Frequency domain synthesis of trajectory learning controllers for robot manipulators

Trajectory learning control is a method for generating near to optimal feedforward control for systems that are controlled along a reference trajectory in repeated cycles. Iterative refinements of a stored feedforward control sequence corresponding to one cycle of the control trajectory is computed based upon the recorded trajectory error from the previous cycle. Several learning operators have been proposed in earlier work, and convergence proofs are developed for certain classes of systems, but no satisfactory method for design and analysis of learning operators under the presence of uncertainties in the system model have been presented. This article presents frequency domain methods for analyzing the convergence properties and performance of the learning controller when the amplitude and phase of the system transfer function is assumed to be within specified windows. Experimental results with an industrial robot manipulator confirm the theoretical results.     

A new concept of the SCARA robot

Based on the SCARA concept, accepted worldwide, this paper considers the possibility of realizing SCARA with a full circle working area. The basis of the approach is a mechanism with two eccentrically positioned rotating discs instead several tools (hands) is also facilitated. This paper analyzes the advantages of the proposed solution and the possibilities of its realization.     

Design of a PID optimized neural networks and PD fuzzy logic controllers for a two‐wheeled mobile robot

In this paper, two intelligent techniques for a two‐wheeled differential mobile robot are designed and presented: A smart PID optimized neural networks based controller (SNNPIDC) and a PD fuzzy logic controller (PDFLC). Basically, mobile robots are required to work and navigate under exigent circumstances where the environment is hostile, full of disturbances such as holes and stones. The robot navigation leads to an autonomous decision making to overcome an obstacle and/or to stop the engine to protect it. In fact, the actuators that drive the robot should in no way be damaged and should stop to change direction in case of insurmountable disturbances. In this context, two controllers are implemented and a comparative study is carried out to demonstrate the effectiveness of the proposed approaches. For the first one, neural networks are used to optimize the parameters of a PID controller and for the second a fuzzy inference system type Mamdani based controller is adopted. The goal is to implement control algorithms for safe robot navigation while avoiding damage to the motors. In these two control cases, the smart robot has to quickly perform tasks and adapt to changing environment conditions while ensuring stability and accuracy and must be autonomous with regards to decision making. Simulations results aren't done in real environments, but are obtained with the Matlab/Simulink environment in which holes and stones are modeled by different load torques and are applied as disturbances on the mobile robot environment. These simulation results and the robot performances are satisfactory and are compared to a PID controller in which parameters are tuned by the Ziegler–Nichols tuning method. The applied methods have proven to be highly robust.     

Design of robot controllers

The decoupling method is applied to the design of position-speed-acceleration and force/position-speed-acceleration robot controllers. For this purpose, the Cartesian approach and the decoupling method are used to derive the generating rules of the control laws to be implemented in these systems. In this paper, only the case of non-redundant robots is considered.     

FPGA-realization of the kinematics IP for SCARA robot

Microsystem Technologies - In the implementation of robot motion control, it often requires complex forward and inverse kinematics calculation. However, this algorithm requires more CPU time in the...     

SCARA机器人内模控制方法

为了使SCARA机器人在外界干扰和模型不精确的情况下具有优良的轨迹跟踪性能,提出一种基于内模控制原理设计SCARA机器人控制器的方法。采用拉格朗日方法获得SCARA机器人动力学模型,将其作为内模控制的估计模型;选择内模滤波器[f(S)]设计内模控制器[Q(S),]使其满足稳态误差为零的条件,通过推导得出不同输入信号下的SCARA机器人控制律。通过仿真,将其与自适应模糊滑模控制方法进行对比分析,结果表明所提出的方法轨迹跟踪精度高,抗干扰能力强,控制器参数调节简单。     

Evolutionary robot controllers with competitive and cooperative neural networks

This article describes a new approach for control systems for an autonomous mobile robot by using sandwiches of two different types of neural network. One is a neural network with competition and cooperation, and is used for recognizing sensor information where synaptic coupling are fixed. The second is a neural network with adaptive synaptic couplings corresponding to a genotype in a creature, and used for self-learning for the wheel controls. In a computer simulation model, we were successful in obtaining four types of robot with good performance when going along a wall. The model also showed robustness in a real environment. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo Japan, January 15–17, 2001     

Principles and design of model-based robot controllers

Model-based control algorithms for industrial manipulators require the on-line evaluation of robot dynamics and are particularly sensitive to modelling errors. The development of a unifying framework for the analysis and design of model-based robot control strategies is the theme of this paper. In this framework, the practical problems associated with real-time implementation are highlighted and methods to improve the robustness of the closed-loop system are suggested.     

视觉引导技术在SCARA机器人装配任务中的应用

基于实际生产项目,提出了一种针对平面关节型机器人(SCARA)平面装配任务的手眼标定方法。对线性标定法的输出通过多次迭代使得累积误差和逐渐减小,相较于使用线性标定法来进行手眼标定,视觉定位的平均定位误差降低了0. 4 mm,最大定位误差降低了0. 6 mm。在使用SCARA机器人进行毫米(mm)级作业时,使用迭代线性标定法比传统的线性标定法有更高的视觉定位精度。同时,末端执行器完成对目标工件的抓取任务之后,使用解线性方程的思想求解SCARA机器人完成装配任务的末端位姿,通过实际工程项目的验证,装配成功率可达98. 6%。     

一种新的四自由度SCARA机器人手眼标定方法

针对四自由度机器人手眼标定精度不高的问题,提出了基于标定块的手眼标定系统.通过引入亚像素角点提取算法,提取特征点的精确像素坐标;结合机械手平移规则,完成手眼系统旋转矩阵的标定,通过标定块提取机器人第三连杆中心在工作平台上的投影点所对应的世界坐标,计算系统平移矩阵.实验表明:方法不仅提高了手眼系统标定精度,而且简化了特征点世界坐标的提取过程.     

基于模糊PD型输入迭代学习的工业机器人轨迹跟踪控制

针对工程应用中工业机器人的内置控制器在确定其结构和控制参数后一般不能修改的问题,提出一种基于机器人内置控制器的模糊比例—微分(PD)型输入迭代学习轨迹跟踪控制方法。利用跟踪误差及其导数构建控制律,控制参数采用模糊增益调整型进行自整定,无需根据轨迹反复调整,并将迭代学习量叠加到轨迹输入中,通过更新实际轨迹输入来提高目标轨迹的跟踪精度。MATLAB/SIMULINK仿真和六自由度工业机器人实验结果表明:提出的方法能够在不影响机器人内置控制器稳定性的基础上,实现更高精度的轨迹跟踪。     

Structural properties of a flexible-joint robot model with output controllers and some related applications

This paper considers some structural properties of an n-degree-of-freedom flexible-joint robot with a simple stabilizing output controller. It is well known that, in a nonlinear system, global asymptotic stability does not necessarily imply local exponential stability, while the latter property provides an essential tool in studying various control problems. This study shows that for the model under consideration, global asymptotic stability implies local exponential stability. Applications of this result to the topic of small-signal finite-gain L_p stability and to the analysis of the perturbed system are considered. Finally, we show how a local stabilizing controller which is based on position measurements only can be integrated into a strategy that ensures, under some conditions of system uncertainty, set-point regulation (in the global sense) of an uncertain flexible-joint robot. Simulation results, which demonstrate the applications of a control scheme that is presented in this study, are included.     

Design and experimental evaluation of robust controllers for a two-wheeled robot

The paper presents the design and experimental evaluation of two alternative μ-controllers for robust vertical stabilisation of a two-wheeled self-balancing robot. The controllers design is based on models derived by identification from closed-loop experimental data. In the first design, a signal-based uncertainty representation obtained directly from the identification procedure is used, which leads to a controller of order 29. In the second design the signal uncertainty is approximated by an input multiplicative uncertainty, which leads to a controller of order 50, subsequently reduced to 30. The performance of the two μ-controllers is compared with the performance of a conventional linear quadratic controller with 17th-order Kalman filter. A proportional-integral controller of the rotational motion around the vertical axis is implemented as well. The control code is generated using Simulink® controller models and is embedded in a digital signal processor. Results from the simulation of the closed-loop system as well as experimental results obtained during the real-time implementation of the designed controllers are given. The theoretical investigation and experimental results confirm that the closed-loop system achieves robust performance in respect to the uncertainties related to the identified robot model.     

Experimental and statistical determination of the static position repeatability and a recommended specification for a SCARA robot

This paper describes an experiment and the statistical analysis performed to evaluate the repeatability of a SCARA robot and proposes an alternative form of specification for repeatability. Repeatability has been chosen because the precision obtained from teach-and-play-back programming for pick-and-place tasks, which is still widely used, depends primarily upon this performance value. The measuring method uses two theodolites, which though laborious in set-up is nevertheless simple, economical and sufficiently accurate for the purpose intended. The results are used for comparison with the given specification and for studying the influence of factors such as load, speed and spatial location in the working envelope using analysis of variance; the estimate of the repeatability value is calculated using the standard deviations of the measured coordinates of representative points modified by a factor from Student's t curves. From the analysis, it can be inferred that the repeatability value is dependent upon operating speed, load and plane location. The experimental study also points to a possible form of specification. For example, for the specification to be useful in the study of arrangement of feeders of parts to be assembled by the robot and the estimation of throughput given part weight, it could be given in a table form showing the range of the repeatability value for the designed combinations of speed, payload and position in the envelope.     

Development of a flexible autonomous robot without sensors or controllers

Recently, various robots with many degrees of freedom, such as rescue robots and domestic robots, have been developed and used in practical applications. It is difficult to control such robots autonomously in real environments, because in order to control the many degrees of freedom, we have to observe many states, calculate huge amounts of information, and operate many actuators. In this study, we consider a flexible robot without sensors or controllers that can determine the inclination of a slope and climb up the slope. In order to demonstrate the effectiveness of the proposed framework, we have developed a prototype robot and conducted experiments. The result indicates that the robot could determine the inclination and climb up a gentle slope autonomously. Thus, we have realized an autonomous robot that has no explicit sensors or controllers.     

Designing a Fuzzy-like PD controller for an underwater robot

The design of a steering and depth control in terms of course-changing and course-keeping tracking mission and motion of an underwater vehicle is described in this paper. Fuzzy-like proportional derivative (PD) controller is used where the Fuzzy-like part of the controller is optimised based on its structure and parameter design aspects, whereas the scaling factors of the PD part is optimised based on the minimum number of experiments in a real environment. The experiments were planned using Taguchi design of experiments method. The experimental trials and their results are presented and analysed extensively.     

Three methodologies for the calibration of industrial manipulators: Experimental results on a SCARA robot

This article presents and compares three algorithms for the geometric parameter identification of industrial robots to increase its accuracy (static calibration). The estimation is based on the measure of the gripper pose errors when the robot follows suitable trajectories. The algorithms are general and can be applied to any robot providing that its kinematics is known. After a theoretical introduction to the general methodologies, these are applied to a selective compliance assembly robot arm (SCARA) robot analyzing its performance (precision, efficiency). Experimental results obtained with three methodologies are presented and discussed. The measure of the gripper pose error is based on a laser triangulation technique whose working principles are also recalled. © 2000 John Wiley & Sons, Inc.     

A reinforcement learning with switching controllers for a continuous action space

Reinforcement learning (RL) attracts much attention as a technique for realizing computational intelligence such as adaptive and autonomous decentralized systems. In general, however, it is not easy to put RL to practical use. This difficulty includes the problem of designing a suitable action space for an agent, i.e., satisfying two requirements in trade-off: (i) to keep the characteristics (or structure) of an original search space as much as possible in order to seek strategies that lie close to the optimal, and (ii) to reduce the search space as much as possible in order to expedite the learning process. In order to design a suitable action space adaptively, in this article, we propose a RL model with switching controllers based on Q-learning and an actor-critic to mimic the process of an infant’s motor development in which gross motor skills develop before fine motor skills. Then a method for switching controllers is constructed by introducing and referring to the “entropy.” Further, through computational experiments by using a path-planning problem with continuous action space, the validity and potential of the proposed method have been confirmed.     

Digital high-gain PD control of robot manipulators

For all its simplicity, local proportional and derivative (PD) control remains an effective and popular tool in robot manipulation. The analysis of such a control system has usually been based on the assumption that the PD algorithm is implemented continuously. This article explores the issue of digital high-gain PD control on robot manipulators from the viewpoint of singular perturbation. It is shown that the fast subsystem becomes unstable when the gains are high enough, due to the effect of sample-and-hold. The stability is related to the feedback gains, the length of sampling period, the computation time, and the eigenvalues of the mass matrix. With reasonable approximations, simple and explicit stability criteria are derived. It is also shown that when the gains reach the critical values, chattering in the control signal occurs, similar to what happens in a variable structure system with sliding mode. Since the eigenvalues of the mass matrix vary with robot positions, the system stability and control chattering are also affected by the trajectory that the robot is planned to follow. © 1997 John Wiley & Sons, Inc.     

基于PMAC下SCARA机器人的PID参数调节

本文介绍了在使用美国Delta-Tau公司的PMAC控制卡对四轴SCARA机器人进行PID参数调节过程中所遇到典型问题，以及解决方法。