移动焊接机器人的坡口自寻迹及算法实现

介绍了具有自寻迹功能的移动焊接机器人的系统组成，在分析移动机器人运动学模型的基础上，讨论了机器人坡口自寻迹的算法以及实现过程，最后重点分析了自寻迹过程中的轨迹规划．试验结果表明：研制的移动焊接机器人能成功地完成焊前的自寻迹任务，误差精度可控制在±1.5mm左右，满足实际焊接工程需要．     

PMSM驱动机器人的FSMC与EPCH协同控制

单独一种控制方法难以使机器人末端快速、准确地跟踪位置变化,针对这一问题,提出了模糊滑模(FSMC)信号控制与误差端口受控哈密顿(EPCH)能量控制的协同控制策略.FSMC解决了系统动态时的快速性问题,EPCH控制解决了系统稳态时的准确性问题.设计了基于误差的协同函数,利用协同函数来实现对机器人关节系统的协同控制,使机器...     

基于人工智能的图书馆书籍定位机器人自动化控制系统设计

为提高图书馆书籍定位精度，提升图书馆智能化服务质量，设计基于人工智能的图书馆书籍定位机器人自动化控制系统。将该系统整体分为人机交互层、行为评估层、运动规划层以及机器人执行层，通过自主控制器控制机器人执行层的机器人在远程端、本地端两种控制模式下的运动状态，实现机器人的位姿控制。在执行层中，引用Roberts算子完成对彩色图像的灰度处理，在自主控制器中设有基于粒子滤波的重定位增强方法，实现机器人对书籍的精定位。测试结果显示，该系统控制下书籍定位误差均低于2.5 mm，可精准识别作业环境区域，同时位姿角控制精度高，可自主躲避突发闯入行人，避障精准度可达到98%。     

机器人辅助微创全膝关节置换手术系统

开发了面向全膝关节置换手术的机器人辅助截骨系统,实现了膝关节解剖结构精准建模、术前截骨路径3维规划、图像配准以及术中机器人可视化导航.采用多模态图像融合与主动轮廓模型分割技术实现了包含关节软骨在内的膝关节自动化建模与可视化;在此基础上采用3维交互技术实现截骨路径的术前规划;术中基于自主研发的双目视觉跟踪系统,采集关节骨表面3维点云与术前3维模型进行形状配准,完成图像空间和机器人空间之间的映射;最后通过视觉导航技术引导机器人完成截骨操作.实验结果表明,机器人系统综合定位误差为0.87 mm,截骨操作误差小于1 mm.     

基于点线特征的解耦视觉伺服控制方法

针对机器人的自动对准问题,提出一种基于点线特征的解耦视觉伺服控制方法。所提方法以点和直线作为图像特征,并利用图像特征的交互矩阵解耦姿态控制和位置控制,实现六自由度对准。首先利用直线及其交互矩阵设计姿态控制律,以消除旋转偏差;然后利用点及其交互矩阵设计位置控制律,以消除位置偏差;最后实现机器人末端目标的自动对准。在对准控制过程中,基于执行的相机运动量以及相机运动前后特征的变化量,可实现对深度的在线估计。另外,还设计了监督器对相机的运动速度进行调节,从而确保特征一直处于相机视野当中。在Eye-in-Hand机器人平台上,分别用所提方法和传统的基于图像的视觉伺服方法实现了机器人的六自由度对准。所提方法经过16步实现了机器人的自动对准,对准结束时机器人末端位姿的最大平移误差为3.26 mm,最大旋转误差为0.72°。相较于对比方法,该方法的控制过程更加高效,控制误差收敛更快,对准误差更小。实验结果表明,所提方法可以实现快速高精度的自动对准,能够提高机器人操作的自主性和智能化水平,有望应用于目标跟踪、拾取和定位、自动化装配、焊接、服务机器人等领域。     

可运动解耦的连续体单孔手术机器人设计与控制

提出一种可拓扑解耦的连续体单孔手术机器人,通过设计中间联动连续体段可以实现多段驱动间的解耦,并且机器人的末端姿态仅取决于远端形变段,实现了位姿分离.基于该运动解耦构形,设计了一种基于空间十字交叉曲面盘的连续体骨架结构来实现具有6自由度的多段连续体机器人,建立了机器人的正运动学,并给出了逆运动学的直接求解法.最后进行了机器人驱动解耦与轨迹跟踪控制实验,经过测试,机器人解耦运动的平均角度误差为2.39?,在20 mm/s的速度及无负载条件下轨迹跟踪误差为1.46 mm.实验表明机器人具有较好的驱动空间解耦能力,并能够基于逆运动学直接求解法实现机器人稳定的运动控制.     

基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统设计

为了保证机器人能够在保持稳定的情况下,按照规划轨迹执行工作任务,从硬件和软件两个方面,设计了基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统。装设机器人传感器与状态观测器,改装机器人鲁棒滑模跟踪控制器,完成系统硬件设计;综合机器人结构、运动机理和动力机制3个方面,构建机器人数学模型;根据状态数据采集结果与规划轨迹之间的偏差,计算机器人跟踪控制量;依据滑模运动与切换方程,利用Sigmoid函数生成机器人鲁棒滑模控制律,将生成控制指令作用在机器人执行元件上,实现系统的鲁棒滑模跟踪控制功能;在系统测试与分析中,所设计控制系统的平均位置跟踪控制误差为0.93 mm,与设定轨迹目标基本重合,机器人姿态角跟踪控制误差为0.06 mm,具有较好的鲁棒滑模跟踪控制效果,能够有效提高机器人鲁棒滑模跟踪控制精度。     

西红柿采摘机器人视觉系统的设计与研究

设计、开发了西红柿采摘机器人的双目立体视觉系统,为机器人自动化采摘作业提供条件。采用VFW方法进行了实时采集系统的设计;基于成熟西红柿与背景之间颜色特征的差异信息进行图像分割来识别成熟西红柿;在摄像头标定和形心匹配的基础上,通过三维立体重建获取了西红柿果实的空间位置信息。实验结果表明:视觉系统的成熟果识别率可达到98%,图像分割识别整个过程消耗平均时间0.21s;当工作距离小于500mm时,除个别奇异点,测试距离误差绝对值可控制在14mm以内,能较好满足实际工作需要。     

基于误差补偿的移动式双臂协作机器人自适应协同装配均衡控制方法

为了提高移动式双臂协作机器人的自适应协同控制能力,提出基于反馈调节均衡误差补偿的移动式双臂协作机器人自适应协同装配均衡性控制技术。构建移动式双臂协作机器人控制约束参数和对象模型,采用空间规划和负荷均衡调节方法,实现对移动式双臂协作机器人的自适应参数融合和控制量优化辨识,通过随机负荷误差补偿的方法构建移动式双臂协作机器人自适协同装配过程中的均衡参数集,结合模糊度检测和自适应跟踪补偿方法,构建移动式双臂协作机器人的自适应均衡控制模型,根据参数寻优结果,实现对移动式双臂协作机器人自适应协同装配过程中的反馈调节均衡误差补偿,提高装配的稳定性和可靠性。仿真结果表明,采用该方法进行移动式双臂协作机器人自适应协同装配控制的输出均衡性较好,误差补偿能力较强,提高了机器人控制的稳定性和鲁棒性。     

机器人轨迹纠偏控制方法研究

为减小机器人在执行轨迹跟踪任务过程中末端产生的位姿误差,在建立机器人轨迹纠偏系统模型的基础上,提出了一种积分型纠偏控制器实现方案.该方案直接在机器人的关节空间上对误差进行补偿.基于前述模型和一系列假设,首先从数学上证明了比例-积分纠偏控制器能够使纠偏误差以负指数收敛,进而说明积分型纠偏控制器的有效性.实验结果表明:通过设置合适的参数,在初始轨迹最大偏差为8 mm的情况下,纠偏控制后偏差均方根值小于0.07 mm,最大值小于0.4 mm.     

Intelligent hierarchical robot control for sewing fabrics

In this paper an intelligent hierarchical controller for the robotized sewing of two plies of fabrics is presented. The proposed system is based on the concept: fabric properties estimation – tensional force determination – sewing – adaptation. A new methodology for integrating the tensile test of fabrics into the robotic sewing station using the sewing machine is presented. The output of this test is the estimation of the fabrics extensibility, which is fed to the next level of decision making to determine the appropriate fabric tensional force that should be applied during the sewing process. Computational intelligence methods (fuzzy logic and neural networks) have been used throughout the hierarchical structure of the controller. The present research is focused on the concept of using qualitative properties of the fabrics and the processing of qualitative and quantitative knowledge in different levels of the introduced hierarchical system. The proposed system is flexible, adaptable and robust enough to sew a wide range of unknown double ply of fabrics as it is shown by the test results. It has also the capability of on-line and endless training in order to be able to respond, handle and sew new types of fabrics. Seams that are produced by the robot and a human operator for joining two pieces of fabrics are presented and compared.     

Guidelines to sewing machine workstation design for improving working posture of sewing operator

Sewing machine operators suffer from musculoskeletal problems imposed due to constrained restricted body postures. This study was conducted to investigate the effects of three design parameters (fore/aft sewing distance, sewing desk inclination and sewing desk height) of sewing workstation on postural variables and subjective experience and to develop guidelines for sewing workstation design. At a prototype of adjustable sewing workstation, ten professional sewing machine operators performed sewing task in nine different workstation arrangements. Sewing machine operators working posture and perceptions were recorded. It was shown that trunk, neck and arm postures were influenced by fore/aft sewing distance, sewing desk inclination and sewing desk height. The determinant factor for sewing machine operators’ perception on the trunk and neck found to be fore/aft sewing distance, sewing desk inclination. The sewing desk height influences the arm posture significantly. Based on the results, the following guidelines were developed: (1) Fore/aft sewing distance should be adjusted to 140 mm towards the sewing operator; (2) a 10° sewing desk inclination towards sewing should be used at sewing workstations. (3) Sewing desk height should be adjusted between 762 mm and 787 mm from the ground.     

Precise and smooth contact force control for a hybrid mobile robot used in polishing

Contact force is dominant in robotic polishing since it directly determines the material removal. However, due to the position and stiffness disturbance of mobile robotic polishing and the nonlinear contact process between the robot and workpiece, how to realize precise and smooth contact force control of the hybrid mobile polishing robot remains challenging. To solve this problem, the force tracking error is investigated, which indicates that the force overshoot mainly comes from the input step signal and the environmental disturbance causes force tracking error in stable state. Accordingly, an integrated contact force control method is proposed, which combines feedforward of the desired force and adaptive variable impedance control. The nonlinear tracking differentiator is used to smooth the input step signal of the desired force for force overshoot reduction. Through modeling of the force tracking error, the adaptive law of the damping parameter is established to compensate disturbance. After theoretical analysis and simulation verification, the polishing experiment is carried out. The improvement in force control accuracy and roughness of the polished surface proves the effectiveness of the proposed method. Sequentially, the proposed method is employed in the polishing of a 76-meter wind turbine blade. The measurement result indicates that the surface roughness after mobile robotic polishing is better than Ra1.6. The study provides a feasible approach to improve the polishing performance of the hybrid mobile polishing robot.     

Fuzzy Logic Decision Mechanism Combined with a Neuro-Controller for Fabric Tension in Robotized Sewing Process

A new approach for flexible automated handling of fabrics in the sewing process is described, which focuses to control the cloth tension applied by a robot. The proposed hierarchical robot control system includes a Fuzzy decision mechanism combined with a Neuro-controller. The expert's actions during the sewing process are investigated and this human behavior is interpreted in order to design the controller. The Fuzzy Logic decision mechanism utilizes only qualitative knowledge concerning the properties of the fabrics, in order to determine the desired tensional force and the location of the robot hand on the fabric. A Neural Network controller regulates the fabric tension to achieve the desired value by determining the robot end effector velocity. The simulation results demonstrate the efficiency of the system as well as the robustness of the controller performance since the effects of the noise are negligible. The system capabilities are more evident when the controller uses its previously acquired experience.     

基于三坐标测量机的机器人位姿精度检测方法

针对医疗场合导航引导下的手术机器人定位精度检测问题,提出了基于三坐标测量机的机器人位姿距离精度测量方法。该方法通过放置在一个平面上的三个标准球来实现三坐标测量机对姿态精度的测量,并参照机器人辅助外科手术系统的定位原理构建基于三坐标测量机的机器人位姿检测平台。在此基础上,依据国家标准规定的机器人性能检测方法和过程,完成机器人位姿距离精度的测量。通过该方法对研发的骨科手术定位机器人进行测量的结果表明,所设计机器人位置距离准确度和重复性分别在[10-1]mm和[10-2]mm级别,姿态距离准确度和重复性分别在[10-1]度和[10-2]度级别。最后将该机器人应用于前交叉韧带重建手术实验,结果表明通过这种方法检测的机器人能够满足手术场合要求。     

人与机器人共存中的位姿估计与碰撞检测

提出了一种人与机器人共存中的位姿估计与碰撞检测方法。首先,利用光学3维动作捕捉系统获取标记点位姿信息,建立人体手臂的运动学模型。其次,针对工作空间中障碍物遮挡导致部分标记点位姿信息丢失的问题,将角度传感器获取的肘关节角度作为人体手臂运动学模型的输入,获取人体手臂末端位姿信息。再次,构建人体手臂和协作机器人的胶囊体模型,计算各胶囊体之间的最短距离,从而判断人机的相对位姿关系并实现碰撞检测。最后,通过10个人在不同人机共存场景下对人机位姿估计与碰撞检测方法进行评价。实验结果表明,本方法估计的人体手臂末端位置误差在20mm以内,人机最短距离的最大误差为14.53mm,能够实现人机碰撞检测。     

机器人力控制器的鲁棒性设计及其在装配作业中的应用

当机器人与外界环境发生接触时,接触刚度等不确定性因素对机器人力控制系统的稳定性有很大影响。为了解决这个问题,本文根据变结构控制理论设计了一个机器人力控制器,并提出了一种旋转滑动平面的自适应算法,以加快系统状态的收敛速度和保证收敛过程的鲁棒性。装配实验结果表明,利用本文的方法所设计的机器人力控制器对接触刚度的变化具有很好的鲁棒性。     

Accuracy analysis in mobile robot machining of large-scale workpiece

Mobile robot machining provides more flexible machining mode compared to the robot machining with a fixed base. However, its machining accuracy is frequently questioned. This paper focuses on the accuracy analysis in mobile robot machining. To evaluate the machining error qualitatively, the tool center point (TCP) error index is defined as the distance between the TCP and the designed machining point. The different error sources acting on the TCP error index are enumerated, and the theoretical accuracy analysis is proposed to eliminate the TCP error. The mobile robot machining strategy is then proposed based on the accuracy analysis. To ensure high machining accuracy, the global measurement system locates the position of the workpiece and the mobile platform. The force-controlled grinding head is used to compensate the TCP error. Experimental results show that the TCP error during mobile robot machining is lower than 40 mm, which mainly introduced by the calibration of the workpiece. The force-controlled grinding head can compensate the TCP error and the fluctuation of the grinding force under the control is lower than ±2 N.     

基于目标检测的机器人手眼标定方法

智能协作机器人依赖视觉系统感知未知环境中的动态工作空间定位目标,实现机械臂对目标对象的自主抓取回收作业。RGB-D相机可采集场景中的彩色图和深度图,获取视野内任意目标三维点云,辅助智能协作机器人感知周围环境。为获取抓取机器人与RGB-D相机坐标系之间的转换关系,提出基于yolov3目标检测神经网络的机器人手眼标定方法。将3D打印球作为标靶球夹持在机械手末端,使用改进的yolov3目标检测神经网络实时定位标定球的球心,计算机械手末端中心在相机坐标系下的3D位置,同时运用奇异值分解方法求解机器人与相机坐标系转换矩阵的最小二乘解。在6自由度UR5机械臂和Intel RealSense D415深度相机上的实验结果表明,该标定方法无需辅助设备,转换后的空间点位置误差在2 mm以内,能较好满足一般视觉伺服智能机器人的抓取作业要求。