机械臂D-H参数和减速比几何标定及误差补偿

针对机械臂D-H参数和关节电机减速比不精确导致机械臂绝对定位精度降低的问题,提出了在利用几何分析标定机械臂D-H参数的基础上,通过分析关节实际旋转角度和相应电机编码器码值的线性关系,标定关节电机减速比的方法;针对关节角误差微分补偿法计算量大的缺点,通过推导机械臂末端位姿矩阵误差和关节角误差之间的微分关系建立误差模型,求解关节补偿角,避免了雅各比矩阵的求取,提高了计算效率;最后采用三维激光跟踪仪搭建测量系统,完成了一种6自由度机械臂的标定及补偿实验;实验结果表明,通过参数标定及误差补偿,机械臂的绝对定位误差均值从标定前的2.83 mm和1.14°降低到0.54 mm和0.24°,验证了方法的有效性。     

一种基于指数积的移动机械臂联合标定方法

提出一种基于指数积的移动机械臂联合标定方法,以实现移动平台和机械臂两者间位姿标定与机械臂运动学参数标定模型的统一.机械臂运动学参数标定使用最多的是基于D-H参数法,但D-H参数法无法克服相邻关节平行或接近平行时的奇异性问题,以及建模过程复杂、建模后的模型通用性差等问题.基于指数积的移动机械臂联合标定方法建模时不会因为关节轴平行而出现奇异性问题,建模过程简单.通过对整个系统的运动学方程进行微分运算,获得末端位姿误差和移动机械臂零位状态旋量误差及关节旋量误差的线性化模型.利用伴随矩阵方式建立关节旋量理论值与关节旋量实际值的关系,并通过改变伴随矩阵实现基于最小二乘法的参数辨识计算过程中参数更新.使用高精度激光跟踪仪作为测量工具,通过实验验证所提出方法的有效性.     

排爆机器人机械臂定位精度误差自动补偿方法研究

针对于排爆机器人在进行排除爆破物质时,机械臂不能满足绝对准确的定位要求,位置检测精度与实际距离之间存在一定的误差。为了解决这一问题,提出排爆机器人机械臂定位精度误差自动补偿方法。基于D-H运动模型和微分变换法创建排爆机器人机械臂位姿误差模型,对误差模型进行重复参数分析,去除重复参数获得可辨识的线性方程;在可辨识的运动学参数误差模型线性方程中加入一个增量进行误差补偿。最后通过仿真实验结果表明,所提方法通过对机械臂位姿误差模型进行有效补偿,使排爆机器人机械臂绝对定位精度均值提升1.3mm。     

基于改进型RLM算法的六轴机械臂运动学标定实验

六自由度机械臂为高维性、强耦合的非线性时变系统,其模型较复杂,参数辨识易受外界扰动影响,导致末端绝对定位精度低,精度一致性差等问题。以某型六轴机械臂为研究对象,根据微分运动学原理并忽略高阶项,获得末端线性误差模型,提出了收敛速度快且鲁棒性较强的改进型RLM算法进行几何参数的误差辨识,在此基础上搭建综合标定实验平台,利用静态测量精度较高的API T3三维激光跟踪仪采集工作空间中灵敏度较高的样本位姿点,根据国际标准ISO 9283中的位置精度评价标准,比较标定前后的位置误差分布区间,并对分析结果给出评价和总结,完成六自由度工业机械臂本体标定实验。     

六轴工业机器人的参数辨识方法

机器人末端位姿的精度依赖于各关节几何参数的精度。为了提高机器人的位姿精度,提出了一种简单实用的机器人参数辨识方法。利用D-H 算法建立的机器人运动学方程,得到了末端位姿与各关节参数的关系。为了解决辨识过程中的复杂计算问题,设计了一种采用拆分参数的迭代方法和相应的实验方法,运用激光跟踪仪对位姿进行精确测量,求得实际几何结构参数。实验结果验证了所提出方法的有效性。     

基于PMPSD的工业机器人几何参数标定方法

针对由几何参数不精确引起工业机器人绝对定位精度低的问题,提出一种基于位姿修正位置敏感探测器的几何参数标定方法。通过建立误差运动学模型,使用位置敏感探测器(PSD)装置进行数据采样,利用位姿修正原理对末端激光器位姿和关节转角进行修正,构建模型约束目标函数,运用LM算法计算得到几何参数误差,修正几何参数名义值。实验结果表明,该方法避免了PSD反馈控制,能够快速实现工业机器人几何参数标定,定位平均误差和标准差分别为78.28%、76.38%,有效提高了机器人的定位精度。     

一种激光跟踪仪误差标定装置

激光跟踪仪作为一种精密测量仪器近年来已得到广泛运用,因其精度受环境、仪器自身及操作等因素影响,其测量精度一直难以提升。针对这一问题,本文以激光跟踪仪系统的误差模型为基础,设计了一款激光跟踪仪的误差标定装置,提出基于标准距离的位姿测量误差标定方法,对位姿测量系统误差进行补偿,从而提升激光跟踪仪的测量精度。     

结构光视觉引导的轨迹跟踪系统的标定技术

为实现机械臂对工业现场三维特征点的跟踪,提出一种基于结构光视觉,六轴机械臂的整体标定方法。利用自制平面靶标求取单映射矩阵,根据张正友标定方法标定相机内参以及对应外参,利用LM算法优化参数,根据激光光条在靶标平面的参数方程和对应的外参标定出激光光平面在相机坐标系下的平面方程,通过求解[AX=XB]方程得到相机坐标系与机械臂末端坐标系的齐次变换矩阵[X],并对特定位姿下的工件偏移进行修正。实际测试表明：静态跟踪误差在±1.2 mm,满足工业现场应用要求。     

基于激光靶向跟踪的悬臂式掘进机位姿测量系统研究

掘进机位姿准确快速测量是煤矿巷道智能掘进的前提和基础。目前悬臂式掘进机位姿测量存在非绝对位姿测量、测量精度低、布置复杂或仅能测量少数位姿参数等问题,无法满足智能掘进需要。针对上述问题,在基于激光靶向跟踪的悬臂式掘进机位姿测量方法的基础上,设计了一种基于激光靶向跟踪的悬臂式掘进机位姿测量系统。该系统由激光跟踪装置和激光标靶组成,激光跟踪装置安装在巷道后方,发射激光到安装在悬臂式掘进机机身上的激光标靶上并跟踪激光标靶移动,通过求解激光跟踪装置、激光标靶、掘进机和巷道等坐标系间的转换矩阵即可测得掘进方向位置、偏距、高度、偏向角、俯仰角和翻滚角6个绝对位姿参数,实现了悬臂式掘进机在巷道大地坐标系中绝对位姿的全参数实时测量。分析了该系统的误差影响因素,仿真得到了其误差分布规律：随着掘进距离增加,掘进机姿态测量误差在一定范围内变化,偏距和高度测量误差呈线性增加趋势;在5～80 m测量范围内,掘进机偏向角、俯仰角和翻滚角测量误差分别小于1.4,1,0.03°,掘进方向位置测量误差小于5 mm,偏距和高度测量误差均小于20 mm。利用履带式机器人底盘搭建了位姿测量实验系统,开展了其在模拟巷道中的位姿测...     

工业机器人的形位检测及精度标定研究

针对传统六自由度机器人进行形位分析与标定研究,采用运动学DH参数法建立机器人运动学位姿模型,利用激光跟踪仪进行机器人空间形位的辨识与减速比数据的采集,结合阻尼最小二乘法进行机器人零位与执行器的标定,通过修改控制器中机器人的末端执行器配置参数,完成传统工业机器人的末端位姿误差补偿,提高了机器人的绝对定位精度。     

Kinematic Calibration of a Parallel Manipulator for a Semi-physical Simulation System

In the application of a semi-physical simulation system of a space docking mechanism, the simulation precision is determined by pose accuracy of the parallel manipulator. In order to improve pose accuracy, an effective kinematic calibration method is presented to enable the full set of kinematic parameter errors to be estimated by measuring the docking mechanism’s poses. A new calibration model that takes into account geometrical parameter errors and coordinates transformation errors is derived by using a differential geometry method. Based on the calibration model, an iterative least square algorithm is utilized to calculate the above errors. Simulation and experimental results show the calibration method can obviously improve pose accuracy.     

A monocular vision system for online pose measurement of a 3RRR planar parallel manipulator

In this paper, we develop a monocular vision system for online pose measurement of a 3-RRR planar parallel manipulator (PPM). By combining with a camera with global shutter, an active marker array, an industrial personal computer, and a degenerated perspective-n-points (DPnP) algorithm, a monocular vision measurement system (MVMS) is established. To improve measuring accuracy of the MVMS, factors that cause inaccuracy including the lens distortion, non-perpendicular angle, and input parameters’ uncertainty are analyzed and modeled in detail. In the simulation, effects of these error factors on the accuracy of the MVMS are quantitatively displayed, and comparisons between the DPnP algorithms and other state-of-art PnP algorithms are conducted. Experimental tests on the constructed MVMS demonstrate that it not only can accurately and efficiently measure pose of the 3RRR PPM, but possesses a higher operability and stability compared to the laser tracker.     

Accuracy improvement of a 3D passive laser tracker for the calibration of industrial robots

The laser tracker has been used as the mainstream instrument for the position accuracy calibration of industrial robots for quite a long time. However, due to the complexity of the built-in dual-axis active servo tracking system, its cost is high and the target reflector has to adjust its pose frequently, so it cannot be popularized in the production and application sites of industrial robots. Based on this drawback, a 3D passive laser tracker (3DPLT) with high precision, simple structure, easy operation and low cost is proposed in this paper. Firstly, the overall structure of the system is designed, and its position error model based on the principle of spherical coordinate measurement and vector transfer method is established. Then, the error parameters are identified by experiments to formulate the error compensation model. Finally, the multi-pose and large-range spatial error compensation verification experiments of the system are carried out on a commercial coordinate measuring machine. The results show that the spatial volumetric errors of the 3DPLT can achieve within 40 μm after compensation with a good repeatability of ±4 μm. A comparison contouring test with a commercial ballbar is also carried out to validate its applicability of robot calibration.     

羽毛球机器人机械臂运动轨迹多目标规划

为了实现羽毛球机器人机械臂高速连续平滑地击打羽毛球动作,提出了一种新的多目标机械臂运动轨迹优化模型。首先,该轨迹优化模型根据D-H运动学模型,通过坐标变换建立机械臂的位姿表达式。然后,采用牛顿下山法求出给定路径关键点的运动学逆解集,并基于最短路径算法从逆解集中求出最优解。最后,根据所求出最优解,采用三次样条插值建立电机转角函数,以实现机械臂的连续平滑运动。实验结果表明：新的轨迹优化模型能够有效地降低电机能耗和提高转动效率,从而保证了机械臂响应速度。     

基于免疫进化的并联机器人的位姿估计

提出了一种基于免疫进化算法的并联机器人位姿估计算法。建立了视觉检测坐标系和位姿参数估计模型;借鉴生物免疫系统中克隆变异和免疫记忆机理,通过免疫进化获得位姿参数的可行解。实验表明,相较于传统迭代算法,基于免疫进化算法的位姿检测算法收敛快,精确度高,对噪声不敏感,具有较好的鲁棒性。     

大尺寸复杂形状组合测量系统的全局标定与多视数据融合

为解决大尺寸复杂形状全局测量与局部精度控制的矛盾,提出以大空间测量设备为全局控制手段,集成终端近距离测量设备的组合测量、全局标定与数据融合方法.在多站位下观测测量控制网以获取冗余观测数据,利用测量平差优化技术完成控制网的高精度标定.建立全局测量坐标系与测量控制网的物理关联,实现测量空间基准定义的唯一性.布设扫描仪观测目标并建立基准坐标系,为扫描仪位姿空间定位提供观测目标.建立扫描仪坐标映射模型,基于平差优化技术完成模型的高精度标定.测量过程中通过移动扫描仪获取多视角精密测量数据,利用激光跟踪仪完成局部视角位姿的动态跟踪,结合控制网的坐标观测实现局部视角测量数据的全局标定与数据融合.实验结果表明,所提出的组合测量与标定方法有效地拓展了测量空间并控制了全局测量误差,同时避免了额外标定设备与标定操作的介入对测量工作的干扰.     

A novel kinematic parameters calibration method for industrial robot based on Levenberg-Marquardt and Differential Evolution hybrid algorithm

The poor absolute positioning accuracy of industrial robots is the main obstacle for its further application in precision grinding of complex surfaces, such as blisk, blade, etc. Based on the established kinematic error model of a typical industrial robot FANUC M710ic/50, a novel kinematic parameters calibration method is proposed in this paper to improve the absolute positioning accuracy of robot. The pre-identification of the kinematic parameter deviations of robot was achieved by using the Levenberg-Marquardt algorithm. Subsequently, these identified suboptimal values of parameter deviations were defined as central values of the components of initial individuals to complete accurate identification by using Differential Evolution algorithm. The above two steps, which were regarded as the core of this Levenberg-Marquardt and Differential Evolution hybrid algorithm, were used to obtain the preferable values for kinematic parameters of the robot. On this basis, the experimental investigations of kinematic parameters calibration were conducted by using a laser tracker and numerical simulation method. The results revealed that the robot positioning error decreased from 0.994 mm, initial positioning error measured by laser tracker, to 0.262 mm after calibration with this proposed hybrid algorithm. The absolute positioning accuracy has increased by 40.86% than that of the Levenberg-Marquardt algorithm, increased by 40.31% than that of the Differential Evolution algorithm, and increased by 25.14% than that of the Simulated Annealing algorithm. This work shows that the proposed kinematic parameters calibration method has a significant improvement on the absolute positioning accuracy of industrial robot.