Elasto-geometrical error and gravity model calibration of an industrial robot using the same optimized configuration set

Position error is a significant limitation for industrial robots in high-precision machining and manufacturing. Efficient error measurement and compensation for robots equipped with end-effectors are difficult in industrial environments. This paper proposes a robot calibration method based on an elasto–geometrical error and gravity model. Firstly, a geometric error model was established based on the D-H method, and the gravity and compliance error models were constructed to predict the elastic deformation caused by the self-weight of the robot. Subsequently, the position error model was established by considering the attitude error of the robot flange coordinate system. A two-step robot configuration selection method was developed based on the sequential floating forward selection algorithm to optimize the robot configuration for calibrating the position error and gravity models. Then, the geometric error and compliance coefficient were identified simultaneously based on the hybrid evolution algorithm. The gravity model parameters were identified based on the same algorithm using the joint torque signal provided by the robot controller. Finally, calibration and compensation experiments were conducted on a KR-160 industrial robot equipped with a spindle using a laser tracker and internal robot data. The experimental results show that the robot tool center point error can be significantly improved by using the proposed method.     

基于RobotStudio的机器人上下料工作站设计与仿真

以机器人上下料工作站为研究对象,针对其轨迹优化和自动化生产协调之间难度大的问题,提出了利用RobotStudio仿真软件进行机器人上下料工作站的离线编程和动态模拟.给出了工作站的结构布局及上下料平台的Smart组件设计,结合机器人离线编程对工作站进行了仿真调试.在此基础上,设计出实际的模拟机器人上下料工作站,工作站由双爪机器人、供料单元、机床卡盘、立体仓库及主控PLC等组成.给出了工作站主控系统架构和设备间的通信方式,将仿真工作站的程序导入实际工作站进行设备调试.这种由虚拟仿真到实际设计制造的方式,大大缩短了工作站的开发调试周期,对于传统机械加工类企业进行设备升级改造具有很好的借鉴意义.     

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.     

Decoupling force and motion control in industrial robots

A theoretical approach to force control design for industrial robots involved in surface-following tasks is described in this paper, assuming an infinitely stiff environment. Independent Joint Control techniques, based on standard (PID) algorithms, are adopted for position control. Force control acts as an outer loop, by adding a bias to the position set points in the joint space. A simple model and compensation of the joint flexibility effects, that play an important role in determining the dynamic behavior of the system, are also presented, leading to a force control decoupled from motion control. Some experimental results are discussed, with reference to the industrial robot SMART.     

Posture optimization methodology of 6R industrial robots for machining using performance evaluation indexes

For industrial robots, the relatively low posture-dependent stiffness deteriorates the absolute accuracy in the robotic machining process. Thus, it is reasonable to consider performing machining in the regions of the robot workspace where the kinematic, static and even dynamic performances are highest, thereby reducing machining errors and exhausting the advantages of the robot. Simultaneously, an optimum initial placement of the workpiece with respect to the robot can be obtained by optimizing the above performances of the robot. In this paper, a robot posture optimization methodology based on robotic performance indexes is presented. First, a deformation evaluation index is proposed to directly illustrate the deformation of the six-revolute (6R) industrial robot (IR) end-effector (EE) when a force is applied on it. Then, the kinematic performance map drawn according to the kinematic performance index is utilized to refine the regions of the robot workspace. Furthermore, main body stiffness index is proposed here to simplify the performance index of the robot stiffness, and its map is used to determine the position of the EE. Finally, the deformation map obtained according to the proposed deformation evaluation index is used to determine the orientation of the EE. Following these steps, the posture of the 6R robot with the best performance can be obtained, and the initial workpiece placement can be consequently determined. Experiments on a Comau Smart5 NJ 220-2.7 robot are conducted. The results demonstrate the feasibility and effectiveness of the present posture optimization methodology.     

Reflective workpiece detection and localization for flexible robotic cells

A smart vision system for industrial robotic cells is presented. It can recognize and localize a reflective workpiece, and allows for automatic adjustments of the robot program. The purpose of the study is to improve industrial robots awareness of the environment and to increase adaptability of the manufacturing processes where full control over environment is not achievable. This approach is particularly relevant to small batch robotic production, often suffering from only partial control of the process parameters, such as the order of jobs, workpiece position, or illumination conditions.A distinguishing aspect of the study is detection of workpieces made of diverse materials, including shiny metals. Reflective surfaces are common in the industrial manufacturing, but are rarely considered in the research on object recognition because they hinder many of the object recognition algorithms. The proposed solution has been qualified and tested on a selected benchmark in a realistic workshop environment with artificial light conditions. The training of the object recognition software is an automatic process and can be executed by non-expert industrial users to allow for recognition of different types of objects.     

视觉图像技术与机器人工件抓取的协作应用

工业机器人在抓取环节如果配置机器视觉装置,应用图像处理技术,在抓取效率和准确度方面就有优势。该文介绍机器人功能实训台的工件抓取视觉系统的组成,侧重工件轮廓的图像处理技术,以图像处理作为机器人视觉系统处理的核心目标,将视觉图像技术与机器人工件抓取技术协作应用于工业机器人实训平台的抓取环节,利用工业机器人运动过程中坐标的转换,通过相机的正确标定与抓取动作的共同控制,实现工件的精确定位,达到可靠抓取的目的。总结图像处理技术在工件抓取中的协作应用效果,期待便捷的视觉图像技术与机器人工件抓取的协作应用。     

Robot-process precision modelling for the improvement of productivity in flexible manufacturing cells

Industrial robots are traditionally used at machining cells for machine feeding and workpiece handling. A reassignment of tasks to improve the productivity requires a modelling of the robot behaviour from the point of view of its position precision. This paper characterizes and predicts the precision achievable when drilling with an industrial robot in order to use it in machining operations.Robot behaviour and drilling phenomena are analysed to determine working accuracy and their contribution in position deviation and uncertainty. An efficient model for drilling is developed, applying quaternions and considering the influence of all cutting tool angles, providing a very precise estimation of drilling torques and forces. An innovative model for the robot is developed based on multibody systems, using mixed natural coordinates that enhance the computing and deliver outputs with direct interpretation. Besides, the effect of stiffness is added in joints as additional element.The complete robot-process model shows the significative process influence in working precision against robot influence. This influence is responsible of up to 40% of the total uncertainty. The model and the tests performed show that the deviations and their uncertainties depend strongly on drilling forces and the robot configuration. In the other hand, the model allows to correct the systematic behaviour in robot deviations and improve with that the position tolerance of the holes to be drilled.     

Efficiency evaluation of robots in machining applications using industrial performance measure

The paper is devoted to the robotic based machining. The main focus is made on robot accuracy in milling operation and evaluation robot capacity to perform the task with desired precision. Particular attention is paid to the proper modeling of manipulator stiffness properties and the cutting force estimation. In contrast to other works, the robot performance is evaluated using the circularity norm that evaluates the contortion degree of the benchmark circle to be machined. The developed approach is applied to five industrial robots of KUKA family, which have been ranked for several machining tasks. The validity of the proposed technique was confirmed by experimental study dealing with robot-based machining of circular grooves for several workpiece samples and different locations.     

Dynamic simulation and neural network compliance control of an intelligent forging center

Automation of forging processes is important for both safety and efficiency in today's advanced manufacturing operations. This work supports the development of an Intelligent Open Die Forging System which will integrate state-of-the-art modelling techniques, automatic die selection and sequencing, full system dynamic simulation, automatic machine programming and coordination, and sensor-based process control to enable the production of more general and complex workpiece geometries than are achievable using current forging methods. Effective automation of this open die forging system requires the coordination and control of the major system components: press, robot, and furnace. In particular, forces exerted on the robot through its manipulation of the workpiece during forging must be minimized to avoid damage to the manipulator mechanism. In this paper, the application of neural networks for compliance control of the forging robot to minimize these forces is investigated. Effectiveness of the neural network-based compliance control module is evaluated through a full dynamic system simulation, which will later form a central part of the complete Intelligent Forging System. Dynamic simulation of the robot is achieved using an efficient O(N) recursive algorithm, while material flow of the workpiece is modeled with a finite element approach. Simulation and timing results for the complete processing system for a specific open die forging example are presented.     

基于机器视觉的机器人自动上料系统设计

本文提出一种基于机器视觉的机器人自动上料系统的设计方案。系统利用相机对工件形状、大小和位姿信息进行采集,上位机的图像软件进行处理并与设定好的标准模板进行特征匹配,最后通过PLC控制的工业机器人利用获得的位姿信息进行快速抓取,触摸屏能够作为操作平台和监控设备来保障系统稳定运行。实验结果显示,自动上料系统能够精确抓取物体,减少了上料时间,提高了生产效率。     

Process intermittent measurement of tools and workpieces

This paper describes the application of surface sensing probes in unmanned machining. The aim is to automate tool setting, workpiece alignment, machining allowance test, and also to provide workpiece inspection capability. Special emphasis is given to the mathematical aids for the compensation of the machine tools systematic errors. A hardware-software system has been designed to solve this problem. It is an integrated part of the control unit and executes the necessary transformations of the subsequent numerical control sentences.     

A closed-loop error compensation method for robotic flank milling

Errors of diverse sources prevented industrial robots from being adopted into milling applications. This paper proposes a closed-loop error compensation method for robotic flank milling of complex shaped surfaces. First, the finished surface is measured in situ by a laser tracker based measuring system without unclamping the fixture. Then, the sampled points are mapped into the model reference coordinate system and a deterministic bicubic B-spline surface is fitted to extract the systematic components of the machining errors. Finally, the compensation tool path is directly generated for the mirror symmetry points of the only-systematic-error-contained sample points. The robot motion program is converted accordingly for further machining. The experiment shows that the surface accuracy is improved significantly in terms of the profile error via the proposed error compensation process, which well validates the effectiveness of the method.     

Automation of chamfering by an industrial robot; for the case of hole on free-curved surface

The study deals with the automatic chamfering for the case of hole on free-curved surface on the basis of CAD data, using an industrial robot. As a chamfering tool, a rotary-bar driven by an electric motor is mounted to the arm of the robot having six degrees-of-freedom in order to give an arbitrary position and attitude to the tool. The robot control command converted from the chamfering path is transmitted directly to the robot. From the experimental results, the system is found effective to remove a burr along the edge of a hole on a workpiece with free-curved surface.     

Stereo vision based automation for a bin-picking solution

As flexibility becomes an important factor in factory automation, the bin-picking system, where a robot performs pick-and-place tasks for randomly piled parts in a bin through measuring the 3D pose of an object by a 3D vision sensor, has been actively studied. However, conventional bin-picking systems that are employed for particular tasks are limited by such things as the FOV (Field of View), the shape of landmark features, and computation time. This paper proposes a general-purpose stereo vision based bin-picking system. To detect the workpiece to be picked, a geometric pattern matching (GPM) method with respect to the 2D image with a wide FOV is applied. The accurate 3D pose of a selected workpiece among the pick-up candidates is acquired by measuring the 3D positions of three features in the workpiece using the stereo camera. In order to improve the 3D position estimation performance, the GPM method is also used instead of the stereo matching method. The multiple pattern registration and ellipse fitting techniques are additionally applied to increase the reliability. The grasp position of a workpiece without collision is determined using the pose of the object and the bin information. By using these methods a practical bin-picking strategy is established to operate robustly with minimum help from the human workers in the factory. Through experiments on commercial industrial workpieces and industrial robot, we validated that the proposed vision system accurately measures the 3D pose of part and the robot successfully manipulates the workpiece among randomly stacked parts.     

Updating workpiece geometry using robotic sensor information gathered during contact tasks

During robotic contact tasks, geometric information of the workpiece is used to specify the position of the robot’s hand on the workpiece and the direction of force control. This geometry is idealized in a typical CAD file, but due to manufacturing precision or wear, the actual workpiece geometry is inevitably deviated from the desired geometry. Furthermore, when the workpiece is mounted, position and orientation inaccuracies emerge. In this paper, we investigate two questions: (1) Can the workpiece geometry in the CAD file be used to control a robot in contact with an inaccurately placed workpiece?; and (2) Once the task is performed, how can the robot’s sensor information be used to update the geometry of the workpiece? A methodology is developed to solve robotic control problems with workpiece position and geometry inaccuracies. Once performed, the CAD file image is displaced to fit the sensed trajectory of the robot’s hand. Finally, the workpiece image geometry is modified using a least squares approximation to fit the sensed data more accurately. In the end, the robot performs the contact task while gathering information that is used to update the original CAD file geometry. The methodologies are demonstrated through a simulation experiment that requires a robot to shave a geometrically altered face that is inaccurately positioned.     

Planning and controlling cooperating robots through distributed impedance

This article presents distributed impedance as a new approach for multiple robot system control. In this approach, each cooperating manipulator is controlled by an independent impedance controller. In addition, along selected degrees of freedom, force control is achieved through an external loop, to improve control of the object's internal loading. Extensive stability analysis is performed, based on a realistic model that includes robot impedance and object dynamics. Experiments are performed using two cooperating industrial robots holding an object through point contacts. Force and position control actions are suitably dispatched to achieve both internal loading control and object position control. Individual impedance parameters are specified according to the theoritical stability criterion. The performance of the system is demonstrated for transportation and contact tasks. © 2002 Wiley Periodicals, Inc.     

提高机器人扫描加工系统加工精度的方法

将机器人三维扫描系统应用到工业加工中,建立了机器人在线测量加工系统.利用已知半径的标准球体作为参照工具,提出一种基于几何约束的非线性优化方法.在线精确地标定了便携式三维扫描系统和机器人的位姿关系,提高了测量精度.同时,提出一种使用虚拟刀具工具中心点和预补偿机器人系统误差的方法,提高了机器人的加工精度.对吉他的边缘进行扫描和加工的实验结果表明:该系统具有稳定、高精度、易于自动化等优点.     

Adaptive hierarchical positioning error compensation for long-term service of industrial robots based on incremental learning with fixed-length memory window and incremental model reconstruction

Industrial robots have been extensively used in industry, however, geometric errors mainly caused by connecting rod parameter error and non-geometric errors caused by deflection and friction, etc., limit its application in high-accuracy machining. Aiming at addressing these two types of errors, parametric methods for error compensation based on the kinematic model and non-parametric methods of directly establishing the mapping relationship between the actual and target poses of the robot end-effector are investigated and proposed. Currently both types of methods are mainly offline and will be no longer applicable when the pose of the end-effector in the workspace changes dramatically or the working performance of the robot degrades. Thus, to compensate the positioning error of an industrial robot during long-term operation, this research proposes an adaptive hierarchical compensation method based on fixed-length memory window incremental learning and incremental model reconstruction. Firstly, the correlation between positioning errors and robot poses is studied, a calibration sample library is created, and thus the actively evaluating mechanism of the pose mapping model is established to overcome the problem of the robot’ workspace having a differential distribution of error levels. Then, an incremental learning algorithm with fixed-length memory window and an incremental model reconstruction algorithm are designed to optimize the pose mapping model in terms of its parameters and architecture and overcome the problem that the performance degradation of the robot exacerbates the positioning error and affects the applicability of the pose mapping model, ensuring that the pose mapping model runs stably above the target accuracy level. Finally, the proposed method is applied to the long-term compensation case of a Stäubli industrial robot and a UR robot, and compared to state-of-art methods. Verification results show the proposed method reduces the position error of the Stäubli robot from 0.85mm to 0.13mm and orientation error from 0.68° to 0.07°, as well as reduces the position error of the UR robot from 2.11mm to 0.17mm, demonstrating that the proposed method works in real world scenarios and outperforms similar methods.