FANUC M420iA机器人动力学性能分析与仿真

利用了基于Jacobian矩阵和Hessian矩阵四自由度串联机器人加速度全局性能指标,改变在机构分析时只考虑一阶影响系数矩阵的局限性。利用该指标,分析FANUC M420iA（FMA）机器人,给出了运动学和动力学性能指标的图谱,探讨了不同尺寸之间的性能差异。最后,利用OpenGL进行了仿真,验证了加速度性能指标的正确性,为机构设计提供依据。     

欠驱动步行机器人实时仿真系统设计

开发了异构多软件平台融合的机器人实时仿真系统。在欠驱动步行机器人动力学建模中引入虚拟样机技术,利用ADAMS软件生成动力学模型,利用MATLAB软件设计控制器,二者通过接口实现联合仿真;在开发人机界面及连接各个模块的接口中引入MATLAB和VC＋＋混合编程技术,完成对硬件的驱动控制及系统平台的操作。该仿真系统实现对欠驱动步行机器人进行理论步态仿真、控制方法的开发及实验研究,对实体机器人的控制调试、实时控制算法的设计。     

深海复合轮式采矿机器人越障性能研究

针对深海富钴结壳和热液硫化调查区复杂多变的底质环境特征,提出了一种兼有主被动混合越障模式的复合轮式采矿机器人.该机器人主体由4组复合轮组与铰接密封抗压型整体罐式车架组成.建立了典型越障工况下复合轮组结构的静力学模型,得到了影响其越障性能的主要结构参数,利用MATLAB工具箱对复合轮组结构参数进行优化设计,实现机器人越障性能的提高.结合深海复杂多变的底质环境特征,运用ADAMS软件对优化设计后的复合轮式机器人进行动力学建模和仿真分析.获得了机器人越障过程中的运动学特性曲线和力学特性曲线,并通过研制原理样机对其越障性能进行测试验证.结果表明,该机器人在复杂多变的深海底质环境下中具有较强的越障能力和通过稳定性.     

改进的Hestenes SVD方法及其并行计算和在并联机器人中的应用

提出一种改进的Hestenes SVD处理方法,显著减少了矩阵奇异值分解计算的循环轮次数和正交化次数,也方便和加快了矩阵的求(伪)逆运算过程.研究了两种分别基于行划分和列划分策略的改进Hestenes SVD方法的并行计算方案,并对算法性能进行了分析.针对目前并联机器人计算需求不断扩大的特点,以6自由度并联机器人一、二阶影响系数矩阵为算例对改进Hestenes SVD方法及其并行算法进行了实验.结果表明该算法可大幅度提高矩阵奇异值分解的效率,益于基于大量影响系数矩阵运算的并联机器人运动学、动力学性能分析和实时控制.相关方法也适用于具有类似矩阵处理的其他诸多工程领域.     

全柔性铰链平面并联微动机器人的有限元分析

介绍了并联机器人的特点及其应用,对全柔性铰链平面并联机器人建立了刚性模型,并采用闭环线型原理建立理论运动学线性模型（Jacobian矩阵）,用ANSYS软件对其进行有限元分析,得到有限元运动学模型（Jacobian矩阵值）,讨论两者关系,发现有限元模型比理论模型要精确.     

机器人可视化动态仿真中的三维建模

机器人三维空间模型的建立是研究其动力学和运动学性的重要基础。要准确、逼真地进行三维建模必须恰当地选择开发工具,并简化由机器人连杆坐标变换和运动学方程所产生的复杂、大量的矩阵运算。在AutoCAD2005环境下,以VBA为二次开发工具,实行VBA和MATLAB的混合编程,把MATLAB作为后台矩阵计算引擎,可以较好地解决上述问题,成功地实现机器人计算机动态图形仿真系统的三维建模,从而为机器人动态仿真系统的开发奠定良好基础。     

主从同构穿刺手术机器人遥操作控制策略研究

文章在分析了穿刺机器人系统功能需求的基础上,搭建了主从遥操作系统的半实物仿真平台。基于等效微分变换的思想,提出雅克比矩阵(Jacobian Matrix)方法和比例微分(Proportional-Derivative,PD)控制律的联合控制方法。通过设计数字滤波器来消除外科医生的手部低频抖动对穿刺手术机器人精度的影响。实验结果表明从机器人末端执行器在笛卡尔空间坐标下能够精确快速安全地跟随主机器人末端执行器的位置变化,并且主机器人端的手部抖动能够被消除。     

机器人力控制仿真试验与研究

为了解决机器人在特定接触环境操作时对可以产生任意作用力柔性的高要求和机器人在自由空间操作时对位置伺服刚度及机械结构刚度的高要求之间的矛盾.对机器人力控制问题进行了研究,利用机械动力学仿真软件ADAMS/VIEW建立关节机器人的虚拟样机模型,通过其输入输出接口实现与MATLAB的通信,基于SIMULINK建立关节机器人力控制系统模型,将联合仿真概念引入到机器人力控制领域,最后进行仿真试验,对控制算法进行仿真验证,以提高控制精度和控制质量,通过对仿真结果的分析和处理证明此方法的合理性和有效性,为机器人力控制提供了一套有效的分析方法.     

“天龙一号”机器人的运动学和动力学仿真研究

本文对“天龙一号”五自由度弧焊机器人的运动学和动力学进行了数字仿真研究。文中采用齐次变换矩阵法详细推导了“天龙一号”机器人的运动学方程和求解逆问题的公式,给出机器人运动学和动力学数字仿真的算法及递推公式.最后,通过举例给出了“天龙一号”机器人数字仿真结果。这些仿真结果对评价机器人的性能及校验机器人系统的刚度、强度、电机的功率和转矩、极限速度和抓重都有重要意义.     

排爆机械臂的运动学仿真

在机械臂性能优化设计的研究中,为了使排爆机械臂能够灵活、有效的处理爆炸物,需对其进行运动学仿真,针对所设计的排爆机械臂的机械结构,通过D-H方法建立相应的运动学模型,运用矩阵逆乘的方法分离变量,求得了运动学正解和逆解.用MATLAB平台中机器人工具箱编程并建立ADAMS虚拟样机,对机械臂的末端位移、速度和加速度做了运动学仿真,通过仿真验证了机构设计的合理性和仿真方法的正确性.结果为排爆机器人的结构设计和优化,为排爆机械臂的电机选择提供了依据.     

基于RBF神经网络整定的高速公路匝道PID控制器

研究RBF神经网络整定PID控制器的参数,并应用到高速公路入口匝道控制中。首先阐述了入口匝道控制原理,然后建立了高速公路交通流模型,并设计了RBF神经网络整定的高速公路匝道PID控制器,RBF神经网络通过对被控对象Jacobian信息的辨识来动态调节PID控制器的参数,最后用MATLAB软件进行系统仿真。仿真结果表明,该控制器具有优越的动态和稳态性能,用于高速公路入口匝道控制中效果良好。     

Formal analysis of the kinematic Jacobian in screw theory

As robotic systems flourish, reliability has become a topic of paramount importance in the human–robot relationship. The Jacobian matrix in screw theory underpins the design and optimization of robotic manipulators. Kernel properties of robotic manipulators, including dexterity and singularity, are characterized with the Jacobian matrix. The accurate specification and the rigorous analysis of the Jacobian matrix are indispensable in guaranteeing correct evaluation of the kinematics performance of manipulators. In this paper, a formal method for analyzing the Jacobian matrix in screw theory is presented using the higher-order logic theorem prover HOL4. Formalizations of twists and the forward kinematics are performed using the product of exponentials formula and the theory of functional matrices. To the best of our knowledge, this work is the first to formally analyze the kinematic Jacobian using theorem proving. The formal modeling and analysis of the Stanford manipulator demonstrate the effectiveness and applicability of the proposed approach to the formal verification of the kinematic properties of robotic manipulators.     

三分支机器人协调操作及关节力矩优化

针对三分支机器人协调运动，采用分离影响系数法分离各个分支的雅可比矩阵和惯性矩阵，再重新组合成整个系统的雅可比矩阵和惯性矩阵，建立三分支机器人运动学和动力学方程．应用乘子罚函数方法，对三分支机器人基于最小关节驱动力矩优化设计,避免矩阵的奇异值分解，提高计算的稳定性，应用迭代方法，简化了问题的求解．     

Computer-aided-design tool for simplification of robot dynamic model based on manipulator system performance

The dynamic performance of a robot manipulator is directly dependent on the efficiency of the controller and the dynamic model of the robot. This paper addresses the fundamental issue of how much manipulator dynamics information should be included in the manipulator dynamic model for control such that the manipulator will achieve the desired system performance under a proportional-plus-derivative control scheme. An efficient minimax simplification scheme has been developed which automatically generates simplified closed-form manipulator motion equations in symbolic form while maintaining the desired manipulator system performance under a proportional-plus-derivative controller. The scheme involves the identification and selection of basis functions that represent the dynamic coefficients in the dynamic model. These basis functions consist of a linear combination of the product terms of sinusoidal and polynomial functions of the generalized coordinates and form a Chebyshev set on the workspace of the manipulator. A multi-layered decision scheme is developed for selecting significant basis terms in each layer for each dynamic coefficient. The linear combination of these significant basis terms is then utilized to construct each simplified dynamic coefficient based on the minimax approximation technique. A verification of the proposed scheme on a Stanford robot arm is included for discussion.     

SYMBOLIC COMPUTATION OF ROBOT DYNAMIC PARAMETERS

Optimal performance of robot manipulators can be achieved only by utilizing advanced control algorithms. However, precise control of robot motion requires the use of accurate dynamic models, which are very complicated due to varying arm geometric configuration, uncertain effects of load handling on the dynamic stability of the arm, and the high degree of nonlinearty and coupling exhibited between different links. Therefore, an efficient and fast method for on-line tuning of robot dynamic parameters must be devised. In this work a simplified model based on Lagrange-Euler dynamics is developed. The proposed method is simple and systematic for the extraction and identification of robot dynamic parameters. The dynamic parameters are then formulated as a regression model. This model is used to generate the closed-form solution of the dynamics. The analysis in this work is based on a set of compiled data for the Stanford arm to facilitate the study of the dynamic performance and closed-loop solutions of robot manipulators. For the derivation of the dynamics MAPLE (symbolic computer algebra language) is used.     

Periodic step-size adaptation in second-order gradient descent for single-pass on-line structured learning

It has been established that the second-order stochastic gradient descent (SGD) method can potentially achieve generalization performance as well as empirical optimum in a single pass through the training examples. However, second-order SGD requires computing the inverse of the Hessian matrix of the loss function, which is prohibitively expensive for structured prediction problems that usually involve a very high dimensional feature space. This paper presents a new second-order SGD method, called Periodic Step-size Adaptation (PSA). PSA approximates the Jacobian matrix of the mapping function and explores a linear relation between the Jacobian and Hessian to approximate the Hessian, which is proved to be simpler and more effective than directly approximating Hessian in an on-line setting. We tested PSA on a wide variety of models and tasks, including large scale sequence labeling tasks using conditional random fields and large scale classification tasks using linear support vector machines and convolutional neural networks. Experimental results show that single-pass performance of PSA is always very close to empirical optimum.     

Kinematic design optimization of a parallel ankle rehabilitation robot using modified genetic algorithm

Rehabilitation robotics is an evolving area of active research and recently novel mechanisms have been proposed to reinstate complex human movements. Parallel robots are of particular interest to researchers since they are rigid and can provide enough load capacity for human joint movements. This paper proposes a soft parallel robot (SPR) for ankle joint rehabilitation. Kinematic workspace analysis is carried out and the singularity criterion of the SPR’s Jacobian matrix is used to define the feasible workspace. A global conditioning number (GCN) is defined using the Jacobian matrix as a performance index for the evaluation of the robot design. An optimization problem is formulated to minimize the GCN using modified genetic algorithm (GA). Results from simple GA and modified GA are compared and discussed. As a result of the optimization, an optimal robot design is obtained which has a near unity GCN with almost uniform distribution in the entire feasible workspace of the robot.     

基于MATLABGUIDE的电力系统潮流计算

潮流计算是电力系统分析中最基本和最重要的一种计算。对电力系统的数学建模以牛顿-拉夫逊法为基础,通过改进雅可比矩阵的分块方式以利于计算机编程。以MATLAB开发潮流算法程序,利用MATLAB内置的可视化编程工具GUIDE开发潮流计算程序界面,并给出了相关实例。