Error Modeling and Sensitivity Analysis of a Parallel Robot with SCARA（Selective Compliance Assembly Robot Arm） Motions

Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.     

一种协作机器人位姿重复性优化综合

在给定位姿重复性要求的前提下,寻找各关节随机运动精度的最优分配方案能够使协作机器人设计更加合理,对降低机器人制造成本有重要意义.首先,在机器人位姿重复性分析的基础上,建立了位姿重复性数学模型,该数学模型包含机器人位置重复性和姿态重复性;其次,以协作机器人KUKA iiwa 7为例,以关节运动误差最大化为优化目标,对该机...     

基于广义几何误差模型的微机器人精度分析

提出了一个用于微机器人精度分析的通用方法,该方法以广义几何误差的形式描述各种误差源对机器人本体产生的影响,通过任两座标系间的向后微分关系,利用运动学方程以及并联机构的环路特性,建立了微机器人的广义几何误差模型。基于此模型,对工作空间中的位姿误差进行了仿真分析,验证了该法的有效性。此方法虽然是针对微机器人,但可推广应用到一般并联机器人的误差建模和精度分析。     

基于标定和关节空间插值的工业机器人轨迹误差补偿

轨迹精度是工业机器人重要的动态性能,目前工业机器人的轨迹精度远低于定位精度,提出一种基于机器人运动学标定和关节空间插值误差补偿的方法来提高机器人轨迹精度。基于MD-H方法建立机器人的运动学模型,在此基础上运用机器人微分运动学理论建立末端位置误差模型和轨迹误差模型。为克服最小二乘法等传统方法在数据噪声较大且不符合高斯分布时收敛慢甚至发散的问题,提出一种基于扩展卡尔曼滤波算法的机器人运动学参数辨识方法,实现运动学参数辨识的快速收敛。经过分析发现机器人误差在关节空间具有连续性的特点,为此提出一种关节空间插值误差补偿方法,建立网格形式的误差补偿数据库,并利用关节空间距离权重函数和已知的网格顶点误差计算各控制点的关节转角误差。通过试验对所提出的参数辨识和关节空间误差补偿方法进行了验证,试验结果表明：经过运动学参数辨识和补偿后机器人的绝对定位精度由1.039 mm提高到0.226 mm,轨迹精度由2.532 mm提高到1.873 mm,应用关节空间插值误差补偿后机器人的轨迹精度进一步提高到1.464 mm。     

Elasto-geometrical error modeling and compensation of a five-axis parallel machining robot

Parallel manipulators have the potentials of high efficiency and high precision in the field of machining and manufacturing. However, accuracy improvement of the parallel manipulator is still an essential and challenging issue, encountering two important problems. Firstly, the ignorance of elastic deformation caused by gravity or deviations of static stiffness model restricts further improvement of accuracy. To solve this problem, an elasto-geometrical error modeling method is proposed. The comprehensive effects of structural errors, elastic deformation under gravity and compliance parameter errors on pose deviations are disclosed. On this basis, the identification equation of actual structural errors and compliance parameter errors can be established. Secondly, the ill-conditioned identification matrix and the identification equation with anisotropic residual error can lead to inaccurate identification results. To solve this problem, a weighted regularization method is proposed. The identification equation with isotropic residual error is built, and accurate identification can be realized with the regularization method. Based on the proposed methods, the error compensation experiment is conducted on the prototype of a five-axis parallel machining robot using a laser tracker. Experiment results show that the accuracy of the machining robot is significantly improved after compensation. An M1_160 test piece and an S-shaped test piece are machined and measured to further validate the effectiveness of the proposed methods. The elasto-geometrical error modeling method and the weighted regularization method can be applied to other parallel manipulators’ accuracy improvement.     

一种并联机器人误差综合补偿方法

针对并联机器人轨迹规划和轨迹跟踪过程中,同时存在机构误差引起的期望轨迹与理想轨迹之间的偏差和非线性摩擦、负载变化等扰动因素引起的动态误差,提出一种并联机器人误差综合补偿方法:在轨迹规划过程中,基于并联机器人位姿误差模型将位姿误差补偿转化为驱动杆参数组合优化问题,进而利用粒子群算法寻优驱动杆参数,修正并联机器人期望轨迹;在轨迹跟踪过程中,设计基于自适应迭代学习控制算法的动态误差补偿策略,实现对期望轨迹的有效跟踪。在Stewart平台下基于ADAMS和Matlab进行仿真试验,在轨迹规划和轨迹跟踪过程中,分别修正期望轨迹偏差并补偿轨迹跟踪动态误差,实现并联机器人误差综合补偿。进一步,基于混联机床进行工件加工试验,验证方法对于提高并联机器人工作精度的有效性。     

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。     

基于虚设运动副的并联机器人静态误差建模与标定

基于并联机器人影响系数和虚位移原理,以一般空间并联机器人为例,通过虚设运动副,提出一种并联机器人静态误差建模与分析的通用新方法。该方法用于确定各个原始加工装配误差源对并联机器人末端位姿的独立影响,具有物理意义明确、建模分析便捷等优势。在此基础上,基于虚设运动副建立了3-P(4S)并联机器人各误差映射矩阵,并对该机器人开展了静态误差标定实验研究。实验结果表明,基于该方法标定后,3-P(4S)并联机器人输出定位误差最大值由0.585mm减小到0.142mm,标定后机器人定位精度明显提高,从而验证了该方法的有效性。     

Motion error compensation of multi-legged walking robots

Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot’s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot’s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.     

基于改进IGG3权函数距离误差模型的工业机器人标定

在工业机器人的标定过程中,测量粗差数据会对标定结果精度产生影响,为此,提出了一种基于改进IGG3权函数距离误差模型的工业机器人标定方法,将改进的IGG3权函数最小二乘辨识算法用于工业机器人距离误差标定中,以进一步提高工业机器人的标定精度。以SR4C型工业机器人为研究对象,建立了机器人距离误差数学模型,进行了IGG3权函数最小二乘辨识算法的理论研究。构建了机器人标定实验系统,进行了基于改进IGG3权函数距离误差模型的工业机器人标定实验,实验结果表明,所提方法可有效减小粗差数据对标定精度的影响。该方法可用于工业机器人标定和校准领域,以提高工业机器人定位精度。     

基于改进粒子群算法的并联机器人运动学精度提高新方法

针对并联机器人在基于给定工作任务进行轨迹规划过程中,存在因机构误差引起的期望轨迹与理想轨迹之间的偏差,由此造成并联机器人运动学精度降低的问题,提出了一种并联机器人运动学精度提高新方法。首先将连续工作任务离散化为满足精度要求的若干理想位姿点,在建立并联机器人位姿误差模型基础上,将机构误差项转化为驱动杆误差;基于种群排列熵模型和粒子速度激活机制改进了粒子群算法,并利用改进的粒子群算法组合优化驱动杆参数,补偿并联机器人位姿误差,进而修正期望轨迹以提高并联机器人运动学精度。通过MATLAB和ADAMS仿真验证了所提出方法的可行性和有效性。     

Energy dissipation rate control and parallel equations solving method for planar spined quadruped bouncing robot

This paper continues our investigation into Energy dissipation rate control (EDRC) and Parallel equations solving method (PESM). Our previous works showed how EDRC enables us to provide stable walking or running gaits for legged robots via controlling robot’s loss of energy rate during Impact phases (IP). This is while PESM facilitates the trajectory designing process of the robot’s active joints during each Single support phase (SSP) by solving the robot’s inverse kinematic and inverse dynamic equations in parallel. Even though PESM is very powerful and suitable for both quadruped robot, and despite the under actuation problem at the ankle joint, and biped robots, despite the presence of Zero momentum point criteria (ZMP) at the ankle joint, still, this method is limited to robots just with three and five DoFs. Therefore, the main purpose hereis to show how it is possible to extend the application of PESL to a spined quadruped robot with four DoFs by employment of the Central pattern generator (CPG) controller units and finding a connection among CPG’s output, PESM and the robot’s foot placement. Besides, as EDRC is employed to realize a stable bouncing gait for the robot, a whole numerical study is performed on the robot’s impact dynamic equations to evaluate the effect of spine joint on the robot’s impact dynamics.

     

Offline and online strategies to improve pose accuracy of a Stewart Platform using indoor-GPS

The pose accuracy of a robot manipulator may be improved by assessing and correcting systematic errors. Both offline and online strategies can be considered. To date, there has not been a solution for the online pose error correction of parallel manipulators. Moreover, offline strategies using indoor-GPS as reference measurement system have not yet been investigated. In this paper an optimization-based kinematic calibration method and an online correction technique are proposed and implemented for a low-cost Stewart Platform. In both cases, an indoor-GPS system was used as reference measurement equipment. Performance of both strategies are compared to a kinematic calibration method based on direct parameter measurement. Pose errors are evaluated for each strategy using a robotic total station. Performance of the optimization-based calibration and the online correction technique were similar and better than the direct parameter measurement calibration. Both techniques resulted in average pose errors less or equal to 0.3 mm and 0.05°. The proposed strategies may be adapted to other similar parallel manipulators and are applicable to large sized equipment.     

BP神经网络补偿并联机器人定位误差

为减小机构末端定位误差,提高机器人运动精度,分析了所开发的6-DOF精密并联机器人末端位姿的误差来源及以往误差补偿方法的局限性。通过实际测量末端位姿,在精密定位的局部工作空间内,提出了基于BP神经网络的机器人关节空间误差补偿方法。确定了BP神经网络模型,建立了误差补偿的数据样本,并对数据样本进行了标准化,通过实验对比的方法确定了隐层神经元的个数,同时对网络的推广能力进行了验证。经过误差补偿,6-DOF精密并联机器人的平移定位误差下降了80%,转角定位误差下降了60%。该实验结果表明,基于BP神经网络的误差补偿方法对机器人局部工作空间的补偿具有明显的效果,满足精密并联机器人工作的精度要求。     

Eccentricity estimation with error modeling in dynamic wafer handling

Wafer-handling robots are used to transfer wafers in semiconductor manufacturing. Typically, a pick–measure–place method is used to transfer wafers accurately between stations. The measurement step is performed using an aligner, which is time-consuming. To increase the wafer transfer efficiency, it is desirable to speed up the measurement process or place it in parallel with other operations. Hence, optic sensors are installed at each station to estimate the wafer eccentricity on the fly. The eccentricity values are then used to control the robot to place the wafer directly onto another station accurately without using the aligner. In this paper, the kinematic model of a wafer-handling robot is developed. The errors in the kinematics model are analyzed. A model parameter identification method is proposed to obtain the parameters. A wafer eccentricity identification method is derived to calculate the eccentricity values on the fly. Experiments were performed to validate the proposed methods. The computed eccentricity errors are compared with those obtained by other researchers. The results demonstrated that the kinematics error modeling method can increase the wafer eccentricity identification accuracy. Hence, the developed methods can be applied to estimate the wafer eccentricity on the fly to reduce the wafer transfer cycle time and increase wafer-handling efficiency.     

近似度加权平均插值的机器人精度补偿方法研究

为实现物流包装的身份和受潮信息双重检测,设计了一种新型的低成本无芯片RFID湿度传感器,使用电耦合LC谐振器(ELC谐振器)作为湿度传感器监测目标环境相对湿度、U型环谐振器作为无芯片编码结构识别目标身份。通过射频仿真软件HFSS研究谐振器结构参数与谐振频率的关系,获得相应拟合公式,为结构参数设计提供理论依据,并在此基础上设计了8位编码结构;系统研究不同质量分数的聚乙烯醇(PVA)溶液对湿度传感器感湿灵敏度和感湿范围的影响,研制出8位无芯片RFID湿度传感器。根据散射参量提取法获得了U型环谐振器的有效电磁参数,表明其具有超材料属性。所研究的湿度传感器具有感湿灵敏度高、编码容量大、结构简单等优点,有望在智能包装领域得到应用。     

机器人基座六维力传感器重力补偿研究

机器人基座六维力传感器常受到安装精度和机器人重力影响而出现测量误差。为了解决这一问题,在利用 D-H 法建立机器人位姿模型的基础上,推导出基于最小二乘法的基座六维力传感器静态重力补偿算法。针对算法中需要采集大量机器人位姿数据的问题,采用正交实验法确定样本空间以减少位姿采集量。最后以六自由度协作机器人为例,利用 6 因素 5 水平的正交实验表获取机器人典型位姿,搭建数据采集平台,实现补偿算法所需数据的采集,求解该机器人的基座六维力传感器静态重力补偿矩阵。实验表明,该补偿算法能够有效得到基座六维力传感器测得的误差值。     

A new screw theory method for the estimation of position accuracy in spatial parallel manipulators with revolute joint clearances

This paper presents a novel method based on screw theory for the analysis of position accuracy in spatial parallel manipulators with revolute joint clearances. The method is general, and can tackle with an arbitrary pose error function, expressed as a quadratic function of the end-effector displacement.The method performs a maximization of the pose error function, based on a 2-step computational procedure. The first computational step is analytical and leads to a sub-optimal estimate of the maximum pose error. This analytical solution represents the exact maximum pose error for the calculus of the angular accuracy in the special case of fully translational parallel mechanisms. The second computational step is numerical, and starting from the previous solution, can converge to the exact maximum pose error in a limited number of iterations.The relevance of the method is demonstrated through some application examples, where the worst-case angular and linear position accuracy in translating fully parallel manipulators is determined. As a further contribution, this paper shows how the position accuracy due to joint clearances in parallel manipulators is strictly dependent of the mechanism pose and its association to kinematic isotropy.     

考虑气象因素的农业采摘机器人轨迹纠偏控制方法

为了减少气象因素对农业采摘机器人轨迹的影响,提出了考虑气象因素的农业采摘机器人轨迹纠偏控制方法,以解决机器人位姿精度较低和定位时间较长等问题。采用云储存技术对运动的目标果实进行检测与跟踪。利用改进的蚁群算法规划最优路径,通过 RBF 神经网络最佳逼近算法对动力学方程加以优化,加强其逼近能力,从而完成对采摘机器人轨迹纠偏的控制。实验结果表明,该方法可以有效地提高位姿精度、提高定位成功率、缩短定位时间并获得更为顺畅的采摘路径。     

基于CPA方法的串联工业机器人运动学标定精度试验研究

几何参数误差是影响工业机器人定位精度的主要误差源,约占总误差的80％以上.基于圆点分析法(circle points analysis,CPA)所标定的几何参数与机器人的实际结构相关,并且能够将几何参数误差与其他误差源解耦.研究表明CPA方法的测量策略对其标定精度具有较大影响.针对基于CPA方法的串联工业机器人运动学标...