故障容错串联机械臂设计方法研究

本文从机械臂运动学任务特性出发,定义了故障容错机械臂的相关特性,论证了运动学关节冗余也可以提高机械臂系统的可靠性,故障容错机械臂所应该具备的自由度数,以及针对不同的任务对象要求,设计故障容错机械臂的方法.将任务空间抽象简化为一系列的特征点,建立机械臂参数与理想值相关的罚函数,选择有效的优化算法,设计出了一系列故障容错平面位置机械臂和故障容错空间位置机械臂.建立起完整的故障容错机械臂的设计方法,对危险环境机器人、医疗机器人的研究设计具有重要价值.     

基于运动学模型重构的单关节故障机械臂容错路径规划

针对单关节故障机械臂的路径规划问题,提出一种基于运动学模型重构的容错路径规划方法.首先基于旋量理论进行单关节故障机械臂的通用运动学模型重构;然后分析机械臂的退化工作空间,并以运动性能平稳为约束对其进行栅格化处理;最后通过改进传统的A$^\ast$算法,在退化工作空间中搜索出能够满足任务要求的轨迹.以七自由度机械臂为对象进行仿真实验,验证了所提出方法的正确性和有效性.     

基于免疫遗传算法的冗余空间机械臂设计

空间机械臂的工作任务特殊,工作环境极其恶劣,因而提高空间机械臂的可靠性显得尤为重要。冗余是提高机械臂可靠性的重要方法,寻求实用的故障容错冗余机械臂设计方法是论文研究的核心内容。冗余机械臂设计是多参数、多模态、非线性设计问题,用传统的优化方法难以解决。论文模拟抗体搜索机制,结合免疫网络理论,用抗体表示函数优化解的可能模式,通过克隆算子完成全局搜索,利用B细胞网络保持抗体的多样性。通过实际设计表明,算法是可行有效的。     

考虑多传感器故障的可重构机械臂主动取代分散容错控制

针对可重构机械臂系统位置传感器和速度传感器多故障, 提出一种主动取代分散容错控制方法. 基于可重构机械臂的模块化属性, 设计正常工作模式下的分散神经网络控制器. 利用微分同胚原理将子系统结构进行非线性变换, 将传感器故障转化成伪执行器故障, 设计分散滑模观测器以对多传感器故障进行实时检测, 并利用其输出信号取代故障传感器信号, 实现了多传感器故障情形下可重构机械臂的主动容错控制. 仿真结果表明了所设计的容错控制方法的有效性.     

基于深度强化学习的机械臂容错控制方法

针对机械臂突发单关节故障的情况,提出一种基于深度强化学习的机械臂容错控制方法。在建立环境模型和奖罚机制的基础上,针对机械臂正常运行和故障运行的情况,使用无模型的强化学习算法进行离线训练。在Rviz中建立机械臂模型并使用上述网络进行在线控制。实验证明:该算法可以有效完成机械臂的正常控制和容错控制。     

线驱动柔性机械臂的运动学分析

与传统的由连杆和关节构成的刚性机械臂不同,设计的柔性机械臂无任何刚性结构,外围驱动装置通过嵌在机械臂内部的拉线与柔性机械臂相联系,控制拉线长度的变化量即可调整柔性机械臂末端执行器的位置和姿态。柔性机械臂由弹性材料制作而成,拥有无穷多个自由度,在确保了高安全性、高灵活性的同时,随之也带来运动学和动力学建模复杂、控制难度大等问题。基于分段常曲率的假设,提出了一种运动学建模方法,通过建立3个空间,即驱动空间、虚拟关节空间、任务空间,以及两个映射,即驱动空间-虚拟关节空间映射、虚拟关节空间-任务空间映射,将拉线长度的变化量和柔性机械臂末端执行器的位置和姿态关联起来。仿真结果表明,提出的线驱动柔性机械臂的运动学模型,能较为真实地模拟柔性机械臂在拉线长度变化时的形态,计算末端执行器的位置和姿态。     

空间机械臂柔性连杆的弯曲形状

研究单连杆旋转柔性空间机械臂的弯曲形状,以确定空间柔性机械臂末端的位置.在考虑连杆变形对力矩影响和曲率表示式中不忽略形状函数一阶导数平方的情况下,利用Taylor展式表示连杆的变形,导出了连杆变形的数学模型.通过降阶方法导出形状函数一阶导数的解析式,并给出了由此解析式利用数值积分确定形状函数的方法.给出了利用二分法确定变形后的连杆在其固连坐标系中最大横坐标的方法.针对一组参数进行了仿真,证实了这种方法确定空间柔性机械臂末端的位置的可行性.     

基于信号重构的可重构机械臂主动分散容错控制

针对可重构机械臂系统传感器故障,提出一种基于信号重构的主动分散容错控制方法. 基于可重构机械臂系统模块化属性,采用自适应模糊分散控制系统实现正常工作模式时模块关节的轨迹跟踪控制. 当在线检测出位置或速度传感器故障时,分别采用数值积分器或微分跟踪器重构相应信号,并以之代替故障信号进行反馈实现系统的主动容错控制. 此方法充分利用了冗余信息,避免了故障关节控制性能的下降对其他关节的影响. 数值仿真结果验证了所提出容错控制方法的有效性.     

一种基于多视角图像的目标物体定位方法

在遥操作机械臂时,为了能有一个更加友好的人机交互界面,往往需要在控制界面中构建一个虚拟的机械臂以及机械臂工作空间,所以,在虚拟工作空间中标示出目标物体与虚拟机械臂的相对位置,给操作人员一个直观的提示,是虚拟工作空间重构的关键问题.针对机械臂遥操作,提出了一种基于不同视角图像的快速高效的定位方法,该方法根据目标物体在多个不同视角图像中的位置,计算出目标物体在实际工作空间中的位置,从而在虚拟机械臂工作空间中标示出目标物体与虚拟机械臂的相对位置.最后,构建了机械臂遥操作实物系统,验证了该方法的正确性.     

基于Matlab机械臂力控系统仿真研究

以位置控制为主的机械臂控制方法已不能满足某些复杂环境（装配、抛光、去毛刺）的应用要求,控制机械臂与环境间的接触力已成为机器人学研究的一个热点。提出一种在Matlab/SimMechanics环境下平面二自由度机械臂力控制的仿真研究方法。在平面中模拟机械臂与环境的接触面,设计振荡抑制控制器,实现机械臂与环境间接触力的控制,以及机械臂与刚性环境碰撞接触过程中冲击振荡阶段的振荡抑制,生成机械臂期望的运动轨迹。仿真结果表明,该方法可实现特定作业下机械臂与环境间接触力的控制。     

Optimal path planning of redundant free-floating revolute-jointed space manipulators with seven links

The path planning of free-floating manipulators is of great interest in space operations. The manipulators in the free-floating mode exhibit nonholonomic characteristics due to the nonintegrability of the angular momentum, which makes the problem complicated. This paper analyzes the path planning of redundant, free-floating space manipulators with revolute joints and 7 degrees of freedom. The primary task of manipulators is to move the manipulator arms so that the desired end-effector position and orientation can be achieved. The motion of the manipulators can produce an attitude disturbance of the base, which has an adverse impact on the spacecraft operation. Thus, it is necessary to minimize the base attitude disturbance in order to reduce the fuel consumption for attitude maintenance. Practically, the path planning of redundant free-floating manipulators with higher degrees of freedom (7 degrees of freedom in this paper) in three-dimensional space is more complicated than path planning with fewer degrees of freedom, including planar or fixed base cases. This paper provides a tractable planning method to solve this problem, which could avoid the pseudo inverse of the Jacobian matrix. The sine functions, whose arguments are the polynomial functions with unknown coefficients, are used to specify the joint paths. The PSODE algorithm (particle swarm optimization combined with differential evolution) is applied to optimize the unknown coefficients of the polynomials in order to achieve the desired end-effector position and orientation and simultaneously minimize the base attitude disturbance. The simulations demonstrate that this method could provide satisfactory smooth paths for redundant free-floating space manipulators.     

Design and analysis of kinematically redundant parallel manipulators with configurable platforms

Redundancy can, in general, improve the ability and performance of parallel manipulators by implementing the redundant degrees of freedom to optimize a secondary objective function. Almost all published researches in the area of parallel manipulators redundancy were focused on the design and analysis of redundant parallel manipulators with rigid (nonconfigurable) platforms and on grasping hands to be attached to the platforms. Conventional grippers usually are not appropriate to grasp irregular or large objects. Very few studies focused on the idea of using a configurable platform as a grasping device. This paper highlights the idea of using configurable platforms in both planar and spatial redundant parallel manipulators, and generalizes their analysis. The configurable platform is actually a closed kinematic chain of mobility equal to the degree of redundancy of the manipulator. The additional redundant degrees of freedom are used in reconfiguring the shape of the platform itself. Several designs of kinematically redundant planar and spatial parallel manipulators with configurable platform are presented. Such designs can be used as a grasping device especially for irregular or large objects or even as a micro-positioning device after grasping the object. Screw algebra is used to develop a general framework that can be adapted to analyze the kinematics of any general-geometry planar or spatial kinematically redundant parallel manipulator with configurable platform.     

On the dynamics and control of flexible joint space manipulators

Space manipulator systems are designed to have lightweight structure and long arms in order to achieve reduction of fuel consumption and large reachable workspaces, respectively. Such systems are subject to link flexibilities. Moreover, space manipulator actuators are usually driven by harmonic gear mechanisms which lead to joint flexibility. These types of flexibility may cause vibrations both in the manipulator and the spacecraft making the positioning of the end-effector very difficult. Here, both types of flexibilities are lumped at the joints and the dynamic equations of a general flexible joint space manipulator are derived. Their internal structure is highlighted and similarities and differences with fixed-base robots are discussed. It is shown that one can exploit the derived dynamic structure in order to design a static feedback linearization control law and obtain an exact linearization and decoupling result. The application of such controllers is desired in space applications due to their small computational effort. In case of fixed-base manipulators, the effective use of a static feedback controller is feasible only if a simplified model is considered. Then, the proposed static feedback linearization control law is applied to achieve end-effector precise trajectory tracking in Cartesian space maintaining a desirable non-oscillatory motion of the spacecraft. The application of the proposed controller is illustrated by a planar seven degrees of freedom (dof) system.     

Study and resolution of singularities for a 6-DOF PUMA manipulator

Upon solving the inverse kinematics problem of robot manipulators, the inherent singularity problem should always be considered. When a manipulator is approaching a singular configuration, a certain degree of freedom will be lost such that there are no feasible solutions of the manipulator to move into this singular direction. In this paper, the singularities of a 6-DOF PUMA manipulator are analyzed in detail and all the corresponding singular directions in task space are clearly identified. In order to resolve this singularity problem, an approach denoted Singularity Isolation Plus Compact QP (SICQP) method is proposed. The SICQP method decomposes the work space into achievable and unachievable (i.e., singular) directions. Then, the exactness in the singular directions are released such that extra redundancy is provided to the achievable directions. Finally, the Compact QP method is applied to maintain the exactness in the achievable directions, and to minimize the tracking errors in the singular directions under the condition that feasible joint solutions must be obtained. In the end, some simulation results for PUMA manipulator are given to demonstrate the effectiveness of the SICQP method.     

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.     

Sliding Mode Adaptive Neural-Network Control for Nonholonomic Mobile Modular Manipulators

A general mobile modular manipulator can be defined as a m-wheeled holonomic/nonholonomic mobile platform combining with a n-degree of freedom modular manipulator. This paper presents a sliding mode adaptive neural-network controller for trajectory following of nonholonomic mobile modular manipulators in task space. Dynamic model for the entire mobile modular manipulator is established in consideration of nonholonomic constraints and the interactive motions between the mobile platform and the onboard modular manipulator. Multilayered perceptrons (MLP) are used as estimators to approximate the dynamic model of the mobile modular manipulator. Sliding mode control and direct adaptive technique are combined together to suppress bounded disturbances and modeling errors caused by parameter uncertainties. Simulations are performed to demonstrate that the dynamic modeling method is valid and the controller design algorithm is effective.     

An algorithmic approach to coordinate transformation for robotic manipulators

Coordinate transformation is one of the most important issues in robotic manipulator control. Robot tasks are naturally specified in work space coordinates, usually a Cartesian frame, while control actions are developed on joint coordinates. Effective inverse kinematic solutions are analytical in nature; they exist only for special manipulator geometries and geometric intuition is usually required. Computational inverse kinematic algorithms have recently been proposed; they are based on general closed-loop schemes which perform the mapping of the desired Cartesian trajectory into the corresponding joint trajectory. The aim of this paper is to propose an effective computational scheme to the inverse kinematic problem for manipulators with spherical wrists. First an insight into the formulation of kinematics is given in order to detail the general scheme for this specific class of manipulators. Algorithm convergence is then ensured by means of the Lyapunov direct method. The resulting algorithm is based on the hand position and orientation vectors usually adopted to describe motion in the task space. The analysis of the computational burden is performed by taking the Stanford arm as a reference. Finally a case study is developed via numerical simulations.     

On the decoupling of position and force controllers in constrained robotic tasks

In hybrid control of robot manipulators separate controllers are designed for force and position errors control. Controllers are designed either in task or joint space and their outputs combine to provide input torque to the manipulator. Position and force controllers performance in a constrained robotic task is affected by their interaction to a degree dependent on the controller's ability to reject disturbances. Ideally, decoupling of the two control loops is desired to achieve the best performance in position and force directions. In this article, analysis of control loop interactions is performed for contact and noncontact phases, and controller design requirements are developed to achieve maximum decoupling. Design requirements involve output subspace of each controller leading to control discontinuities for contact and noncontact phases. In the noncontact phase, satisfaction of design requirements leads to a fully linearized and decoupled system. When in contact with the constraining surface, design requirements eliminate disturbances in the force loop, but minimize disturbances in the position loop to an extent dependent on force loop performance. Known hybrid control schemes analysis is performed to reveal existence of control loop interactions in these schemes. Confirmation of theoretical analysis is done through simulation of a three revolute planar manipulator. © 1998 John Wiley & Sons, Inc.     

Cartesian path generation of robot manipulators using continuous genetic algorithms

In this paper, the authors describe a novel technique based on continuous genetic algorithms (CGAs) to solve the path generation problem for robot manipulators. We consider the following scenario: given the desired Cartesian path of the end-effector of the manipulator in a free-of-obstacles workspace, off-line smooth geometric paths in the joint space of the manipulator are obtained. The inverse kinematics problem is formulated as an optimization problem based on the concept of the minimization of the accumulative path deviation and is then solved using CGAs where smooth curves are used for representing the required geometric paths in the joint space through out the evolution process. In general, CGA uses smooth operators and avoids sharp jumps in the parameter values. This novel approach possesses several distinct advantages: first, it can be applied to any general serial manipulator with positional degrees of freedom that might not have any derived closed-form solution for its inverse kinematics. Second, to the authors’ knowledge, it is the first singularity-free path generation algorithm that can be applied at the path update rate of the manipulator. Third, extremely high accuracy can be achieved along the generated path almost similar to analytical solutions, if available. Fourth, the proposed approach can be adopted to any general serial manipulator including both nonredundant and redundant systems. Fifth, when applied on parallel computers, the real time implementation is possible due to the implicit parallel nature of genetic algorithms. The generality and efficiency of the proposed algorithm are demonstrated through simulations that include 2R and 3R planar manipulators, PUMA manipulator, and a general 6R serial manipulator.