机器人反向动力学方程的并行计算

以PUMA560机器人的分解牛顿-欧拉反向动力学方程为模型,提出了方程分解的原则,由此得到AOE(Activity On Edge)有向图.以此为基础,按照深度和时差的概念建立了L-W优先表,并导出了一种启发式的调度算法.该算法在微处理机个数一定的情况下,可得到最小调度时间.最后,以Stanford机器人的递推牛顿-欧拉反向动力学方程为例,说明了该算法的有效性.     

BP-MPSO混合算法在机器人空间路径中的应用

在对PUMA机器人空间路径进行BP算法环境建模与目标建模的基础上,针对传统粒子群优化（PSO）算法搜索空间有限、容易陷入局部最优点的缺陷,提出了一种改进的粒子群优化（MPSO）算法。该算法引入了基于全局信息反馈的重新初始化过程机制,并对PUMA机器人空间路径进行了优化。仿真实验表明,该算法的应用不仅降低了求解逆运动方程的难度,还能得到全局最优解。显著地提高了PUMA机器人空间路径优化的效率。     

机器人几何连杆参数辨识

本文给出了一种通用的机器人几何连杆参数估计方法.基于机器人运动学模型和运动学误差模型,可以推导出包含未知参数的线性输入输出方程;然后采用最小二乘法得到参数估计值.该方法已应用于PUMA机器人参数辨识.     

嵌入式工业机器人遗传算法逆解的实现

针对现有控制器的不足,选取OMAP3530和Linux操作系统构建整个工业机器人控制系统,突破了传统工业机器人的封闭结构,具有良好的可扩展性;以PUMA560工业机器人的运动学为模型,给出了一种求解工业机器人逆解的改进的遗传算法,在片上移植Linux系统并加载所需的内核模块,并将算法在该系统上编译运行;将该算法与普通遗传算法分别进行收敛速度和运算精度的对比,同时在不同平台上对算法进行运行时间的对比;实验结果表明该遗传算法具有运算精度高,运行速度快的优点;而且OMAP3530平台更小,功耗更低,完全能满足实时性的要求。     

FUMA560C机器人故障一例及排除

1.问题的提出 浙江大学工业控制技术研究所有一台美国进口的PUMA 560C型机器人。在使用过程中,我们发现它有时会出现一些错误。由于随机所带的资料不全,故单从资料分析中,无法排除故障。 2.PUMA 560C故障一例 在运行PUMA 560C时,机器有时会出现下述故障: *ANY ENCODER ERROR* 即系统某个关节的编码器出错。这时,系统会自动处于停机状态,机器人手臂电源自动切断,机器人出错提示灯亮。此时程序也不再运行。     

改进B样条曲线的机器人轨迹拟合研究

以工业生产中常用的六自由度串联机器人PUMA560为研究对象,在关节空间采用改进B样条曲线进行轨迹拟合规划,相比于传统B样条插值与拟合算法显著改善了规划得到的轨迹全局最优解,并基于最优解对各关节进行规划得到时间最优的运动轨迹,验证该算法可以有效提高机器人运行效率的目的.     

基于对偶四元数的机器人方位与手眼关系同时标定方法

针对相机姿态估计及机器人运动学正解存在测算偏差时,手眼标定及机器人坐标系-世界坐标系标定结果不能准确收敛到全局最优解的问题,提出了一种基于对偶四元数理论的机器人方位与手眼关系同时标定方法.该方法首先将标定方程中坐标系刚体变换关系用螺旋轴、旋转角度和平移量参数化表示,再结合全局优化算法对平移量进行优化.搭建了PUMA560机器人数值仿真系统和工业机器人实测实验平台,将该方法与经典的四元数和对偶四元数标定方法进行了比较分析.仿真和实测结果表明,在相机姿态估计及机器人运动学正解存在测量误差的情况下,该方法无需初值估计和数据筛选依然可以保证求解结果的最优性.     

机器人机构误差建模的摄动法

误差建模的摄动法,即直接对机构中各种原始误差的小位移矢量进行合成,建立机器人手部位姿误差模型.它摈弃了其他误差建模方法均需要的微分运算,并能分析多种原始误差产生的机器人手部位姿误差.用该法建立的误差模型简单且物理意义清楚.作为例题,文中建立了 PUMA560型机器人的误差模型.     

机器人最佳轨迹规划和图形仿真的研究

本文介绍了基于 IBM-PC 微机的机器人轨迹规划的图形仿真系统.该系统可用于机器人运动学分析和最佳轨迹规划,并能产生机械手和广义物体组成的环境物的三维几何模型.系统以交互方式工作.在微机的 CRT 上,机械手连杆的运动具存动态效果.基于 MINIMAX 准则,我们提出了一种动力学性能指标用于轨迹规划.根据该指标所进行的轨迹规划可以获得最小的关节驱动力矩.最后,文中给出了 PUMA 560 机械手的仿真结果.     

NOKIA PUMA 580FA 机器人的原理及应用

本文对 NOKIA PUMA 560 FA 机器人的结构、原理、性能及软、硬件配置做了较详细的介绍,着重剖析了它的伺服控制系统,并对其应用于CO_2气体保护焊的使用方法、技巧等作了一定的介绍,同时也提出了对 PUMA560 FA 机器人的评价,可供从事机器人研究、设计、使用的人员参考.     

利用BP-NN算法的机器人臂重力补偿研究

利用反向传播神经网络(BP-NN)学习算法,对机器人臂的重力补偿进行了研究。给出了机器人臂各关节扭矩的重力项理论计算公式及其连杆参数识别方法,同时,对BP-NN算法进行了详细分析,利用BP-NN来处理机器人臂重力项并进行试验。试验结果表明,采用该学习算法得到的机器人臂重力项输出值和实测值基本一致,能有效减少机器人臂重力项计算量,达到实时控制的目的。     

基于ROS的移动机器人视觉跟随系统设计

视觉跟随是机器人领域中一个比较重要的部分,可以应用在仓储搬运、安防、军事等多种领域。由于传统算法存在当背景比较复杂的情况下无法有效跟踪目标、对跟踪目标和外部环境的分辨率要求高所以只能进行辅助跟踪、计算量大无法满足实时性要求等问题。本文采用KCF算法设计,设计了基于ROS的移动机器人视觉跟随系统,利用循环矩阵在傅里叶空间可对角化的性质,从而使得矩阵运算被转化成元素的点乘,减少了计算量从而提高了运算速度,满足了算法的实时性要求。经过实验和数据分析,本移动机器人可以实时有效的跟随指定目标实现视觉跟随功能。     

Inverse kinematics of spherical wrist robot arms: Analysis and simulation

The spherical wrist robot arm is the most common type of industrial robot. This paper presents an efficient analytical computation procedure of its inverse kinematics. It is based on the decomposition of the inverse kinematic problem to two less complex problems; one concerns the robot arm basic structure and the other concerns its hand. The proposed computation procedure is used to obtain the inverse kinematic position models of two robot arms: one contains only revolute joints and the other contains both revolute and prismatic joints. The 1st and 2nd time derivatives of the obtained models give more accurate inverse kinematic velocity and acceleration models than numerical differentiation. These models are verified by simulation for two different trajectories. The obtained results demonstrate the effect of the proposed procedure on reducing the necessary computation time compared to other computation techniques.     

Optimal landmark selection for triangulation of robot position

A mobile robot can identify its own position relative to a global environment model by using triangulation based on three landmarks in the environment. It is shown that this procedure may be very sensitive to noise depending on spatial landmark configuration, and relative position between robot and landmarks. A general analysis is presented which permits prediction of the uncertainty in the triangulated position.

In addition an algorithm is presented for automatic selection of optimal landmarks. This algorithm enables a robot to continuously base its position computation on the set of available landmarks, which provides the least noise sensitive position estimate. It is demonstrated that using this algorithm can result in more than one order of magnitude reduction in uncertainty.     

改进蚁群算法的机器人焊接路径规划

利用改进蚁群算法,引入最大最小蚂蚁系统和局部搜索策略,避免蚁群算法出现早熟、停滞问题,并提高了算法的求解速度和精度,实现了合理规划白车身机器人焊接路径和提高焊接机器人的工作效率的目的.设计了白车身机器人焊点规划程序,并将其应用到白车身底板某工位,从仿真结果表明:将改进蚁群算法应用到白车身机器人焊接路径规划中,验证了算法的有效性和可行性.     

自主移动机器人定位系统中Kalman滤波算法改进*

为了解决常规Kalman滤波算法在移动机器人定位过程中运算量大、精度不高的问题,在分析传统Kalman滤波器缺点的基础上,提出了一种基于UT参数变换的方法对常规Kalman滤波算法进行了改进。改进后的Kalman滤波算法消减了传统Kalman滤波器高阶项无法忽略而带来的误差。实验结果表明,改进型的Kalman滤波算法使机器人的最大位置偏差得到减小,对移动机器人的定位精度有明显改善,误差仿真曲线表明,改进后的定位结果误差波动不明显,使定位系统的稳定性得到了较大提高。     

A method to learn the inverse kinematics of multi-link robots by evolving neuro-controllers

A general method to learn the inverse kinematic of multi-link robots by means of neuro-controllers is presented. We can find analytical solutions for the most used and well-known robots in the literature. However, these solutions are specific to a particular robot configuration and are not generally applicable to other robot morphologies. The proposed method is general in the sense that it is independent of the robot morphology. The method is based on the evolutionary computation paradigm and works obtaining incrementally better neuro-controllers. Furthermore, the proposed method solves some specific issues in robotic neuro-controller learning: it avoids any neural network learning algorithm which relies on the classical supervised input-target learning scheme and hence it lets to obtain neuro-controllers without providing targets. It can converge beyond local optimal solutions, which is one of the main drawbacks of some neural network training algorithms based on gradient descent when applied to highly redundant robot morphologies. Furthermore, using learning algorithms such as the neuro-evolution of augmenting topologies it is also possible to learn the neural network topology which is a common source of empirical testing in neuro-controllers design. Finally, experimental results are provided when applying the method to two multi-link robot learning tasks and a comparison between structural and parametric evolutionary strategies on neuro-controllers is shown.     

Recursive Implementation of LoG Filtering

LoG filters have been widely used as a second derivative filtering function. One problem with LoG filtering is that it is very time consuming, especially with a large size filter. We use an analytical method to obtain the z-transform of LoG function in a rational function form and develop a recursive implementation. The structure of the recursive filters is defined by the order of rational functions. The algorithm gives a constant computation complexity per pixel. The computational complexity of recursive filtering depends on the number of poles and zeros of the transfer function, i.e., on the structure of the recursive filter. It is independent of the size of the filter, and thus has a substantial saving in computation. A general method of designing high order recursive filters is also given. Recursive functions can be implemented in a number of shifting registers in hardware. The methodology will contribute to real-time image processing and robot vision.     

Design of a walking cyclic gait with single support phases and impacts for the locomotor system of a thirteen-link 3D biped using the parametric optimization

The development of an algorithm of parametric optimization to achieve optimal cyclic gaits in space for a thirteen-link 3D bipedal robot with twelve actuated joints is proposed. The cyclic walking gait is composed of successive single support phases and impulsive impacts with full contact between the sole of the feet and the ground. The evolution of the joints are chosen as spline functions. The parameters to define the spline functions are determined using an optimization under constraints on the dynamic balance, on the ground reactions, on the validity of impact, on the torques, and on the joints velocities. The cost functional considered is represented by the integral of the torques norm. The torques and the constraints are computed at sampling times during one step to evaluate the cost functional for a feasible walking gait. To improve the convergence of the optimization algorithm the explicit analytical gradient of the cost functional with respect to the optimization parameters is calculated using the recursive computation of torques. The algorithm is tested for a bipedal robot whose numerical walking results are presented.     

Transputer arrays for the on-line computation of robot jacobians

On-line computation of forward and inverse Jacobian matrices is essential in robot manipulator controllers, where high-speed robot motion is required. The complexity of Jacobian calculation is such that the computational burden is large, and parallel processing is necessary if on-line computation is to be achieved. Various algorithms and parallel-processing networks suitable for this are considered. All algorithms have been implemented on transputer networks and computation times measured. The paper emphasises the importance of including communication overheads in comparisons of the computational efficiency of alternative algorithms and processor networks. Theoretical processing times based on computer cycle times and arithmetic operation counts are shown to be a false basis for comparison. Whilst considering the specific case of computation of Jacobian matrices for a robot manipulator, the paper provides a useful example of the considerations and constraints involved in distributing any algorithm across a multi-processor network.