Precision measurement and compensation of kinematic errors for industrial robots using artifact and machine learning

Industrial robots are widely used in various areas owing to their greater degrees of freedom (DOFs) and larger operation space compared with traditional frame movement systems involving sliding and rotational stages. However, the geometrical transfer of joint kinematic errors and the relatively weak rigidity of industrial robots compared with frame movement systems decrease their absolute kinematic accuracy, thereby limiting their further application in ultraprecision manufacturing. This imposes a stringent requirement for improving the absolute kinematic accuracy of industrial robots in terms of the position and orientation of the robot arm end. Current measurement and compensation methods for industrial robots either require expensive measuring systems, producing positioning or orientation errors, or offer low measurement accuracy. Herein, a kinematic calibration method for an industrial robot using an artifact with a hybrid spherical and ellipsoid surface is proposed. A system with submicrometric precision for measuring the position and orientation of the robot arm end is developed using laser displacement sensors. Subsequently, a novel kinematic error compensating method involving both a residual learning algorithm and a neural network is proposed to compensate for nonlinear errors. A six-layer recurrent neural network (RNN) is designed to compensate for the kinematic nonlinear errors of a six-DOF industrial robot. The results validate the feasibility of the proposed method for measuring the kinematic errors of industrial robots, and the compensation method based on the RNN improves the accuracy via parameter fitting. Experimental studies show that the measuring system and compensation method can reduce motion errors by more than 30%. The present study provides a feasible and economic approach for measuring and improving the motion accuracy of an industrial robot at the submicrometric measurement level.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00400-6     

轴线测量与迭代补偿的机器人几何参数标定

为了提高串联工业机器人的绝对定位精度,提出了采用轴线测量与迭代补偿相结合的工业机器人几何参数标定方法。首先利用激光跟踪仪测量机器人单轴运动的轨迹,将所测轨迹点通过空间投影计算各轴线的位置;然后根据机器人模型参数的几何定义提取机器人模型的实际参数,并采用基于距离误差的迭代补偿方法进行参数标定效果验证。对埃夫特ER10L-C10工业机器人进行标定实验研究,结果表明:机器人绝对定位误差的最大值、平均值和标准差分别从补偿前的4.215、1.932和1.437 mm减小到补偿后的2.979、1.015和1.031 mm,该方法能够简单快速标定出机器人模型的实际几何参数,有效提高了机器人的绝对定位精度。     

视觉检测系统定位误差分离方法

介绍了视觉检测系统中利用空间解析几何、统计原理、摄动学等方面的知识分离工件定位误差的方法，提出用软件实现定位误差分离，从而在一定程度上剔除了定位误差对测量精度的影响。     

工业机器人校准技术与补偿方法发展现状及趋势

工业机器人因具有自动化程度高、定位精度好等优势,已成为我国工业智能化的攻关方向之一,并将逐步替代人工,在智能制造领域发挥不可替代的作用。但是在使用过程中,造成工业机器人精度下降的因素众多,将直接影响其在叶片研磨、高精度钻铆等高精尖领域的应用。针对上述问题,在总结工业机器人通用校准模型的基础上,分析了工业机器人校准技术与误差补偿方法的现状及存在的问题,阐述了工业机器人校准方法未来发展趋势,为后续工业机器人在线校准与误差补偿方法和规范标准的制定提供借鉴。     

Modelling and compensation of fixture locators’ error in CNC milling

Fixture errors are one of the error sources in machining operations. The fixture errors consist of positioning inaccuracies and errors due to workpiece and fixture deformations. Fixture locators’ height error causes incorrect positioning of the workpiece in the fixture and inaccuracy in machined surfaces which can be much more than the locators’ height error. For machining precise workpieces, it is necessary to eliminate these errors. This paper presents a method for modelling and compensating the fixture locators’ height error effect on workpiece machined surfaces. In this method, the planes of workpiece actual coordinate system (ACS) are mathematically modelled in the workpiece theoretical coordinate system (TCS). Using the model, required homogenous transformation matrix for coinciding ACS with TCS and modifying machining toolpath for compensating the errors is generated. The presented model is used to develop a post-processing fixture locator error compensation module, which can modify CNC machining codes to eliminate the effect of fixture locators’ height error on the workpiece machined surfaces. For verifying the presented method, machining simulations and cutting experiments have been performed in this work. The results show that the method can eliminate the effect of fixture locators’ height error on the workpiece machined surfaces considerably.     

基于移动通信网络的导航定位体系的探讨

因导航定位有不可替代的作用,本文简要介绍了几种常用的导航定位方法,并对几种常用导航定位系统进行阐述,总结归纳了不同导航定位系统的特点.进而,提出了一种基于移动通信网络基站的低成本、高精度、快速、全球导航定位体现框架,并对其特点、优势和技术可行性进行了讨论.该导航体现框架有望在未来的智能交通、智能机器人、智能物流、智能边...     

线性运动平台多自由度几何运动误差测量技术

线性运动平台是精密制造和测量的基础,其定位精度直接影响着制造和测量的精度。由于制造和装配误差的影响,运动平台存在六个自由度的运动误差,将影响运动平台的定位精度。为了提高运动平台的定位精度,需要准确地测量各项运动误差。传统的测量方法只能对单一误差进行测量,并且测量仪器体积较大,无法集成在运动平台中进行实时误差测量。本文提出了一系列成本低、体积小、易集成的高精度多自由度几何运动误差同时测量技术,可以根据测量需求选择测量系统的自由度,在提高测量精度的同时,还可以实现在线测量,为提高线性运动平台运动精度起到重要作用。     

多冲击声源定位算法

为了解决导弹、空投鱼雷等各种类型物体入水点精确定位问题,针对多个冲击声源产生的复杂抵达序列,提出先排序组合定位,再对最小方差项排序,然后用组合关联模型选取最优解组合的算法,实现对多个冲击声源目标的精确定位.误差分析给出了阵位误差和测时误差对定位精度的影响.仿真测试了13枚弹头在130m×30ｍ区域内、1s时间内均匀分布的冲击定位情况,13点定位误差与阵位预置误差基本相当,并且,冲击区域在阵中心时的定位精度高于冲击区域在阵边缘时的定位精度.港内试验验证了该算法能够有效地对多个点进行解算定位,其定位精度在5m以内.     

Kalman滤波中测量粗差的探测与修复

在动态定位的数据处理中动态观测量可能存在粗差,若数据处理不考虑对这些异常的特别处理,则所提供的动态信息将极不可靠。文中计算了粗差对滤波结果的影响,并由此建立了动态定位中粗差的探测和修复算法。最后用数字仿真实验论证了方法的可行性。     

面向机器人标定的单激光跟踪仪顺序多站式测量系统建模与分析

为实现大型串联工业机器人的高精度标定,搭建了一种单激光跟踪仪的顺序多站式测量系统。该系统仅需单台激光跟踪仪,先后在不同的基站位置对工业机器人的末端位置进行独立测量,并基于多边测量方法计算机器人的末端位置。计算过程中仅需激光跟踪仪的距离信息,有效地优化了末端位置的测量不确定度。首先,建立了该测量系统的仿真模型,深入地分析了测量点的数量与分布形状、测量距离以及工业机器人定位精度等因素对系统测量精度的影响;然后,依据分析结果确定单激光跟踪仪顺序多站式测量系统的搭建方案。实验结果表明:该系统在2.5m距离上的测量误差仅为0.023mm,优于激光跟踪仪的测量精度,满足大型串联工业机器人参数标定的测量精度要求。     

基于PLC与触摸屏的码垛工业机器人操作系统设计

目的对工业机器人码垛操作系统进行改进,使用三菱GS2110-WTBD触摸屏实现工业机器人便捷的操作控制与工作状态的直观监视。方法三菱GS2110-WTBD触摸屏与PLC使用串口通讯,PLC与工业机器人使用以太网通讯,实现信息交互。外接控制按钮及传感器与QX40模块连接,QY10模块与工业机器人控制器I/O接口连接,三菱Q系列PLC控制三菱QD75P1N定位模块驱动供料进给。结果编写PLC程序和机器人程序使得机器人与物料盘供料驱动相互配合,能实现对动态物体的精准抓取或放置。触摸屏设计可以实现不同码垛功能的选择和工作状态的监视。结论该操作系统可使单台工业机器人灵活运用在变化的控制线上,可广泛应用在码垛工业机器人控制中。     

防跌倒步态平衡训练机器人发展现状

目的 介绍国内外防跌倒步态平衡训练机器人研究的主要进展,为防跌倒步态平衡训练机器人等医工结合领域的研究提供可借鉴的思路。方法 主要从4个方面总结了下肢辅助康复机器人研究的最新进展,具体包括机器人构型,机构控制策略和算法,步态数据采集方法和步态数据分析方法。结论 在国内外对步态平衡训练机器人的研究中,机器人的市场定位细分是当前学界面临的挑战。各主流解决方案侧重点都不相同,针对用户细分的方法也不一样。由于主要的目标人群老年人群体用户差异性强,因此用户的个性化训练需求较高,未来需要进一步细化步态平衡训练机器人的定位,满足不同情况下不同用户在不同阶段的个性化训练需求,有望提升步态平衡训练机器人的整体水平。     

On the comparison of bilinear, cubic spline, and fuzzy interpolation techniques for robotic position measurements

This paper describes a novel technique for position error compensations of robots based on a fuzzy error interpolation method. A traditional robot calibration implements either model or modelless methods. The compensation of position error in a model-less method is to move the robot's end-effector to a target position in the robot workspace, and to find the target position error online based on the measured neighboring four-point errors around the target position. For this purpose, a stereo camera or other measurement device can be used to measure offline the position errors of the robot's end-effector at predefined grid points. By using the proposed fuzzy error interpolation technique, the accuracy of the position error compensation can be greatly improved, which is confirmed by the simulation results given in this paper. A comparison study among various interpolation methods, such as bilinear, cubic spline, and the fuzzy error interpolation technique is also made via simulation. The simulation results show that more accurate compensation results can be achieved using the fuzzy error interpolation technique compared with its bilinear and cubic spline counterparts.     

索牵引并联机器人中变长度柔索的动力学分析

现有索牵引并联机器人研究中大多将柔索处理成简单的索杆单元,没有充分考虑柔索的动力学特性对末端执行器定位精度的影响。为此,本文提出了一种柔索长度慢速变化时的索牵引并联机器人动力学模型。文中首先推导了描述变长度柔索动力学特性的偏微分方程,空间离散化后采用有限差分法将其转换成普通微分方程。然后,根据末端执行器与柔索之间的动力耦合关系,得出索牵引并联机器人的动力学模型,模型中同时包含有柔索和末端执行器的自由度。最后,给出两个算例来验证本文模型的有效性,同时说明工作空间巨大时考虑柔索动态特性的必要性。     

MAGNETIC BEARING SPINDLES FOR ENHANCING TOOL PATH ACCURACY

Thin rib machining of electronic components or airframe structures can benefit from high speed machining for burr free cutting, improved surface quality and increased metal removal rate. It is suggested that the use of a magnetic bearing spindle can not only successfully provide the benefits of high speed machining but, more importantly, minimize tool path errors. In this paper the various sources of tool path error are discussed as functions of machine tool positioning errors and cutting force errors which are characterized as static, dynamic and stochastic. The operation of high speed magnetic bearing spindles is described and a control scheme whereby the spindle may be translated and tilted for minimizing tool path errors is discussed. This overall research activity is a cooperative effort between the University of Maryland, Cincinnati Milacron, Magnetic Bearings, Inc., The Uestinghouse Corporation, and The National Bureau of Standards.     

基于模糊神经网络的包装机械臂定位方法研究

目的 为提高包装机械臂的抓取精度,文中基于模糊神经网络设计一种包装机械臂定位方法。方法 将激光测距仪与工业相机融合,可实现目标点的初步定位并得到位姿偏差。以机械臂末端位置误差补偿为例,设计一种模糊神经网络控制器,可实现PID控制关键参数的在线调整以提高误差补偿精度。进一步地,采用果蝇优化算法实现神经网络控制器初始值的优化,可提高控制系统性能。最后,进行实验研究。结果 实验结果表明,机械臂定位算法可使最大绝对误差从7.704 9 mm下降到1.424 2 mm;平均绝对定位误差降低约82.5%;机械臂执行效率与对照组相当。结论 该定位方法可以大幅度提高包装机械臂定位精度,可满足包装、化工、食品等相关行业要求。     

Automated assembly of precision-mechanical and electronic products†

Smaller production lots and new products require the application of programmable robots in assembly areas for the production of precision-mechanical and electronic devices. The article provides an overview of the whole subject. The application of robots in timer production for the insertion of components to PC boards and the positioning of special components is explicitly described.     

多目视觉测量系统的光束法平差改进

为了消除三维扫描测量机器人系统中工业机器人定位误差对测量结果的不利影响,搭建了多目视觉测量系统对三维扫描测头进行空间同步定位。由于系统中相机与标志点之间的距离变化较大,标志点重投影误差难以评价空间定位误差,另外受相机标定精度影响,光束法平差对三维坐标修正不明显。为解决上述问题,本文改进了光束法平差,在传统光束法平差的误差方程中引入摄影比例尺,再将整体参数的优化分为两步,先修正相机内、外参数,再修正被测点三维坐标,以提升系统的三维重建精度。实验结果表明,在对一维基准尺长度的测量实验中,测量结果与参考值之间的偏差小于0.300 mm,标准差不大于0.110 mm,满足三维扫描测量机器人系统的应用需求。     

雷达-光电经纬仪联合定位模型及误差分析

在现代靶场测量系统中,将不同测量设备测量数据进行融合处理以提高系统的综合测量水平和设备的使用效率。利用部署在光电经纬仪附近的雷达,建立雷达-光电经纬仪联合定位模型,将测角信息和部署在其附近雷达的测距信息进行数据融合,可以得到目标相对于经纬仪的距离,从而确定目标的空间三维位置;分析了定位模型的主要误差来源和典型情况下的误差情况。其结果表明,在典型情况下雷达经纬仪联合定位模型距离定位误差与雷达测距误差基本相当。     

基于多传感器融合信息的移动机器人速度控制方法

为提高移动机器人在复杂环境下的速度控制精度和适应能力,提出了一种基于多传感器融合信息的移动机器人速度控制方法.首先,根据多传感器非线性优化融合理论,通过最小化运动观测残差的方法来构建移动机器人运动状态优化估计模型.然后,对利用单目相机、轮式里程计及惯性测量单元(inertial measurement unit,IMU...