智能制造技术在行业中的应用 第一讲 全智能喷涂线的控制

在喷涂生产线中,采用FX5U、3D质量检测和Python编程,可以快速调节喷枪工作频率、喷涂浓度和范围、喷枪到工件表面直线距离,使得产品复杂表面涂层的厚度均匀美观,成功打造智能制造的成功范例。     

A frequency-domain approach to determining the path separation for spray coating

Many modern spray deposition processes, such as spray painting or coating, are automated by using a robot to move an applicator in a series of passes over the surface being sprayed. Determining the robot path that creates the required coat thickness over the surface can be considered as an optimization problem, which traditionally has been solved in the spatial domain. In this paper, results from sampling theory are used to transfer the problem into the spatial frequency domain, which determines the optimal separation between passes. The paper also shows how angled raster patterns can be combined to provide a continuous path over the surface that generates the required distribution of deposited material. Note to Practitioners-This paper is motivated by the problem of producing a given distribution of coat thickness during an automated spraying or deposition process. The coating is applied by an applicator that is moved by a robot whose path consists of a series of passes over a surface, and the aim is to determine the separation between the passes and the changes to the deposition rate or robot velocity that will produce the required thickness distribution. In many applications, a uniform thickness is required over the surface, but this paper also considers the problem of producing a shaped thickness profile. The analysis uses ideas from Shannon's sampling theorem to move the problem into the frequency domain, which provides a direct link between the Fourier transform of spray footprint on the surface and the separation of passes of the applicator as it moves over the surface. The paper also introduces a scanning strategy that consists of a combination of two sets of angled raster scans. Compared to paths consisting of conventional scans, this has the advantage that it reduces the time that the robot spends off the edge of the surface.     

Process modeling,simulation, and paint thickness measurement for robotic spray painting

An algorithm and a computer program are developed for modeling of the spray painting process, simulation of robotic spray painting, and off‐line programming of industrial robots for painting of curved surfaces. The computer program enables the user to determine the painting strategies, parameters, and paths which will give the desired paint thickness. Surface models of the parts that are to be painted are obtained by using a computer‐assisted design (CAS) software. Models of relatively simple surfaces are formed by using the surface generation tools of the CAD software. For parts with more complex surfaces, point data related to the part is collected by using a laser scanner, and this data is used to form the CAD model of the part surface. The surface is then divided into small triangular elements and centroid coordinates, and unit normals of the elements are determined. Surface data together with the spray distance, painting velocity, and paint flow rate flux are used for simulation of the process and paint thickness analysis. Paint flow rate flux is determined experimentally by using different spray gun settings and painting parameters. During the experiments flat surfaces are painted by using a single painting stroke of the gun. Then, paint thickness measurements are made on the surfaces. It is observed that besides the technical specifications of the spray gun, air and paint nozzles, and paint needle, basic settings like paint tank pressure, spray air pressure, and gun needle‐valve position affect paint cone angle and paint flow rate, which finally characterize the spray painting process. For that reason, settings and parameters should be changed and the painting process should be simulated until an acceptable paint thickness distribution is obtained for the part that is going to be painted. The robot program is then generated in the robot's programming language. Paint thickness distribution on the painted surface is determined by measuring the thicknesses using the robot and the CAD model of the part surface. The thicknesses are measured at the centroids of the surface elements. A measurement probe of the coating thickness measurement gauge is attached to the wrist of the robot by using a feedback/safety adapter designed and manufactured for this purpose. © 2000 John Wiley & Sons, Inc.     

Parameter optimization for spray coating

The aim of planning path-oriented spray-coating processes is to find a time-dependent continuous sequence of spray gun configurations so that a coating of desired thickness is achieved when executing the sequence. A novel approach to solving the planning task, called “geometry-last”, is outlined which leads to a more general gun configuration cover problem. The gun configuration cover problem is to find a finite set of spray gun configurations, which minimizes the error between a target coating and the coating induced by simultaneously activating those configurations. A suitable objective function for gun configuration covers is defined, and algorithmic solutions for the optimization problem are presented, including speed-up by hierarchization and use of graphics hardware. An experimental evaluation shows that good approximations of the desired coatings can be achieved within reasonable computing times. In contrast to other approaches, geometry-last gains additional flexibility required to find complex paths for free-form workpieces.     

基于三步法的机械臂轨迹跟踪控制

考虑机械臂末端轨迹跟踪控制问题,以跟踪逆运动学求解出的末端期望轨迹对应的各关节期望角度为控制目标.设计了一种基于三步法的控制器,该控制器由类稳态控制、可变参考前馈控制和误差反馈控制3部分组成.证明了该控制器可以通过控制机械臂的各关节力矩实现各关节实际角度对期望角度的状态跟踪,进而使得末端轨迹渐近跟踪期望轨迹,并且跟踪误差是输入到状态稳定的.仿真表明基于三步法控制器的空间机械臂末端可以渐近跟踪期望轨迹,并且该算法可以克服系统的末端负载质量变化等不确定性的影响.     

基于全自动热喷涂技术的电力设备零部件涂层制备工艺研究

变电设施常常服役于空气环境中,容易受到腐蚀的影响,对设备进行表面改性处理可以大幅改善设施的防腐蚀性能,提升其使用寿命。全自动热喷涂技术作为一种新型表面改性方式,是通过热源将合金加热至熔融或半熔融状态并涂覆与基体表面的技术。本文对其工艺参数进行了系统研究,发现当喷涂速度为0.1m/s,涂层厚度最大(700μm)、孔隙最小(2.1%)、性能最佳。喷涂距离对涂层孔隙率的影响较大,在距离为180mm,孔隙率达到最低(4.3%),此外还可根据对涂层厚度需求以及孔隙率的大小选择合适的喷涂电压和电流。对最佳参数条件下热喷涂铝涂层的试样进行盐雾试验。发现涂层表面会发生氧化腐蚀,生成以Al(OH)₃为主的腐蚀产物并在涂层表面形成致密的氧化膜。此外,产生的腐蚀产物还可以填补热喷涂过程中形成的孔隙,阻止腐蚀介质继续向涂层内部渗入。     

Robot manipulator control for hazardous waste-handling applications

The U.S. Department of Energy has identified robotics as a major technology to be utilized in its program of environmental restoration and waste management, and in particular has targeted robotic handling of hazardous waste to be an essential element in this program. Successful performance of waste-handling operations will require a robot to perform complex tasks involving both accurate positioning of its end effector and compliant contact between the end effector and the environment, and will demand that these tasks be completed in uncertain surroundings. This article focuses on the development of a robot control system capable of meeting the requirements of hazardous-waste-handling applications and presents as a solution an adaptive scheme for controlling the mechanical impedance of kinematically redundant manipulators. The proposed controller is capable of accurate end effector impedance control and effective redundancy utilization, does not require knowledge of the complex robot dynamic model or parameter values for the robot or the environment, and is implemented without calculation of the robot inverse kinematic transformation. Computer simulation results are given for a 4 degree of freedom redundant robot under adaptive impedance control. These results indicate that the proposed controller is capable of successfully performing tasks of importance in robotic waste-handling applications.     

三维可视化的喷涂机器人离线轨迹规划系统

传统的喷涂机器人采用人工示教的方式生成喷涂轨迹,该方法依赖工人经验,规划时间长,且不能产生最佳轨迹。为克服这些缺陷,提高喷涂机器人的喷涂质量与喷涂效率,文中通过对喷涂机器人喷涂过程建模、喷涂路径规划、喷涂过程仿真进行深入的研究与分析,建立了喷涂机器人离线轨迹规划与仿真系统整体框架。在此基础上,采用MFC和OpenGL开发了完整的离线轨迹规划与仿真系统,该系统能够针对不同的工件生成正确的轨迹,并能够进行三维可视化的仿真及效果显示。     

Torque Optimizing Control with Singularity-Robustness for Kinematically Redundant Robots

A new control method for kinematically redundant manipulators having the properties of torque-optimality and singularity-robustness is developed. A dynamic control equation, an equation of joint torques that should be satisfied to get the desired dynamic behavior of the end-effector, is formulated using the feedback linearization theory. The optimal control law is determined by locally optimizing an appropriate norm of joint torques using the weighted generalized inverses of the manipulator Jacobian-inertia product. In addition, the optimal control law is augmented with fictitious joint damping forces to stabilize the uncontrolled dynamics acting in the null-space of the Jacobian-inertia product. This paper also presents a new method for the robust handling of robot kinematic singularities in the context of joint torque optimization. Control of the end-effector motions in the neighborhood of a singular configuration is based on the use of the damped least-squares inverse of the Jacobian-inertia product. A damping factor as a function of the generalized dynamic manipulability measure is introduced to reduce the end-effector acceleration error caused by the damping. The proposed control method is applied to the numerical model of SNU-ERC 3-DOF planar direct-drive manipulator.     

软体机器人手眼视觉/形状混合控制

当末端带有相机的连续型软体机器人进行作业时,由于避障、安全性等多方面因素,既需要末端相机－机器人系统的视觉伺服,也需要机器人的整体形状控制．针对这个问题,本文提出了一种软体机器人手眼视觉/形状混合控制方法．该方法无需知道空间特征点的3维坐标,只需给定特征点在末端相机像平面的期望像素坐标和软体机器人的期望形状就可达到控制目的．建立了软体机器人的运动学模型,利用该模型,结合深度无关交互矩阵自适应手眼视觉控制和软体机器人形状控制,提出了一种混合控制律,并用李亚普诺夫稳定性理论对该控制律进行证明．仿真和实验的结果均表明,末端相机特征点像素坐标和形状可以收敛到期望值．     

A Lagrangian network for kinematic control of redundant robotmanipulators

A recurrent neural network, called the Lagrangian network, is presented for the kinematic control of redundant robot manipulators. The optimal redundancy resolution is determined by the Lagrangian network through real-time solution to the inverse kinematics problem formulated as a quadratic optimization problem. While the signal for a desired velocity of the end-effector is fed into the inputs of the Lagrangian network, it generates the joint velocity vector of the manipulator in its outputs along with the associated Lagrange multipliers. The proposed Lagrangian network is shown to be capable of asymptotic tracking for the motion control of kinematically redundant manipulators.     

Adaptive unified motion control of mobile manipulators

This paper presents a unified motion controller for mobile manipulators which not only solves the problems of point stabilization and trajectory tracking but also the path following problem. The control problem is solved based on the kinematic model of the robot. Then, a dynamic compensation is considered based on a dynamic model with inputs being the reference velocities to the mobile platform and the manipulator joints. An adaptive controller for on-line updating the robot dynamics is also proposed. Stability and robustness of the complete control system are proved through the Lyapunov method. The performance of the proposed controller is shown through real experiments.     

Kinematic path‐tracking of mobile robot using iterative learning control

This paper develops a kinematic path‐tracking algorithm for a nonholonomic mobile robot using an iterative learning control (ILC) technique. The proposed algorithm produces a robot velocity command, which is to be executed by the proper dynamic controller of the robot. The difference between the velocity command and the actual velocity acts as state disturbances in the kinematic model of the mobile robot. Given the kinematic model with state disturbances, we present an ILC‐based path‐tracking algorithm. An iterative learning rule with both predictive and current learning terms is used to overcome uncertainties and the disturbances in the system. It shows that the system states, outputs, and control inputs are guaranteed to converge to the desired trajectories with or without state disturbances, output disturbances, or initial state errors. Simulations and experiments using an actual mobile robot verify the feasibility and validity of the proposed learning algorithm. © 2005 Wiley Periodicals, Inc.     

基于自适应和神经动力学的轮式移动机器人路径跟踪控制(英文)

本文提出一种自适应和神经动力学相结合的轮式移动机器人路径跟踪控制方法.首先,设计运动学控制器用来获得机器人期望速度;其次,考虑机器人动力学模型参数的不确定性,利用模型参考自适应方法来设计动力学控制规律,使得机器人实际速度渐近逼近期望值;再次,为克服速度和力矩的跳变,加入神经动力学模型对控制器进行优化,并且通过Lypunov理论来证明整个控制系统的稳定性;最后仿真结果表明该控制方法的有效性.     

A case study of two-robot-arm workcell material handling

More problems are involved in collaborating multi-robot-arm systems than in single robot arms. These problems stem from mutual dynamic and kinematic effects between the arms. This work is confined to only the kinematics of two robot arms; other problems like control, force distribution, and so on are not addressed here. A particular case of a material handling problem with two collaborating robot arms loading/unloading long objects from a conveyor is studied. The feasibility of the task from a kinematics point of view, and the necessary conditions and constraints for the relative set-up of the two manipulators are discussed. These conditions originate from the working envelope of the two arms which depends on three factors: the working envelope of each individual arm, the spacing between them, and the dimensions of the workpiece. To assist this study, an efficient algorithm for determining the two-dimensional contours of the workspace of a single arm is included.     

An offset error compensation method for improving ANN accuracy when used for position control of precision machinery

Artificial Neural Networks (ANNs) have recently become the focus of considerable attention in many disciplines, including robot control, where they can be used as a general class of nonlinear models to solve highly nonlinear control problems. Feedforward neural networks have been widely applied for modelling and control purposes. One of the ANN applications in robot control is for the solution of the inverse kinematic problem, which is important in path planning of robot manipulators. This paper proposes an iterative approach and an offset error compensation method to improve the accuracy of the inverse kinematic solutions by using an ANN and a forward kinematic model of a robot. The offset error compensation method offers potential to generate accurately the inverse solution for a class of problems which have an easily obtained forward model and a complicated solution.Now Lecturing in Taiwan.     

Learning Dynamic Obstacle Avoidance for a Robot Arm Using Neuroevolution

Neural networks can be evolved to control robot manipulators in tasks like target tracking and obstacle avoidance in complex environments. Neurocontrollers are robust to noise and can be adapted to different environments and robot configurations. In this paper, neurocontrollers were evolved to position the end effector of a robot arm close to a target in three different environments: environments without obstacles, environments with stationary obstacles, and environments with moving obstacles. The evolved neurocontrollers perform qualitatively like inverse kinematic controllers in environments with no obstacles and like path-planning controllers based on Rapidly-exploring random trees in environments with obstacles. Unlike inverse kinematic controllers and path planners, the approach reliably generalizes to environments with moving obstacles, making it possible to use it in natural environments.     

Direct adaptive impedance control of robot manipulators

This article presents an adaptive scheme for controlling the end-effector impedance of robot manipulators. The proposed control system consists of three subsystems: a simple “filter” that characterizes the desired dynamic relationship between the end-effector position error and the end-effector/environment contact force, an adaptive controller that produces the Cartesian-space control input required to provide this desired dynamic relationship, and an algorithm for mapping the Cartesian-space control input to a physically realizable joint-space control torque. The controller does not require knowledge of either the structure or the parameter values of the robot dynamics and is implemented without calculation of the robot inverse kinematic transformation. As a result, the scheme represents a general and computationally efficient approach to controlling the impedance of both nonredundant and redundant manipulators. Furthermore, the method can be applied directly to trajectory tracking in free-space motion by removing the impedance filter. Computer simulation results are given for a planar four degree-of-freedom redundant robot under adaptive impedance control. These results demonstrate that accurate end-effector impedance control and effective redundancy utilization can be achieved simultaneously by using the proposed controller.     

A general solution for the position,velocity, and acceleration of hyperredundant planar manipulators

A new approach for the solution of the position, velocity, and acceleration of hyperredundant planar manipulators following any twice‐differentiable desired path is presented. The method is singularity free, and provides a robust solution even in the event of mechanical failure of some of the robot actuators. The approach is based on defining virtual layers, and dividing them into virtual/real three‐link or four‐link subrobots. It starts by solving the inverse kinematic problem for the subrobot located in the lowest virtual layer, which is then used to solve the inverse kinematic equations for the subrobots located in the upper virtual layers. An algorithm is developed that provides a singularity‐free solution up to the full extension through a configuration index. The configuration index can be interpreted as the average of the determinants of the Jacobians of the subrobots. The equations for the velocities and accelerations of the manipulator are solved by extending the same approach, and it is shown that the value of the configuration index is critical in maintaining joint velocity continuity. The inverse dynamic problem of the robot is also solved to obtain the torques required for the robot actuators to accomplish their tasks. Computer simulations of several hyperredundant manipulators using the proposed method are presented as numerical examples. © 2002 John Wiley & Sons, Inc.     

Dynamic state feedback control of two cooperative manipulators

Dynamic coordinated control of two robot manipulators that rigidly grasp a common object is studied. A dynamic coordinated control model for the two manipulators is derived that is suitable for system analysis and design in state space. The model takes into account kinematic and dynamic constraints between the two manipulators, and is explicitly described by non-linear state equtions and non-linear output equations in the state space. Since coordinated control requires the control of forces applied to the object by manipulators, the output equations include both position components and force components. While robotic systems with position outputs can be linearized using a static state feedback, systems with force outputs, such as the present two robot system, require a dynamic non-linear state feedback for exact linearization. By using dynamic non-linear feedback, coordinated control of two robotic manipulators is converted into a control problem of linear systems.