模型的基础上,对机器人的宏动进行运动规划．采用激光结构光视觉测量焊缝坐标,并根据焊缝图像偏差控制机器人的微动．结合机器人的宏动规划运动和微动自动调整,实现大范围、高精度的焊缝跟踪．利用宏微运动平台进行了焊缝跟踪实验,实验结果验证了所提出方法的有效性．     

双队列控制的激光视觉焊缝跟踪系统研究

设计与实现了一套激光视觉引导的焊缝自动跟踪系统,包括系统的整体硬件构成和关键算法。在工业机器人末端安装激光视觉传感器构成焊缝跟踪系统的硬件部分。采用小波变换滤除焊缝图像噪声,采用改进的Steger算法和Hough变换方法提取激光条纹中心直线,进一步提取出焊缝位置。提出一种双队列控制策略,在采集的焊缝特征点的基础上进一步插值,从而实现激光视觉引导的焊缝自动与平滑跟踪。实验结果表明,该系统具有较好的跟踪精度,能满足工业实际需求。     

机器人基于电弧传感器对90°折线角焊缝的跟踪

针对准确跟踪90°折线角焊缝比较困难的问题,提出了一种基于旋转电弧传感器和路径规划组合的方法.通过对旋转电弧传感器采集到的焊接电流进行滤波,采用最小二乘偏差识别和模糊控制算法,控制机器人左右轮差速运动或水平滑块伸缩.直角拐弯时基于路径规划和水平滑块伸缩跟踪焊缝,未进入直角拐弯时是基于左右轮差速运动跟踪焊缝.实验结果表明,该算法能够很好地实现90°折线角焊缝的跟踪.     

色噪声下卡尔曼滤波焊缝跟踪算法与试验研究

精确控制激光束使其始终对中并跟踪焊缝是保证激光焊接质量的前提．以大功率光纤激光焊接Type304不锈钢为试验对象,研究一种有色噪声环境下应用卡尔曼滤波最优状态估计预测激光束与焊缝路径偏差的方法．使用高速红外视觉传感器摄取焊接区红外热像,提取焊缝位置参数并构成状态向量,建立基于焊缝位置参数的系统状态方程和焊缝位置测量方程．针对系统动态噪声为有色噪声,通过扩展状态变量的方法建立有色噪声环境下的卡尔曼滤波算法,对焊缝位置进行最优状态估计并得到最小均方差条件下的焊缝偏差最优预测值,消除系统噪声对焊缝偏差测量的影响．焊接试验结果表明新方法可有效抑制有色噪声干扰并提高焊缝跟踪精度．     

弧焊视觉轨迹控制中的自动导引方法研究

本文给出了采用三维视觉焊缝跟踪传感器实现机器人自主寻找焊缝、跟踪焊接、结束焊接的控制方法 ,实验表明该方法能够进一步提高焊接自动化水平     

焊接机器人曲线焊缝的自动跟踪控制

为实现焊接机器人对曲线焊缝的自动跟踪,提出一种简便的位姿实时调整策略和协调视觉跟踪与机器人运动的视觉伺服控制方法。建立了曲线焊缝视觉跟踪过程中焊接机器人期望位姿的数学模型;设计了一种上下层结构的模糊视觉伺服控制器,通过建立焊缝特征点像素坐标偏差与末端轴旋转角度之间的关系模型,动态确定模糊论域的大小,在机器人期望位姿的基础上仅仅通过调整末端轴的旋转量来保证图像特征点始终存在于相机视场内。通过模拟焊接机器人自动跟踪曲线焊缝的实验,验证了所提策略与方法的有效性。     

基于线激光视觉的机器人焊缝跟踪鲁棒控制方法

为了解决机器人在高速状态下进行焊缝跟踪时在拐角处产生的失真变形问题,提出了一种基于线激光视觉的机器人焊缝跟踪鲁棒控制方法。该方法通过视觉系统的预测量获得焊缝轮廓信息,对焊缝拐点进行识别并辨认拐角区域,对不同的轮廓部分采用不同的控制策略,同时引入自动校正过程,校正实际生产过程中的装配误差。实验结果表明该方法可以实现可靠的检测与跟踪,解决了高速状态下的运动轨迹失真问题,有效地提高了机器人焊缝跟踪的速度与精度,并确保系统在外界干扰的情况下仍能保持准确和稳定的运动,增强了系统的鲁棒性。     

履带式智能弧焊机器人焊缝跟踪控制系统

针对新型履带式弧焊机器人焊缝跟踪问题进行了实验研究.通过对爬行机器人行走电机的控制完成机器人焊缝跟踪粗调，对十字滑块电机控制完成机器人焊缝跟踪细调，最终实现了机器人焊缝跟踪，实验表明跟踪效果良好．     

焊接机器人焊缝自动跟踪系统

本文提出了一种焊接机器人焊缝自动跟踪系统用以实现焊枪对焊缝的实时自动跟踪。系统中应用激光焊缝传感器测量焊缝的位置,并采用Fuzzy-P双模分段控制进行焊缝的纠偏。DSP作为系统的核心控制器产生控制信号,驱动焊枪横向步进电机和纵向步进电机动作,调整焊枪实时跟踪焊缝。实验证明,基于双模控制的焊缝自动跟踪系统可以实现焊接机器人焊枪对焊缝的实时自动跟踪。该系统完全满足实际焊接工程的需要。     

基于双模控制的焊接机器人焊缝自动跟踪系统

该文提出了一种基于双模控制的焊接机器人焊缝自动跟踪系统.系统中应用新一代激光焊缝传感器测量焊缝的位置,并采用Fuzzy-P双模分段控制进行焊缝的纠偏.系统中采用DSP作为核心控制器产生控制信号,驱动焊枪横向步进电机和纵向步进电机动作,实现焊接机器人焊枪对焊缝的实时自动跟踪.实验证明,基于双模控制的焊缝自动跟踪系统可以实现焊接机器人焊枪对焊缝的实时自动跟踪.该系统完全满足实际焊接工程的需要.     

An on-line shape-matching weld seam tracking system

Automatic welding technology continues to find a broader application in diverse industries due to its high efficiency and accuracy. In this work, an on-line laser-based machine vision system for seam tracking was developed. To achieve a reliable and accurate seam tracking process that is adaptive to different groove types, a shape-matching algorithm was proposed and implemented. The algorithm uses the previous groove shape as the template to locate the next groove shape. Tests on U-groove, tap-groove and free form groove have verified its adaptability and robustness to different groove types with noise. The shape-matching algorithm also enables the seam tracking system to automatically localize the starting and finishing point of the weld seam. A FIFO based queue was defined and implemented to tackle the lag distance problem between the heat source and the vision sensor. The tracking algorithm, along with the FIFO queue was successfully verified on a sine-shaped seam. A tracking accuracy of ±0.5 mm was achieved in this test, which is acceptable in most of the arc welding applications.     

Autonomous Acquisition of Seam Coordinates for Arc Welding Robot Based on Visual Servoing

Autonomous acquisition of seam coordinates is a key technology for developing advanced welding robot. This paper describes a position-based visual servo system for robotic seam tracking, which is able to autonomously acquire the seam coordinates of the planar butt joint in the robot base frame and plan the optimal camera angle before welding. A six-axis industrial robot is used in this system, which has an interface for communicating with the master computer. The developed visual sensor device is briefly presented that allows the charge-coupled device (CCD) cameras to rotate about the torch. A set of robust image processing algorithms are proposed so that no special requirements of light source are needed in this system. The feedback errors of this servo system are defined according to the characteristics of the seam image, and the robust tracking controller is developed. Both the image processing program and tracking control program run on the master computer. The experimental results on straight line seam and curve seam show that the accuracy of the seam coordinates acquired with this method is more adequate for high quality welding process.     

Real-Time Seam Tracking Technology of Welding Robot with Visual Sensing

A seam tracking system with visual sensing free from calibration was developed for the robot applied in gas tungsten arc welding. A visual sensor with double-layer filter system was researched for the different levels of the welding current. An image processing in C+?+ language was developed to extract the seam trajectory and the offset of the torch to the seam in the welding images of aluminum alloys plates with grooves. The rectifying rule of the robot used in this paper was found based on the experimental data, and the seam tracking controller was also analyzed and constructed. The experimental results on straight line seam and curve seam demonstrated the efficiency of the proposal seam tracking system.     

基于激光视觉检测的焊缝自动跟踪系统研究

旨在提高焊缝跟踪精度和焊接质量,提出一种基于激光检测自动焊缝跟踪系统。该系统由激光视觉部件、控制器、步进电机和十字滑架组成。当系统工作时,由激光视觉部件检测焊缝的当前位置与目标位置之间的偏差,控制器基于该偏差确定纠偏量,步进电机驱动十字滑架以纠正焊枪横向与纵向位置偏差。搭建出系统物理样机,进行了焊缝跟踪试验。试验结果表明,基于激光视觉检测的焊缝跟踪误差可控制在0. 5 mm 之内,其在精密焊接领域具有较大应用前景。     

Research on the Real-time Tracking Information of Three-dimension Welding Seam in Robotic GTAW Process Based on Composite Sensor Technology

Aiming at the shortcomings of teaching-playback robot that can??t track the three-dimensional welding seam in real time during GTAW process, this paper designed a set of composite sensor system for tracking the three-dimensional welding seam based on visual sensor and arc sensor technology, which can effectively acquire three-dimensional welding seam information, such as clear images of seam and pool and stable arc voltage signals. The characteristic values of weld image and arc voltage signals were accurately extracted by using proper processing algorithm, and the experiments have been done to verify the precision of processing algorithms. The results demonstrate that the error is very small, which is accurate enough to meet the requirements of the subsequent real-time tracking and controlling during the welding robot GTAW process.