A C5 parallel robot identification and control

The paper proposes a controller scheme based on a priori identification for a C5 parallel robot. First we realize the identification of dynamic parameters of the robot using the Least Squares technique. Different data are used for this step of identification. The cross validation permitted to select and confirm the identified parameters. After, a control scheme (computed torque) is applied to control the C5 parallel robot. The functions of this control scheme are based on precedent identified parameters. In order to reduce the effect of the identification error, we have added a robustness term based on sliding mode technique. The stability of the system in closed loop is presented using the Lyapunov principle. Experimental results of identification and control are presented and show the effectiveness of our methodology.     

A robust adaptive control of a parallel robot

The work presented in this article deals with the robust adaptive control tracking of a 6 degree of freedom parallel robot, called C5 parallel robot. The proposed approach is based on the coupling of sliding modes and multi-layers perceptron neural networks (MLP-NNs). It does not require the inverse dynamic model for deriving the control law. The MLP-NN is added in the control scheme to estimate the gravitational and frictional forces along with the non-modelled dynamic effects. The nonlinearity problem, present in neural networks, is resolved using Taylor series expansion. The proposed approach allows to adjust the parameters of neural network and sliding mode control terms by taking into account a reference model and the closed-loop stability in the Lyapunov sense. We implemented our approach on the C5 parallel robot of LISSI laboratory and performed experiments to observe its effectiveness and the robust behaviour of the controller against external disturbances.     

一种新的六自由度并联机器人分散控制方法

结合六自由度并联机器人机构的特点.提出一种新的分散控制方法.首先依据机构特点指出了关节空间内惯性矩阵块对角占优特性,从而将耦合强烈的邻近支路加以整体考虑,即分散控制3个两输入两输出子系统;然后将惯性矩阵的逆分解为块对角矩阵与耦合矩阵之和,从而得到每个子系统的动力学方程;最后针对子系统负载随机构运动而变化的特点引入线性变参数(LPV)控制方法,降低了使用线性定常控制器的保守性.仿真结果表明了所提出方法的有效性.     

A time-varying geometry modeling method for parts with deformation during machining process

Deformation due to residual stress is a significant issue during the machining of thin-walled parts with low rigidity. If there are multiple processes with deformation during machining, some process suitability issues will appear. On this occasion, the actual geometric state of the deformed workpiece is needed for process adjustment. However, it is still a challenge to obtain the complete geometry information of deformed workpiece accurately and efficiently. In order to address this issue, a time-varying geometry modeling method, combining cutting simulation and in-process measurement, is proposed in this paper. The deformed workpiece model can be reconstructed via transforming the deformed workpiece with only a small amount of the measurement points by superimposing material removal and workpiece deformation simulation according to a time sequence, which takes advantage of the proposed Curved Surface Mapping based Geometric Representation Model (CSMGRM). Machining experiment of a typical structural part has shown that the deformed geometry model of the whole workpiece can be reconstructed within the error of 0.05mm, which is less than one tenth of the finish machining allowance in general cases, and it is sufficient to meet the accuracy requirements for interference or overcut/undercut analysis and process adjustment.     

Decoupling control for spatial six-degree-of-freedom electro-hydraulic parallel robot

This paper presents a decoupling controller equipped with cross-coupling pre-compensation for an electro-hydraulic parallel robot, in order to weaken system dynamic coupling effects usually ignored on the design of advanced controllers and improve system control performance. The mathematical model of the electro-hydraulic parallel robot is built using the Kane method and a hydromechanics approach, and the kinematical model is established with a closed-form solution and the Newton-Raphson method. The feedback linearization theory is applied to reduce coupling effects stemmed from system dynamics of the parallel robot via incorporating force-velocity control with cross-coupling pre-compensations. The control performance involving stability, accuracy, and robustness of the proposed controller for spatial 6-DOF parallel robot is analyzed in theory and experiment. The experimental results illustrate that the proposed controller can highly improve the control performance by weakening system dynamic coupling effects of the electro-hydraulic parallel robot, especially for trajectory tracking performance.     

6-DOF并联机器人并行控制算法与优化

为了实现对6-DOF并联机器人实时在线控制,并能取得良好的控制效果,对其运动控制算法的结构进行了深入剖析与研究,尤其对上平台中心的运动速度和角速度的计算及液压缸各杆的伸长速度计算矩阵进行了细致的研究,提出了并行算法及CPU的优化分配策略,大大提高了并联机器人的实时控制质量.     

GWM-view: Gradient-weighted multi-view calibration method for machining robot positioning

Multi-camera vision is widely used for guiding the machining robot to remove flash and burrs on complex automotive castings and forgings with arbitrary initial posture. Aiming at the problems of insufficient field of vision and regional occlusion in actual machining, a gradient-weighted multi-view calibration method (GWM-View) is proposed for the machining robot positioning based on the convergent binocular vision. Specifically, the mapping between each auxiliary camera and the main camera in the multi-view system is calculated by the inverse equation and intrinsic parameter matrix. Then, the gradient-weighted suppression algorithm is introduced to filter out the errors caused by camera angle variation. Next, the spatial coordinates of the feature points after suppression are used to correct the transformation matrix. Finally, the hand-eye calibration algorithm is implemented to transform the corrected data into the robot base coordinate system for the accurate positioning of the robot under multiple views. The experiment on the automotive engine flywheel shell indicates that the average positioning error is controlled within 1 mm under different postures. The stability and robustness of the proposed method are further improved while the positioning accuracy of the machining robot meets the requirements.     

Dynamic control of a robot manipulator for high-performance conveyor tracking

A new robot control scheme for the specific application to conveyor tracking is presented. To improve the performance of conveyor tracking, the robot arm dynamics is incorporated into the control scheme. The tracking problem for the workpiece on a variable-speed conveyor is formulated as a stochastic optimal tracking problem with specified criteria. Dividing the conveyor speed into the nominal term and the perturbed term, a two-stage control strategy is employed to cope with the nonlinearity and uncertainty of the robot-conveyor system. Simulation results are given to verify the good tracking performance with fast cycle time and high accuracy obtained in a robotic workcell. © 1995 John Wiley & Sons, Inc.     

A high-performance parallel implementation of the certified reduced basis method

The certified reduced basis method (herein RB method) is a popular approach for model reduction of parametrized partial differential equations. In this paper we introduce new techniques that are required to efficiently implement the Offline “Construction stage” of the RB method on high-performance parallel supercomputers. This enables us to generate certified RB models for large-scale three-dimensional problems that can be evaluated on standard workstations and other “thin” computing resources with speedup of many orders of magnitude compared to the corresponding full order model. We use our implementation to perform detailed numerical studies for two computationally expensive model problems: a natural convection fluid flow problem and a “many parameter” heat transfer problem. In the heat transfer problem, we exploit the computational efficiency of the RB method to perform a detailed study of “snapshot” selection in the Greedy algorithm, and we also examine statistics of the output sensitivity derivatives to obtain a “global” view of the relative importance of the parameters.     

A parallel distributed control architecture for multiple robot systems using a network of microcomputers

This paper presents the design and implementation of a parallel distributed control architecture for industrial multiple robot systems. The design methodology is based on a concept of discrete states and actions, and a robotic task is represented as a sequence of primitive actions. For cooperative or exclusive tasks at the synchronous level of multiple robot systems, Petri net representation is applied, and discrete event-driven control is implemented as a data flow network of concurrent processes communicating with each other. Implementation of multiprocessing control on a microcomputer and a network of microcomputers is discussed.     

A test suite for high-performance parallel Java

The Java programming language has a number of features that make it attractive for writing high-quality, portable parallel programs. A pure object formulation, strong typing and the exception model make programs easier to create, debug and maintain. The elegant threading provides a simple route to parallelism on shared-memory machines. Anticipating great improvements in numerical performance, this paper presents a suite of simple programs that indicate how a pure Java Navier–Stokes solver might perform. The suite includes a parallel Euler solver. We present results from a 32-processor Hewlett–Packard machine and a 4-processor Sun server. While speedup is excellent on both machines, indicating a high-quality thread scheduler, the single-processor performance needs much improvement.     

Global G3 continuity toolpath smoothing for a 5-DoF machining robot with parallel kinematics

Toolpath smoothing is an important approach to improve robots’ operational stability and machining quality. Nowadays, the corner rounding smoothing and curve fitting smoothing algorithms are usually adopted to process the linear toolpath segments to improve its continuity. But the high order continuity between the fitted curve and its adjacent curves is difficult to be guaranteed. For parallel machining robots (PMRs), the tangential, curvature and curvature derivative discontinuities at the junction may lead to the self-excited vibration of mechanical structure, consequently the machining efficiency and quality are decreased. Under this consideration, a global G³ continuity toolpath smoothing method for five degrees of freedom (5-DoF) PMRs is proposed. The linear segments toolpath generated by the Computer-Aided Manufacturing (CAM) system is first divided into long linear segments (LLSs) and short linear segments groups (SLSGs) through breakpoint searching. At the junction point, a B-spline transition curve is inserted to blend adjacent toolpaths. For the SLSG, the quintic B-spline is adopted to fit the discrete data points, constraint equations about the derivatives at the start and end points are established to achieve G³ continuity with the adjacent transition curves. Based on the proposed method, the smoothing for two test toolpaths is carried out, and experiments on a 5-DoF PMR are conducted to show the validity of the method in motion smoothness.     

Ontology-based information modeling method for digital twin creation of as-fabricated machining parts

The Digital Twin concept, as the cutting edge of digital manufacturing solution for modern industries, plays a significant role in the Industry 4.0 era. One key enabling technology for developing a DT is the information modeling of physical products, so as to combine the physical world with the cyberspace more extensively and closely. Therefore, the modeling approach to managing as-fabricated data of physical products, which faithfully reflects the product's physical status, emerges to be pivotal. This paper addresses the problem of modeling as-fabricated parts in the machining process, which is difficult to accomplish by relevant methods, and hinders the long-term data archiving and reuse of process data. Furthermore, to fill the gap, an ontology-based information modeling method of as-fabricated parts is proposed as the recommendation to create DTs for as-fabricated parts. It provides a simple and standardized process for companies to create DTs of as-fabricated parts by specifying the information classification, the contents to be modeled and the modeling method. To validate the effectiveness of the proposed approach, a case study is undertaken in an aviation manufacturing plant at last. The result shows that the proposed information modeling methodology is readily to DT creation of as-fabricated parts.     

A noninverting algorithm for path tracking of two cooperating robot arms and its parallel implementation

This paper presents an algorithm for path tracking of two robot arms with end-effectors gripping a common inertial load. The path is generated as a sequence of elementary motions. The most important feature of the present algorithm is that it avoids singularities, because there is no need of using the inverse kinematics. Direction and proximity criteria are introduced. Holonomic constraints are formulated for the position and orientation of the two end-effectors.The application of parallel processing methods to path tracking according to the previous algorithm is presented. The algorithm is implemented in the Alliant FX/80 parallel machine.     

A local method for contour matching and its parallel implementation

This paper presents a local approach for matching contour segments in an image sequence. This study has been primarily motivated by work concerned with the recovery of 3D structure using active vision. The method to recover the 3D structure of the scene requires to track in real-time contour segments in an image sequence. Here, we propose an original and robust approach that is ideally suited for this problem. It is also of more general interest and can be used in any context requiring matching of line boundaries over time. This method only involves local modeling and computation of moving edges dealing “virtually” with a contour segment primitive representation. Such an approach brings robustness to contour segmentation instability and to occlusion, and easiness for implementation. Parallelism has also been investigated using an SIMD-based real-time image-processing system. This method has been validated with experiments on several real-image sequences. Our results show quite satisfactory performance and the algorithm runs in a few milliseconds. Received: 11 December 1996 / Accepted: 8 August 1997     

救灾机器人摆臂驱动系统及其平衡控制方法

针对矿井救灾机器人最大允许体积及质量受限问题,采用单逆变器驱动双电动机形式设计了一种矿井救灾机器人摆臂驱动系统,采取加权求和方法构建了该系统模型,并对该模型双电动机电流关系进行了推导分析。针对煤矿井下复杂工况造成的矿井救灾机器人摆臂负载不一致问题,提出了一种基于有源阻尼机制的矿井救灾机器人摆臂驱动系统平衡控制方法。基于15kW矿井救灾机器人样机对该方法进行了测试,结果表明该方法可在矿井救灾机器人摆臂负载不一致的情况下实现转矩动态匹配。     

Trajectory generation and control of a five-bar-link parallel direct-drive robot

This paper describes a dyanamic learning control method for a five-bar-link parallel direct-drive robot. A new method to generate a complex continuous trajectory in Cartesian coordinates is presented. The trajectory is expressed as a composition of a segment of a parametric free-form space curve. Hosaka's form of the Bezier curve of degree 3, is used in this study. The availability of robot control based on this trajectory is proven through computer simulation.     

农业机器人并联采摘臂视觉伺服控制

介绍了一种基于视觉伺服的农业机器人并联采摘系统,该系统由视觉系统、上位机、下位机、并联机构等4部分组成.视觉系统采集目标图像并传递给上位机,上位机对图像进行处理,识别和定位目标,计算并联机构的运动控制量,通过串口通信发送给下位机,下位机接收到控制量后,根据运动控制量驱动继电器模块作相应的开关动作,完成并联采摘臂的控制.实验证明:该系统对于实现农业机器人采摘作业具有可行性.     

并联机器人基于滑模理论的模糊控制

根据并联机器人控制的特点,运用一种基于滑模理论的模糊控制方法对它进行控制。这种控制算法简单,具有很强的鲁棒性,还能够保证系统的稳定性。仿真结果表明,它对并联机器人的控制具有良好的效果。     

Hybrid moment/position control of a parallel robot

In this paper, a hybrid moment/position controller in task space is proposed for tasks involving a contact between a robot and its environment. We consider a contour-tracking task performed by a six DOF (Degrees Of Freedom) parallel robot. The task space dynamic model of the robot in contact with its environment, seen as a black box, is estimated by a MLP-NN (MultiLayer Perceptron Neural Network). The neural network non-linearity is treated using Taylor series expansion. An adaptation algorithm of the neural parameters resulting from a closed-loop stability analysis is proposed. The performance of the proposed controller is validated on the C5 parallel robot by considering two different environments: rigid and compliant.