一种运动旋量逆解子问题的求解及其应用

旋量理论在机器人运动学逆解过程中将运动方程分解为若干子问题,目前常见的子问题组合并不能完成所有机器人的逆解问题．本文提出了在机器人逆解过程中会遇到的另一种子问题的解法,并给出构造该子问题的限定条件．运用该解法,给出具有RTS运动链并联机器人的运动学逆解方法,并归纳出利用未知量组中对参考点起相同作用的旋量组合来简化计算的方法．该子问题的解决扩充、便利了旋量理论在机器人运动学逆解中的应用．     

基于边界元法的平面运动并联机构静力学解析

针对混联运动机床开发中所采用的2 自由度平面运动并联机构部分进行了深入的研究．介绍了该平面 运动并联机构的组成,推导了并联机构的运动学正、逆解求解公式,求解了该机构的被动关节．基于边界元法对该 机构的受力情况进行了建模和解析,给出了每个杆件的受力情况．通过ADAMS 仿真验证了求解的正确性,为该机 构的设计开发奠定了基础．本文的分析方法也为并联机构的静力学解析提供了新的思路和方法．     

新型6-HTRT并联机器人工作空间和参数研究

本文介绍了新型6-HTRT并联机器人的机构型式和工作原理，给出了考虑到约束条件的 位置逆解算法和存在多组解时的逆解选取准则．利用逆解算法和三维搜索，得到了确定该类 型机器人工作空间的方法和工作空间体积的计算公式．分析了6-HTRT并联机器人工作空间 的形态特点以及机器人结构参数和运动参数对工作空间体积的影响．     

基于遗传算法的机器人运动学逆解

在分析以往逆解方法的基础上，提出了用遗传算法求解机器人运动学逆解的方法，给出了用于优化求解的适合度函数，并提出用二次编码法提高解的精度．计算机模拟证明：该方法能快速收敛于全局最优解，能给出机器人的可能解，并能计算冗余度机器人的逆解．     

关于文"LQ逆问题研究"的问题讨论

关于文“ＬＱ逆问题研究”的问题讨论傅诒辉（华中理工大学自控系武汉４３００７４）关键词ＬＱ逆问题，加权矩阵，极点配置．文［门定理２给出了连续系统ＬＱ逆问题有解的充分条件以及确定加权矩阵Ｑ和Ｒ的参数化方法．本文构造性地给出了满足文［１］定理２全部条件的参...     

机器人运动学反解中的奇异点处理

本文研究机器人运动学反解中的奇异点处理问题，给出了机器人微分运动Ｊａｃｏｂｉａｎ矩阵Ｊ（ｑ）条件数的一个上界，并在此基础上提出机器人关节速度阻尼伪逆解方法中阻尼系数的一种自适应调整方法，该方法可以保证在奇异点附近伪逆解的稳定性。     

四自由度折叠式机械手的控制系统

四自由度折叠式机械手是一台ＳＴＤ戒严控制机管理和控制，通过视觉图象和接近觉传感器操纵机械手在移动空间中完成联送机器人任务，文中推导了机械手运动学方程，给出了运动学正逆解，详细介绍了可编位置控制系统和操纵系统。     

一种新的最优控制系统设计方法

本文采用LQ逆问题方法得到了一种新的最优控制系统设计方法，推导了线性二次型性能指标中的加权矩功Q与开环特征多项式，最优闭环特征多项式之间的关系。并研究LQ逆问题解的存在性和唯一性问题。只要给定期望的闭环极点，即可确定与之对应的加权矩阵Q，从而获得一个具有指定闭环极点的最优控制系统。     

一种新的机械手运动方程求解方法

本文在分析了多关节机械手臂运动关节与手腕姿态关系的基础上，提出了一种新的机械手运动方程求解方法，这种方法与传统的Ｄ－Ｈ算法相比大大减少计算运动方程正逆解的计算量，这对提高通用多关机器人的控制速度是有用的。本文还给出了采用新算法对Ｍｏｖｅｍａｓｔｅｒ－ＥＸ机器人运动方程的正逆解与传统Ｄ－Ｈ算法的比较。     

图像雅可比矩阵伪逆估计在视觉伺服中的应用

在一般无标定视觉伺服算法的基础上,提出了一种基于递推最小二乘法估计图像雅可比矩阵伪逆的无标定视觉伺服算法．这种方法无需计算雅可比矩阵伪逆．针对固定目标,文中给出了比例控制算法的稳定性条件．针对运动目标,推导了基于图像雅可比矩阵伪逆估计的伪高斯—牛顿视觉伺服算法和信任区视觉伺服算法．最后,仿真验证了三种视觉伺服算法的有效性．     

Construction of substantially different solutions of an inverse problem for a toroidal plasma equilibrium equation

The paper is devoted to the reconstruction of the current density in toroidal plasma, using experimentally measured data. The toroidal current density is characterized by two functions in the right-hand side of the Grad-Shafranov equation which, together with the poloidal flux, is to be deter-mined. The question about the uniqueness of the solution of the inverse problem was usually not addressed in the numerical methods developed over the past few decades. However, the theoretical study of this question for simplified models showed the possibility of the existence of substantially different solutions. For a correct understanding of the physical properties of a pulse it is necessary to analyze all possible solutions of the inverse problem in its physically correct formulation. This formulation is presented in the paper. A new numerical method for determining all substantially different solutions of the inverse problem is proposed. Examples of the existence of such solutions are constructed for plasma parameters which are close to experimental.     

Analytical Inverse Kinematic Computation for 7-DOF Redundant Manipulators With Joint Limits and Its Application to Redundancy Resolution

This paper proposes an analytical methodology of inverse kinematic computation for 7 DOF redundant manipulators with joint limits. Specifically, the paper focuses on how to obtain all feasible inverse kinematic solutions in the global configuration space where joint movable ranges are limited. First, a closed-form inverse kinematic solution is derived based on a parameterization method. Second, how the joint limits affect the feasibility of the inverse solution is investigated to develop an analytical method for computing feasible solutions under the joint limits. Third, how to apply the method to the redundancy resolution problem is discussed and analytical methods to avoid joint limits are developed in the position domain. Lastly, the validity of the methods is verified by kinematic simulations.      

6R机器人实时逆运动学算法研究

提出一套解决各类6R机器人逆运动学问题的实时算法. 一般算法通过矢量计算和16阶矩阵分解得到一般6R机器人的最多16组逆运动学解. 封闭解法直接提取运动学等式求出关节变量的解析解. 组合算法将封闭解法或一般算法的结果作为初始值, 采用牛顿-拉夫森方法迭代出逆运动学精确解, 适用于所有接近满足封闭解条件或一般算法条件的6R机器人. 求解实验结果表明, 整套算法最大算法时间约为2.03 ms, 为任意几何结构的6R机器人应用于强实时系统提供了逆运动学解决方案.     

Invariant imbedding and inverse problems with applications to radiative transfer

In this paper, we developed two methods to solve the inverse problem of a nonlinear integro-differential equation. Both methods are based on the principle of invariant imbedding. The first method involves two auxiliary integro-differential equations. The inverse problem is solved by a sequence of approximation solutions of linear equations. The second method involves algebraic equations of scattering matrices under the so-called star-product. An application to a radiative transfer problem such as correction of atmospheric effects on remote sensing is discussed.     

Reliability-based approach to the inverse kinematics solution of robots using Elman's networks

The solution of inverse kinematics problem of redundant manipulators is a fundamental problem in robot control. The inverse kinematics problem in robotics is the determination of joint angles for a desired cartesian position of the end effector. For the solution of this problem, many traditional solutions such as geometric, iterative and algebraic are inadequate if the joint structure of the manipulator is more complex. Furthermore, many neural network approaches have been done to this problem. But the neural network-based solutions are not much reliable due to the error at the end of learning. Therefore, a reliability-based neural network inverse kinematics solution approach has been presented, and applied to a six-degrees of freedom (dof) robot manipulator in this paper. The structure of the proposed method is based on using three networks designed parallel to minimize the error of the whole system. Elman network, which has a profound impact on the learning capability and performance of the network, is chosen and designed according to the proposed solution method. At the end of parallel implementation, the results of each network are evaluated using direct kinematics equations to obtain the network with best result.     

Forward and inverse kinematics of a 5-DOF hybrid robot for composite material machining

Hybrid robots consist of both serial and parallel mechanisms, which have advantages in stiffness and workspace compared with serial/parallel robots when machining composite material. However, the forward and inverse kinematics of hybrid robots generally do not have analytic solutions. This paper deals with the analytic forward and inverse kinematics solutions of a 5-degree-of-freedom (DOF) hybrid robot which consists with a 3-DOF 2UPU/SP parallel mechanism (PM) and a 2-DOF rotating head. In the forward kinematic problem, a method is proposed to transfer the high order kinematic equation to a 4th-order polynomial based on the Sylvester's dialytic elimination, and the analytic solutions can be further obtained by Ferrari's method. In the inverse problem, the redundant Euler angles expressed by four rotations are firstly proposed for decoupling different motions, then, the closed-form solution of inverse kinematics can be found. Finally, a simulation trajectory is given, and the result shows that the accuracy of the solutions’ calculation reaches femtometer grade and the efficiency reaches microsecond grade; furthermore, an experiment is performed on the prototype to validate the effectiveness of the proposed forward and inverse kinematics.     

Neural network modeling of vector multivariable functions in ill-posed approximation problems

A neural network solution of the ill-posed inverse approximation problem of a multivariable vector function based on of a committee of multilayer perceptrons is proposed. A nonlinear adaptive decision-making rule by the committee is developed that improves the accuracy compared with other neural network solutions of the inverse problem. Using a model example, the accuracy characteristics of the method are shown. An applied engineering problem is considered and the results of its solution by the proposed method are presented.     

On the existence of a global minimum in inverse parameters identification by Self-Optimizing inverse analysis method

In this paper, a mathematical proof of the existence of a global minimum of Self-Optim (Self-Optimizing Inverse Analysis Method) cost functional is presented based upon weak-solution theory of partial differential equations. The Self-Optim provides single global minimum rather than having multiple global minima corresponding to unrealistic solutions of the inverse problem. Furthermore, discrete approximation of the inverse problem and computational methods for the cost functional are proposed and the proof is numerically verified. This paper provides a rigorous mathematical foundation for applications of the Self-Optim method to various inverse problems in mechanics.     

利用有限差分法计算真实头模型脑电正问题

脑电研究领域的两个关键问题是脑电正问题和脑电逆问题,脑电正问题是脑电逆问题的基础.由于复杂、非规则真实头模型中的脑电正问题不存在解析解,因此脑电源分析依赖于正问题数值算法的精度和效率.文章首先详细推导了有限差分算法求解三维各向同性脑电正问题的数学模型,然后在三层同心球模型上通过与解析解比较验证了该算法的精度和效率,最后将该算法应用于真实头模型.仿真结果表明,有限差分法可以有效地处理任意形状几何体的电位场分布问题,是模拟计算真实头模型中脑电正问题的有力工具.