机械手轨迹规划的神经网络逆模控制

针对二自由度机械手动力学模型的非线性和参数的不确定性,提出了一种神经网络与逆模控制相结合的控制策略。针对传统BP算法在神经网络训练后期收敛速度慢且容易陷入局部极小的缺点,提出一种快速启发式学习算法。采用所提出的快速启发式网络学习算法训练多层前馈神经网络,建立机械手的逆动力学模型,实现对机械手的非线性控制。仿真结果表明了所提出控制策略的有效性和快速启发式网络学习算法的快速收敛性。     

考虑驱动系统动态的机械手神经网络控制及应用

针对结构和参数均未知的机械手控制问题, 提出了考虑驱动系统动态的机械手神经网络控制方法, 采用稳定的径向基(Radial basis function, RBF)神经网络辨识机械手未知动态, 而附加的鲁棒控制可以保证存在神经网络的建模误差和外部干扰时系统的稳定性和性能, 并且该方法使机械手闭环系统一致最终有界. 同时开发了基于半实物仿真技术的机械手控制系统, 最后, 将本文方法与经典的PD控制器和自适应控制器在同一机械手平台上进行了实验验证与分析, 实验结果表明该方法具有良好的控制性能.     

基于改进自构形学习算法的RBF网络结构优化

RBF网络中的隐层神经元的数目直接影响着整个网络的性能和效率,因而对RBF网络的结构优化是一个非常必要的环节。本文先采用分步式训练构造初始RBF网络,然后利用改进的神经网络自构形学习算法对所构造的RBF网络的隐层进行优化,最后通过实验结果的分析与对比,验证改进的神经网络自构形学习算法对RBF网络优化的有效性。     

欠驱动机械手的非线性补偿控制的实现

以具有欠驱动关节的水平两自由度机械手为对象,建立了其动力学数学模型。对具有非完全约束机器人的特点进行了分析。利用解非线性方程的有效方法一平均值法对模型进行了处理,得到平均值系统,使模型得到简化。含有非驱动关节的平面二自由度机械手具有不可积分的速度和加速度束。因而是一个二阶非完整系统。通过分析系统的动力学机构,设计了一种非线性补偿控制的方法来对欠驱动关节实现控制。实验结果表明。该控制方法在控制模型、控制算法和反馈控制方法上都是十分有效的。     

基于RBF神经网络逆系统的机械手解耦控制策略

针对机械手系统具有非线性时变、多变量、强耦合的特点,提出一种基于RBF神经网络逆系统的机械手解耦控制策略。首先证明了系统的可逆性,进一步通过神经网络在线逆辨识建立机械手的神经网络逆系统模型,并将辨识得到的逆模型作为控制器模型与机械手系统串联,构成伪线性复合系统,实现了将具有强耦合特性的多变量输入/输出机械手系统解耦成单个独立的伪线性对象。最后以两关节机械手为仿真对象进行了仿真,仿真结果验证了本方案的有效性和可行性。     

多自由度分拣机械手位置的PLC控制仿真

机械手具有能不断重复工作和劳动的特点,由于其本身的结构刚度和接触刚度较低时,容易产生振动。为了获取良好的机械手位置控制结果,提出一种基于PLC的多自由度分拣机械手位置控制方法。分析多自由度分拣机械手的运动方式,通过Burg算法对机器人运动想象原始脑电数据滤波处理,提取和运动想象相关的频段。多自由度分拣机械手信号经过小波分解处理后获取小波系数,将其和运动想象频段两者相互对应的时域信息输入共空间模式,完成脑电信号的预处理和特征提取。将机器人运动想象任务转换为控制命令输入到PLC控制器中,使其可以驱动电机,同时利用传感器完成机械手位置控制。实验测试结果表明,所提方法控制机械手的真实轨迹跟踪与期望轨迹基本一致,跟踪轨迹的误差小,表明所提方法能够精准完成机械手的位置控制。     

基于Lasso稀疏学习的径向基函数神经网络模型

传统径向基函数(RBF)神经网络模型使用完整的隐含层节点进行模型构建时,会因缺乏隐含层节点抽取机制而使得受训模型的泛化性能下降,导致模型更加复杂。为此,提出一种改进的RBF神经网络模型。通过Lasso稀疏约束对隐含层节点和输出层连接权值进行稀疏表示,去除冗余和不相关隐含层节点的同时保留重要的隐含层节点,并使用交叉验证和网格搜索确定收缩参数以优化模型分类性能。实验结果表明,与现有RBF神经网络模型相比,该模型具有更低的计算复杂度和更高的分类精度。     

改进人工蜂群算法优化RBF神经网络的短时交通流预测

为了提高径向基函数RBF神经网络预测模型对短时交通流的预测准确性,提出了一种基于改进人工蜂群算法优化RBF神经网络的短时交通流预测模型。利用改进人工蜂群算法确定RBF网络隐含层的中心值以及隐含层单元数,然后训练改进的人工蜂群算法RBF神经网络预测模型,并将其应用到某城市4天的短时交通流量数据的验证。将实验结果与传统RBF神经网络预测模型、BP神经网络预测模型和小波神经网络预测模型进行了比较。对比结果表明,该方法对短时交通流具有更高的预测准确性。     

基于RBF的船用污水处理装置运行状态在线监测研究

应用径向基函数RBF神经网络对船用污水处理装置运行状态在线监测,以提高船用污水处理装置运行状态监测与管理的效率。在分析了RBF神经网络原理的基础上,研究一种监测船用污水处理装置运行状态的三层径向基神经网络。通过实际在线监测数据的RBF神经网络监测训练和实验验证,表明RBF神经网络对运行状态的分类效果较佳,能够有效地监测船用污水处理装置的状态,并为装置维修提供科学的决策支持。     

基于局部模型逼近的一种绳牵引并联机器人自适应径向基神经网络控制

为了保证风洞试验绳牵引并联机器人(WTT–WDPR)末端执行器的位姿,提出了一种基于局部模型逼近的自适应径向基(RBF)神经网络控制.采用牛顿–欧拉法建立了飞机模型的动力学方程,并基于动态力矩平衡方程建立了驱动系统的动力学方程.采用RBF神经网络进行了局部模型的逼近设计和控制律设计,并通过构建Lyapunov函数对系统进行了稳定性分析,结果证明WTT–WDPR是趋于渐进稳定的.对WTT–WDPR进行MATLAB/Simulink仿真实验,仿真结果验证了所设计的自适应RBF神经网络控制的正确性和可行性,满足系统控制精度的要求,也为在样机上进行实际应用和技术实现奠定了理论基础.     

Kinematics of mobile manipulators and implications for design

A systematic, unified kinematic analysis for manipulator arms mounted to mobile platforms is presented. The differential kinematics for the composite system is used, along with an extended definition of manipulability, to generate a design tool for this class of systems. An example is presented in which a 3 DOF anthropomorphic manipulator is mounted on a platform powered by two independent drive wheels. Scaled manipulability ellipses are used to visualize the effect of manipulator mounting position on the overall mobility of the system. Given information about the intended tasks of the mobile manipulator, conclusions may be drawn as to the most appropriate mounting site. For the tasks which motivated this research, automated highway construction and maintenance, it was concluded that the manipulator base should be near the axles of the drive wheels and far from the centerline of the platform. © 2000 John Wiley & Sons, Inc.     

Analysis and Verification of Repetitive Motion Planning and Feedback Control for Omnidirectional Mobile Manipulator Robotic Systems

Mobile manipulator robotic systems (MMRSs) composed of a manipulator and a mobile platform are investigated in this paper. In order for the mobile manipulator robotic system (MMRS) to return to its initial state when the manipulator’s end-effector is requested to execute cyclical tasks, a quadratic program (QP) based repetitive motion planning and feedback control (RMPFC) scheme is proposed and analyzed. Such an RMPFC scheme can not only mix motion planning and reactive control, but also consider the physical limits of the robotic system. Mathematically, the efficacy of the RMPFC scheme is verified via gradient dynamics analysis. To further demonstrate the effectiveness of the RMPFC scheme, a kinematically redundant MMRS composed of a three degrees-of-freedom (DOF) planar manipulator and an omnidirectional mobile platform is designed, modeled and analyzed. Then, repetitive motion planning and feedback control for the designed omnidirectional MMRS is studied. Besides, a numerical algorithm is developed and presented to solve the QP and resolve the redundancy of the robotic system. Moreover, computer simulations are comparatively performed on such an omnidirectional MMRS, and simulation results substantiate the effectiveness, accuracy and superiority of the proposed RMPFC scheme.     

Disturbance rejection for space‐based manipulators

Most industrial manipulators operate from a fixed base. Hence, there are no disturbances from the environment to alter the position of the end‐effector. On the other hand, manipulators that are mounted on mobile platforms are subject to disturbances emerging from unwanted motion at the base. Similarly, manipulators that perform delicate operations in space while on board in‐orbit spacecraft experience disturbances. This article describes the design and implementation of a disturbance rejection controller for a 6 degree‐of‐freedom (DOF) programable universal manipulator for assembly (PUMA) manipulator mounted on a 3‐DOF platform. A control algorithm is designed to track the desired position and attitude of the end‐effector in inertial space, subject to unknown disturbances in the platform axes. Experimental results are presented for step, sinusoidal, and random disturbances in the platform rotational axis and in the neighborhood of kinematic singularities. ©1999 John Wiley & Sons, Inc.     

Motion planning for mobile manipulators with a non-holonomic constraint using the FSP (full space parameterization) method

The efficient utilization of the motion capabilities of mobile manipulators, i.e., manipulators mounted on mobile platforms, requires the resolution of the kinematically redundant system formed by the addition of the degrees of freedom (DOF) of the platform to those of the manipulator. At the velocity level, the linearized Jacobian equation for such a redundant system represents an underspecified system of algebraic equations, which can be subject to a varying set of contraints such as a non-holonomic constraint on the platform motion, obstacles in the workspace, and various limits on the joint motions. A method, which we named the Full Space Parameterization (FSP), has recently been developed to resolve such underspecified systems with constraints that may vary in time and in number during a single trajectory. In this article, we first review the principles of the FSP and give analytical solutions for constrained motion cases with a general optimization criterion for resolving the redundancy. We then focus on the solutions to (1) the problem introduced by the combined use of prismatic and revolute joints (a common occurrence in practical mobile manipulators), which makes the dimensions of the joint displacement vector components non-homogeneous, and (2) the treatment of a non-holonomic constraint on the platform motion. Sample implementations on several large-payload mobile manipulators with up to 11 DOF are discussed. Comparative trajectories involving combined motions of the platform and manipulator for problems with obstacle and joint limit constraints, and with non-holonomic contraints on the platform motions, are presented to illustrate the use and efficiency of the FSP approach in complex motion planning problems. © 1996 John Wiley & Sons, Inc.     

Endogenous configuration space approach to mobile manipulators: A derivation and performance assessment of Jacobian inverse kinematics algorithms

By a mobile manipulator we mean a robotic system composed of a non-holonomic mobile platform and a holonomic manipulator fixed to the platform. A taskspace of the mobile manipulator includes positions and orientations of its end effector relative to an inertial coordinate frame. The kinematics of a mobile manipulator are represented by a driftless control system with outputs. Admissible control functions of the platform along with joint positions of the manipulator constitute the endogenous configuration space. Endogenous configurations have a meaning of controls. A map from the endogenous configuration space into the taskspace is referred to as the instantaneous kinematics of the mobile manipulator. Within this framework, the inverse kinematic problem for a mobile manipulator amounts to defining an endogenous configuration that drives the end effector to a desirable position and orientation in the taskspace. Exploiting the analogy between stationary and mobile manipulators we present in the paper a collection of regular and singular Jacobian inverse kinematics algorithms. Their performance is evaluated on the basis of intense computer simulations.     

Analysis and Control for an Omnidirectional Mobile Manipulator

This paper describes analysis and control for a holonomic omnidirectional mobile manipulator, in which the holonomic omnidirectional platform consists of three lateral orthogonal wheel assemblies and a mounted manipulator with three rotational joints is located at the center of gravity of the platform. We first introduce the kinematic model for the mobile manipulator and derive the dynamical model by using the Newton–Euler method, where a model which simultaneously takes account of features of both the manipulator and the mobile parts is given to analyze the effect of the movement of mounted manipulator on the platform. Then, the computed torque control and the resolved acceleration control methods are used to show that the holonomic omnidirectional mobile manipulator can be controlled so as to retain any end-effector position and orientation, irrespective of the direction of external applied force. The validity of the model and the effectiveness of the present mobile manipulator are proved by using several numerical simulations and 3D animations.     

轮式移动机械臂的建模与仿真研究

移动机械臂系统一般由移动平台和机器臂组成,它既具有机器臂的操作灵活性,又具有移动机器人的可移动性,因此其应用范围要比单个系统宽得多。这篇文章主要研究了由非完整移动平台和完整机械臂组成的轮式移动机械臂系统的建模、跟踪控制及仿真问题。首先。利用拉格朗日动力学方程和非完整动力学罗兹方程建立了移动机械臂系统的精确数学模型;然后。利用非线性反馈将系统解耦。采用类PD控制器进行控制。在考虑了非完整约束及移动平台和机械臂的动态交互影响情况下,该控制算法保证系统同时跟踪给定的终端执行器和平台轨迹;最后,使用Maflah6．5对系统进行了仿真研究,仿真结果表明了其数学模型及控制方法的正确有效性。     

A Sequential Bi-criteria Search Algorithm for Robot Path Planning in the Box Pushing Problem

The collision-free trajectory planning method subject to control constraints for mobile manipulators is presented. The robot task is to move from the current configuration to a given final position in the workspace. The motions are planned in order to maximise an instantaneous manipulability measure to avoid manipulator singularities. Inequality constraints on state variables i.e. collision avoidance conditions and mechanical constraints are taken into consideration. The collision avoidance is accomplished by local perturbation of the mobile manipulator motion in the obstacles neighbourhood. The fulfilment of mechanical constraints is ensured by using a penalty function approach. The proposed method guarantees satisfying control limitations resulting from capabilities of robot actuators by applying the trajectory scaling approach. Nonholonomic constraints in a Pfaffian form are explicitly incorporated into the control algorithm. A computer example involving a mobile manipulator consisting of nonholonomic platform (2,0) class and 3DOF RPR type holonomic manipulator operating in a three-dimensional task space is also presented.     

Extended Jacobian inverse kinematics algorithms for mobile manipulators

We consider the inverse kinematic problem for mobile manipulators consisting of a nonholonomic mobile platform and a holonomic manipulator on board the platform. The kinematics of a mobile manipulator are represented by a driftless control system with outputs together with the associated variational control system. The output reachability map of the driftless control system determines the instantaneous kinematics, while the output reachability map of the variational system plays the role of the analytic Jacobian of the mobile manipulator. Relying on a formal analogy between the kinematics of stationary and mobile manipulators we exploit the extended Jacobian construction in order to design a collection of extended Jacobian inverse kinematics algorithms for mobile manipulators. It has been proved mathematically and confirmed in computer simulations that these algorithms are capable of efficiently solving the inverse kinematic problem. Moreover, a choice of the Jacobian extension may lay down some guidelines for the platform‐manipulator motion coordination. © 2002 Wiley Periodicals, Inc.     

一种基于总线的移动探测机器人控制系统设计与实现

针对机械臂定位相关的控制算法缺乏合适验证平台的问题,将移动机器人技术和机械臂控制技术相结合,在分布式控制系统结构的基础上设计并实现了移动探测机器人原型样机。该系统由一个中央主控单元和多个从控制单元构成,单元之间通过总线相连,以实现探测机械臂各部分的模块化。该控制系统已经成功应用于实验室的探测机器人中。该设计能够完成对机械臂运动控制任务,可以用于移动探测机器人平台的建立以及相关算法的实现。