基于球杆仪检测信息的并联机构运动学标定

由于并联构型装备难于实现全闭环反馈控制,使运动学标定成为一项具有显著经济价值并能非常有效提高并联构型装备精度的手段,运动学标定通常包括误差建模、测量、辨识和补偿4个环节。基于以上因素,以5自由度混联机械手TriVariant为对象,研究一种基于球杆仪检测信息的运动学标定方法。首先建立球杆仪测量值与影响末端可补偿位姿误差的几何误差源的映射关系,并给出可辨识条件。在此基础上,以误差参数辨识矩阵条件数为评价指标,探讨合理设置球杆仪安装位置和数目的方法。最后,计算机仿真和试验验证了所提出方法的可行性和有效性,并指出仍然需要解决的若干问题。     

2UPR&2RPS型冗余驱动并联机器人的运动学标定

运动学标定能够有效提高并联机器人的运动精度.以一类2UPR&2RPS型冗余驱动并联机器人为研究对象,提出了该类装置的运动学标定方法.通过将误差闭环矢量方程分别投影到运动支链的驱动方向和约束方向建立了该机器人的几何误差模型,并分离出可补偿误差源和不可补偿误差源.基于误差映射矩阵建立了误差灵敏度指标,随后通过灵敏度分析找出了对末端误差影响较大的不可补偿误差源.利用正则化算法建立了基于激光跟踪仪末端位置测量的几何误差辨识模型.标定试验结果表明,所提出的运动学标定方法是有效的.     

基于旋量理论的数控机床几何误差分离与补偿方法研究

针对机床制造和装配过程中产生的几何误差,建立一种通用的、系统的机床几何误差模型与补偿方法。首先以旋量理论与多体运动学理论为基础,从机床单个运动链到机床整体进行分析并建立了一种通用的误差模型,该模型可分离出影响可补偿与不可补偿位姿误差的几何误差源。然后基于得到的12项可补偿几何误差利用激光干涉仪进行几何误差测量、补偿实验。为了验证补偿效果,利用球杆仪进行了补偿前后的对比实验。实验结果表明:经过补偿后机床的垂直度提高了16%,圆度提高了37%。证明了所提出的建模和补偿方法可有效提高机床加工精度。     

Delta并联机构精度标定方法研究

以Delta并联机构为对象,研究一类含平行四边形支链的3自由度并联机构误差建模技术,所建模型可有效分离出影响末端姿态误差的几何误差源。在此基础上提出一种精度标定方法,该方法利用并联机构操作空间与关节空间非线性映射的性质,仅需检测末端沿z向的位置误差、以及在初始位形下的姿态误差便可识别出几何参数,并可通过修改系统输入实现末端位置误差补偿。给出算例以验证该方法的有效性。     

并联机床运动学自标定方法研究

以Stewart型并联机床为对象,研究一种能实现自标定的运动学标定方法,以提高标定效率.在建立两点之间距离误差的基础上,采用哑铃型球杆作为标准的检测量具,并以此建立机床结构参数误差与球杆标准长度之间的误差传递模型.提出了数据自动采集的方案,开发了专用标定软件,实现了数据采集、数据分析处理和机床结构参数补偿的集成.基于提出的方法,利用测头、球杆和为标定而开发的软件,作为加工叶片的Stewart型六自由度并联机床标定的工具.经两次标定,在机床工作空间内,并联机床的运动学定位误差控制在±0.02 mm以内.     

五轴数控机床摆动轴几何误差的测量与辨识

提出一种基于球杆仪的摆动轴几何误差测量和辨识的新方法。通过圆弧测量轨迹测量球杆仪球心在回转工作台上3个安装位置的球心偏差,并利用齐次坐标变换理论建立其几何误差的辨识模型,分两步从球杆仪测量结果中辨识出4项轴线位置误差和6项运动误差。在转摆台式五轴数控机床上采用球杆仪进行实验验证,通过比较误差补偿前后球杆仪的测量值来验证辨识方法的有效性。     

基于球杆仪的五轴数控机床误差快速检测方法

几何误差是五轴数控机床重要误差源,针对传统测量方法仪器昂贵、测量周期长问题,提出基于球杆仪的五轴数控机床几何误差快速检测方法。对于机床的平动轴误差,利用多体系统理论及齐次坐标变换法,建立平动轴空间误差模型,通过球杆仪在同一平面不同位置进行两次圆轨迹,辨识出4项平动轴关键线性误差;针对五轴机床的转台和摆动轴,设计基于球杆仪的多条空间测试轨迹,完整求解出旋转轴12项几何误差。实验结果显示,所提方法获得转角定位误差与激光干涉仪法最大误差为0.001 8°,利用检测结果进行机床空间误差补偿,测试轨迹偏差由16μm降至4μm,为补偿前的25%,验证了方法的有效性。提出的五轴机床几何误差检测方法方便、便捷,适用于工业现场。     

6-PUS/UPS并联机构运动学标定理论与实验研究

基于6-PUS/UPS并联机构,首先建立含结构误差的运动学反解模型;使用遗传算法建立其标定模型,通过Matlab编程验证了模型的正确性和有效性;提出了一种利用球杆仪、高度游标卡尺和双轴倾角传感器配合测量动平台位姿的标定方案;最后进行标定实验及误差补偿,提高了该并联机构的精度。     

一种利用位置误差模型的机器人位姿标定方法

针对机器人位姿标定模型中位置和姿态数据的权重不合理导致参数识别精度低甚至发散问题,给出一种直接基于末端位置坐标测量的机器人位姿标定方法,避免了位置和姿态数据量级不同对参数识别精度的影响。采用指数积方法,建立一种包含3点位置信息的机器人运动学模型。通过对运动学模型取微分,利用指数映射微分公式推导出机器人末端3点位置误差与几何参数误差之间映射关系的显示表达并给出参数误差识别方法。采用激光跟踪仪作为测量设备,以UR5机器人为标定对象进行运动学参数标定和验证试验。试验结果表明,机器人末端位置误差模和姿态误差模的平均值分别降低了90%和92%。     

基于球杆仪的三自由度串联机械臂运动学标定方法研究

考虑所标定机械臂的几何结构特点,采用修正五参数法描述参数误差并建立机械臂末端位置误差模型;在机械臂零位标定基础上,采用单球杆一次安装测得标定所需数据;基于机械臂和球杆仪所组成闭链的几何约束条件和末端位置误差模型建立参数误差辨识模型,并用非线性最小二乘迭代法求得几何参数误差。完成了标定实验,并采用综合误差补偿法进行了机械臂误差补偿。在给定的两条测试轨迹上,球杆长度变化差分别由标定前的0.395 mm、0.456 mm减小到标定后的0.005 mm、0.010 mm。研究表明:该标定方法有效正确,提高了机械臂的位置精度。     

Plane kinematic calibration method for industrial robot based on dynamic measurement of double ball bar

A new calibration method is proposed to improve the circular plane kinematic accuracy of industrial robot by using dynamic measurement of double ball bar (DBB). The kinematic model of robot is established by the MDH (Modified Denavit-Hartenberg) method. The error mapping relationship between the motion error of end-effector and the kinematic parameter error of each axis is calculated through the Jacobian iterative method. In order to identify the validity of the MDH parameter errors, distance errors and angle errors of each joint axis were simulated by three orders of magnitude respectively. After multiple iterations, the average value of kinematic error modulus of end-effector was reduced to nanometer range. Experiments were conducted on an industrial robot (EPSON C4 A901) in the working space of 180 mm × 490 mm. Due to the measuring radius of DBB, the working space was divided into 30 sub-planes to measure the roundness error before and after compensation. The average roundness error calibrated by the proposed method at multi-planes decreased about 21.4%, from 0.4637 mm to 0.3644 mm, while the standard deviation of roundness error was reduced from 0.0720 mm to 0.0656 mm. In addition, by comparing the results of positioning error measured by the laser interferometer before and after calibration, the range values of motion errors of end-effector were decreasing by 0.1033 mm and 0.0730 mm on the X and Y axes, respectively.     

Identification and measurement of geometric errors for a five-axis machine tool with a tilting head using a double ball-bar

Geometric errors are one of the primary potential sources of error in a five-axis machine tool. There are two types of geometric errors: position-dependent geometric errors and position-independent geometric errors. A method is proposed to identify and measure the position-independent geometric errors of a five-axis machine tool with a tilting head by means of simultaneous multi-axis controlled movements using a double-ball bar (DBB). Techniques for identifying position-independent geometric errors have been proposed by other researchers. However, most of these are based on the assumption that position-dependent geometric errors (such as linear displacement, straightness, and angular errors) are eliminated by compensation, once the position-independent geometric errors have been identified. The approach suggested in this paper takes into account the effect of position-dependent geometric errors. The position-dependent geometric errors are first defined. Path generation for circle tests with two or three simultaneous control movements is then carried out to measure the position-independent geometric errors. Finally, simulations and experiments are conducted to confirm the validity of the proposed method. The simulation results show that the proposed method is sufficient to accurately identify position-independent geometric errors. The experimental results indicate that the technique can be used to identify the position-independent errors of a five-axis machine tool with a tilting head.     

基于单目视觉的并联机器人末端位姿检测

高效、准确地检测机器人末端位姿误差是实现运动学标定的关键环节。提出一种基于单目摄像机拍摄立体靶标序列图像信息的末端执行器6维位姿误差辨识方法,构造具有平行四边形几何约束的四个空间特征点,并以平行四边形的两个消隐点为约束,建立空间刚体位姿与其二维图像映射关系模型,实现末端位姿的精确定位,然后以Delta高速并联机器人为对象,进行了运动学标定试验,验证该方法的有效性,为这类机器人低成本、快速、在线运动学标定提供重要的理论与技术基础。     

A systematic approach to identify the error motion of anN-degree of freedom manipulator

A generalised calibration technique for identifying the joint geometric parameters of an N-degrees-of-freedom (d.o.f.) robot manipulator model is presented. The technique is analogous to the synthesising calibration method applied in the calibration of coordinate measuring, machines. It describes the state of each joint by six d.o.f. and assumes rigid-body motion. The initial step in the calibration involves locating the axis of motion of each joint; the axes are then used to extract the kinematic parameters, introduced by Denavit-Hartenberg (D-H). In order to derive the generalised manipulator kinematic equation, the robot model is modified to include the six error motion components associated with each axis. The paper also addresses the problem of identifying the error motion components of each joint, on the basis of a set of measurement of three noncollinear points at the robot end-effector at various joint configurations. Because the technique is based on axis-by-axis calibration, other non-geometric errors such as joint backlash and gear transmission error may also be revealed.     

Machining tests to identify kinematic errors of machine tool table rotation axis based on sensitive directions

Machining tests based on homogeneous transformation matrix approach are relatively complex and time resuming in the mathematical modeling and the implementation of measurement and calculation. A new method is proposed to identify the kinematic errors of the rotation axis of machine tool table by machining tests based on sensitive directions. In order to identify the kinematic errors in the sensitive direction conveniently, a simple mathematical model of the kinematic errors is developed by optimizing the coordinate system settings based on basic kinematic transformation, and the sensitive direction vector was adopted to identify the kinematic errors from the machining errors of the finished workpiece. Experimental results demonstrate that the proposed method can reduce the complexity and time resuming substantially.     

Local POE model for robot kinematic calibration

A robot kinematic calibration method based on the local frame representation of the product-of-exponentials (Local POE) formula is introduced. In this method, the twist coordinates of the joint axes are expressed in their respective local (body) frames. The advantages of this new approach are threefolds: (1) revolute and prismatic joints can be uniformly expressed in the twist coordinates based on the line geometry; (2) the twist coordinates of the joint axes can be set up with simple values because the local frames can be arbitrarily defined on the links; (3) the kinematic parameters described by the twist coordinates vary smoothly that makes the method robust and singularity-free. By assuming that the kinematic errors exist only in the relative initial poses of the consecutive link frames, the kinematic calibration models can be formulated in a simple and elegant way. The calibration process then becomes to re-define a set of new local link frames that are able to reflect the actual kinematics of the robot. This method can be applied to robot manipulators with generic open chain structures (serial or tree-typed). The simulation and experiment results on a 4-DOF SCARA type robot and a 5-DOF tree-typed modular robot have shown that the average positioning accuracy of the end-effector increases significantly after calibration.     

Kinematic errors identification of three-axis machine tools based on machined work pieces

Evaluating machine tool performance under machining conditions is generally used as the final test in machine tool industry. The seventh part of ISO-10791 describes a machining test using the accuracy of a finished work piece to determine the accuracy of three-axis machine tools. However the kinematic errors cannot be distinguished from each other by means of these test pieces. In this paper a new method to identify the kinematic errors of three-axis machine tool is proposed. A set of test pieces are designed where the kinematic errors of a machine tool can be measured separately along X, Y and Z directions. A volumetric error model is also presented based on the measured errors. This method is initially evaluated in virtual environment and then with some test pieces designed for this purpose. The results are compared with the laser interferometry measurements. It is shown that the measured positioning and straightness errors are consistent with the laser interferometry results. Angular errors measured by the test pieces are also complied with the laser interferometry results as long as the angular error magnitudes are large enough.     

可重构混联机械手--TriVariant的误差建模与灵敏度分析

针对少自由度并联构型装备,必须通过误差建模将影响末端可控和不可控误差的几何误差源进行分离,从而指导机构的精度设计和运动学标定的问题,以5自由度混联机械手TriVariant为对象,研究一种少自由度并联构型装备的误差建模方法。该方法可有效分离出影响末端不可控误差的几何误差源,得到由UP支链连架胡克铰的加工和装配误差,以及套筒导轨扭角误差引起的末端姿态误差为不可控误差,从而得到仅需控制恰约束支链的制造和装配误差,便可有效抑制末端的不可控姿态误差的重要结论。在此基础上,借助灵敏度分析方法,在统计意义下定量揭示出上述几何误差源对末端不可控姿态误差的影响。分析结果表明,胡克铰两轴线不相交误差对末端不可控误差的影响最大。     

Geometric error measurement and compensation for the rotary table of five-axis machine tool with double ballbar

This paper proposes a novel measuring method for geometric error identification of the rotary table on five-axis machine tools by using double ballbar (DBB) as the measuring instrument. This measuring method greatly simplifies the measurement setup, for only a DBB system and a height-adjustable fixture are needed to evaluate simultaneously five errors including one axial error, two radial errors, and two tilt errors caused by the rotary table. Two DBB-measuring paths are designed in different horizontal planes so as to decouple the linear and angular errors. The theoretical measuring patterns caused by different errors are simulated on the basis of the error model. Finally, the proposed method is applied to a vertical five-axis machining center for error measurement and compensation. The experimental results show that this measuring method is quite convenient and effective to identify geometric errors caused by the rotary table on five-axis machine tools.