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.     

Feedback Control of an Omnidirectional Autonomous Platform for Mobile Service Robots

This paper proposes a feedback control scheme for an omnidirectional holonomic autonomous platform, which is equipped with three lateral orthogonal-wheel assemblies. Firstly, the dynamic properties of the platform are studied, and a dynamic model suitable for the application of control is derived. The control scheme constructed is of the resolved-acceleration type, with PI and PD feedback. The control scheme was experimentally applied to an actual mobile robotic platform. The results obtained show that full omnidirectionality can be achieved with decoupled rotational and translational motions. Omnidirectionality is one of the principal requirements for mobile robots designed for health-care and other general-hospital services.     

Mobile Manipulator Motion Planning for Multiple Tasks Using Global Optimization Approach

A mobile manipulator can perform various tasks efficiently by utilizing mobility and manipulation functions. The coupling of these two functions creates a particular kinematic redundancy introduced by mobility, which is different from that introduced by extra joints. This redundancy is quite desirable for dexterous motion in cluttered environments, but it also significantly complicates the motion planning and control problem. In this paper we propose a new motion planning method for mobile manipulators to execute a multiple task which consists of a sequence of tasks. The task considered in this paper is that the end-effector tracks a prespecified trajectory in a fixed world frame. In a multiple task, the final configuration of each task becomes the initial configuration of the next subsequent task. Such a configuration is known as a commutation configuration, which significantly affects the performance of the multiple task.We formulate the motion planning problem as a global optimization problem and simultaneously obtain the motion trajectory set and commutation configurations. In the formulation, we take account of the case that the platform has a non-holonomic constraint as well as the one that the platform has a holonomic constraint. Simulation results are demonstrated to verify the effectiveness of the proposed method.     

Optimal Motion Planning of Robotic Manipulators Removing Mobile Objects Grasped in Motion

The following study deals with motion optimization of robot arms having to transfer mobile objects grasped when moving. This approach is aimed at performing repetitive transfer tasks at a rapid rate without interrupting the dynamics of both the manipulator and the moving object. The junction location of the robot gripper with the object, together with grasp conditions, are partly defined by a set of local constraints. Thus, optimizing the robot motion in the approach phase of the transfer task leads to the statement of an optimal junction problem between the robot and the moving object. This optimal control problem is characterized by constrained final state and unknown traveling time. In such a case, Pontryagin"s maximum principle is a powerful mathematical tool for solving this optimization problem. Three simulated results of removing a mobile object on a conveyor belt are presented; the object is grasped in motion by a planar three-link manipulator.     

Coordinated Motion and Force Control of Multi-Limbed Robotic Systems

This analytic and experimental study proposes a control algorithm for coordinated position and force control for autonomous multi-limbed mobile robotic systems. The technique is called Coordinated Jacobian Transpose Control (CJTC). Such position/force control algorithms will be required if future robotic systems are to operate effectively in unstructured environments. Generalized Control Variables (GCVs), express in a consistent and coordinated manner the desired behavior of the forces exerted by the multi-limbed robot on the environment and a system's motions. The effectiveness of this algorithm is demonstrated in simulation and laboratory experiments on a climbing system.     

Leap Motion体感控制器的智能移动机械臂控制系统

设计一种新型的移动机械臂控制系统,可以利用Leap Motion体感控制器替代传统的人机交互方式,进行手部数据采集,将其识别到的手势动作经过计算机分析处理后,通过WiFi传输给开发板,进而控制机械臂模仿人手的动作,同时由于机械臂的载体是一个加载摄像头的移动小车,可以很好地结合机械臂执行各种远程遥控任务.实验结果表明,该移动机械臂便捷灵活、操作简单,能很好地应用在各种领域.     

基于模糊自适应控制的全向移动机器人的运动控制研究

由于四轮驱动全向移动机器人轮系分布的特点,四轮之间存在耦合关系,在运行过程中,机器人整体运动的稳定性及控制精度都不佳。针对此问题,本文设计一种基于模糊自适应控制器的误差修正方法,结合模糊控制和PD控制,在线对机器人体进行误差修正,并将整体误差按轮系结构分布合理分配到单个轮子上,从而将整体的误差修正转化为单个轮子的误差修正。通过在Matlab-Simulink环境下仿真实验表明,在使用模糊自适应控制器进行误差修正后,机器人对线速度及角速度的跟随性明显提高,改善了机器人运动控制的精度。     

Adaptive Polar-Space Motion Control for Embedded Omnidirectional Mobile Robots with Parameter Variations and Uncertainties

This paper presents an adaptive polar-space motion controller for trajectory tracking and stabilization of a three-wheeled, embedded omnidirectional mobile robot with parameter variations and uncertainties caused by friction, slip and payloads. With the derived dynamic model in polar coordinates, an adaptive motion controller is synthesized via the adaptive backstepping approach. This proposed polar-space robust adaptive motion controller was implemented into an embedded processor using a field-programmable gate array (FPGA) chip. Furthermore, the embedded adaptive motion controller works with a reusable user IP (Intellectual Property) core library and an embedded real-time operating system (RTOS) in the same chip to steer the mobile robot to track the desired trajectory by using hardware/software co-design technique and SoPC (system-on-a-programmable-chip) technology. Simulation results are conducted to show the merit of the proposed polar-space control method in comparison with a conventional proportional-integral (PI) feedback controller and a non-adaptive polar-space kinematic controller. Finally, the effectiveness and performance of the proposed embedded adaptive motion controller are exemplified by conducting several experiments on steering an embedded omnidirectional mobile robot.     

时变机器人系统的重复学习控制：一种混合学习方案(英文)

Repetitive learning control is presented for finite- time-trajectory tracking of uncertain time-varying robotic sys- tems.A hybrid learning scheme is given to cope with the con- stant and time-varying unknowns in system dynamics,where the time functions are learned in an iterative learning way,without the aid of Taylor expression,while the conventional differential learning method is suggested for estimating the constant ones. It is distinct that the presented repetitive learning control avoids the requirement for initial repositioning at the beginning of each cycle,and the time-varying unknowns are not necessary to be periodic.It is shown that with the adoption of hybrid learning, the boundedness of state variables of the closed-loop system is guaranteed and the tracking error is ensured to converge to zero as iteration increases.The effectiveness of the proposed scheme is demonstrated through numerical simulation.     

全方位移动机械手路径规划仿真平台的设计

机器人的三维仿真在机器人的研究中起着重要作用,论文以实验室中的全方位移动机械手为背景,建立了该移动机械手的运动学模型,然后利用VisualC++调用OpenGL建立了移动机械手的三维模型及路径规划的仿真平台,给出了实现算法,为移动机械手路径规划算法的研究提供了更为生动形象的仿真平台。     

Motion Planning Strategy for Finding an Object with a Mobile Manipulator in Three-Dimensional Environments

In this paper, we investigate the problem of minimizing the average time required to find an object in a known three-dimensional environment. We consider a 7-d.o.f. mobile manipulator with an 'eye-in-hand' sensor. In particular, we address the problem of searching for an object whose unknown location is characterized by a known probability density function. We present a discrete formulation, in which we use a visibility-based decomposition of the environment. We introduce a sample-based convex cover to estimate the size and shape of visibility regions in three dimensions. The resulting convex regions are exploited to generate trajectories that make a compromise between moving the manipulator base and moving the robotic arm. We also propose a practical method to approximate the visibility region in three dimensions of a sensor limited in both range and field of view. The quality and success of the generated paths depend significantly on the sensing robot capabilities. In this paper, we generate searching plans for a mobile manipulator equipped with a sensor limited in both field of view and range. We have implemented the algorithm and present simulation results.     

Whole-body Control of a Mobile Manipulator Using Feedback Linearization and Dual Quaternion Algebra

This paper presents the whole-body control of a nonholonomic mobile manipulator using feedback linearization and dual quaternion algebra. The controller, whose reference is a unit dual quaternion representing the desired end-effector pose, acts as a dynamic trajectory generator for the end-effector, and input signals for both nonholonomic mobile base and manipulator arm are generated by using the pseudoinverse of the whole-body Jacobian matrix. In order to deal with the nonholonomic constraints, the input signal to the mobile base generated by the whole-body motion control is properly remapped to ensure feasibility. The Lyapunov stability for the proposed controller is presented and experimental results on a real platform are performed in order to compare the proposed scheme to a traditional classic whole-body linear kinematic controller. The results show that, for similar convergence rate, the nonlinear controller is capable of generating smoother movements while having lower control effort than the linear controller.     

Swedish Wheeled Omnidirectional Mobile Robots: Kinematics Analysis and Control

Swedish wheeled robots have received growing attention over the last few years. Their kinematic models have interesting properties in terms of mobility and possible singularities. This paper addresses the issue of kinematic modeling, singularity analysis, and motion control for a generic vehicle equipped with ${bm N}$ Swedish wheels.      

移动机器人运动规划与计算机控制实现

论文针对移动机器人的链式系统提出了一种实时运动规划方法,通过在线更新复合分段常值与多项式输入控制律的系数,来驱使系统到达预定的目标,并将其应用于两伺服直流电机独立控制轮式移动机器人,采用计算机系统以及伺服放大器实现其控制,控制的结果达到了预期的效果。     

移动机器人网络控制系统的输出反馈控制

以线性时不变系统为被控对象,建立了四轮移动机器人网络控制系统的离散数学模型。诱导时延是影响系统性能的关键因素,通过在节点中设置缓冲区的方法可以将网络控制系统中的随机诱导时延转化为确定性时延,从而将网络控制系统由随机系统转化为确定性系统。通过被控对象移动机器人控制实验系统,设计了一个能处理网络诱导时延的输出反馈控制器,分析了采样周期和网络诱导时延对网络控制系统稳定性的影响。仿真结果表明了该控制器和控制策略的正确性及有效性。     

多点焊接机器人最优运动规划策略与算法研究

利用遗传算法寻找多点焊接机器人的最优运动规划的方法。第一步应用遗传算法对多点焊接工业机器人进行全局路径最优规划,确定机器人操作手终端遍历所有目标点的最短路径;然后在相邻目标点之间应用遗传算法进行关节空间的轨迹规划,寻找时间最短的最优轨迹。实验结果表明缩短了运行时间,提高了机器人的工作效率,可见方法的可行性和先进性。     

Multimode Control of a Large-Scale Robotic Manipulator

In this paper, the application of a piezoelectric stack actuator for vibration control in a large-scale robotic manipulator, called a macromanipulator, is studied. In this regard, mechanical design and mathematical modeling of the actuator are discussed. The structural flexibility of the macromanipulator includes deflection and torsional vibration modes. The vibration modes are detected using appropriate sensor attachments. Furthermore, a nominal transfer function matrix between the input signals to the actuators and the output voltages of the sensors is obtained. A closed-loop controller based on the obtained model is designed. Because of the presence of deflection and torsional vibration modes and model uncertainties resulting from manipulator motion, an robust controller is utilized. Experimental results are presented to validate the robustness and performance of the designed controller.     

球形移动机器人基于神经网络的反馈线性化运动控制研究与实验

实现了一种对球形移动机器人的滚动速度进行控制的方法.球形移动机器人的控制输入和状态输出间存在难以精确数学描述的非线性关系,本文采用径向基函数神经网络,以在线训练的方式建立了球形机器人输入与输出的非线性映射;然后采用反馈线性化方法,设计了球形机器人的速度控制器,该控制器由反馈线性化控制器和减小神经网络逼近误差的补偿控制器构成;给出了该控制器的实现步骤.多次实验结果表明,该方法可以实现球形移动机器人稳定的速度控制.     

机器人操作臂跟踪动态目标的轨迹规划方法

针对机器人操作臂跟踪运动目标问题,提出一种基于遗传算法的轨迹规划方法。通过对关节加速度的增量进行编码,实现在操作臂的关节空间进行轨迹优化,得到操作臂在跟踪运动目标过程中所需要的轨迹。仿真计算的结果表明,所提出的方法是有效的。