Encoder based online motion planning and feedback control of redundant manipulators

This paper proposes and investigates an online motion planning and feedback control (OMPFC) scheme for redundant manipulators via techniques of quadratic programming and rotary encoder. The proposed OMPFC scheme is performed on a planar six degrees-of-freedom (DOF) manipulator. This robotic scheme incorporates the feedback of task-space position error. The joint state is obtained in real time via rotary encoders equipped on the physical manipulator. The original scheme is finally reformulated as a unified quadratic program (QP). The QP is solved online during the joint motion by employing an efficient numerical algorithm. Simulation and experimental results validate the physical realizability, online property, and efficacy of the proposed OMPFC scheme (including the employed numerical algorithm).     

轮式移动机械臂的建模与仿真研究

移动机械臂系统一般由移动平台和机器臂组成，它既具有机器臂的操作灵活性，又具有移动机器人的可移动性，因此其应用范围要比单个系统宽得多。这篇文章主要研究了由非完整移动平台和完整机械臂组成的轮式移动机械臂系统的建模、跟踪控制及仿真问题。首先。利用拉格朗日动力学方程和非完整动力学罗兹方程建立了移动机械臂系统的精确数学模型；然后。利用非线性反馈将系统解耦。采用类PD控制器进行控制。在考虑了非完整约束及移动平台和机械臂的动态交互影响情况下，该控制算法保证系统同时跟踪给定的终端执行器和平台轨迹；最后，使用Maflah6．5对系统进行了仿真研究，仿真结果表明了其数学模型及控制方法的正确有效性。     

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.     

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.     

Fault-tolerant motion planning and control of redundant manipulator

One important issue in the motion planning of a kinematic redundant manipulator is fault tolerance. In general, if the motion planner is fault tolerant, the manipulator can achieve the required path of the end-effector even when its joint fails. In this situation, the contribution of the faulty joint to the end-effector is required to be compensated by the healthy joints to maintain the prescribed end-effector trajectory. To achieve this, this paper proposes a fault-tolerant motion planning scheme by adding a simple fault-tolerant equality constraint for the faulty joint. Such a scheme is then unified into a quadratic program (QP), which incorporates joint-physical constraints such as joint limits and joint-velocity limits. In addition, a numerical computing solver based on linear variational inequalities (LVI) is presented for the real-time QP solving. Simulative studies and experimental results based on a six degrees-of-freedom (DOF) redundant robot manipulator with variable joint-velocity limits substantiate the effectiveness of the proposed fault-tolerant scheme and its solution.     

Robust tracking control of a unicycle-type wheeled mobile manipulator using a hybrid sliding mode fuzzy neural network

This article presents a robust tracking controller for an uncertain mobile manipulator system. A rigid robotic arm is mounted on a wheeled mobile platform whose motion is subject to nonholonomic constraints. The sliding mode control (SMC) method is associated with the fuzzy neural network (FNN) to constitute a robust control scheme to cope with three types of system uncertainties; namely, external disturbances, modelling errors, and strong couplings in between the mobile platform and the onboard arm subsystems. All parameter adjustment rules for the proposed controller are derived from the Lyapunov theory such that the tracking error dynamics and the FNN weighting updates are ensured to be stable with uniform ultimate boundedness (UUB).     

Endogenous configuration space approach to mobile manipulators: A derivation and performance assessment of Jacobian inverse kinematics algorithms

By a mobile manipulator we mean a robotic system composed of a non-holonomic mobile platform and a holonomic manipulator fixed to the platform. A taskspace of the mobile manipulator includes positions and orientations of its end effector relative to an inertial coordinate frame. The kinematics of a mobile manipulator are represented by a driftless control system with outputs. Admissible control functions of the platform along with joint positions of the manipulator constitute the endogenous configuration space. Endogenous configurations have a meaning of controls. A map from the endogenous configuration space into the taskspace is referred to as the instantaneous kinematics of the mobile manipulator. Within this framework, the inverse kinematic problem for a mobile manipulator amounts to defining an endogenous configuration that drives the end effector to a desirable position and orientation in the taskspace. Exploiting the analogy between stationary and mobile manipulators we present in the paper a collection of regular and singular Jacobian inverse kinematics algorithms. Their performance is evaluated on the basis of intense computer simulations.     

Neuro-fuzzy and model-based motion control for mobile manipulator among dynamic obstacles

This paper focuses on autonomous motion control of a nonholonomic platform with a robotic arm, which is called mobile manipulator. It serves in transportation of loads in imperfectly known industrial environments with unknown dynamic obstacles. A union of both procedures is used to solve the general problems of collision-free motion. The problem of collision-free motion for mobile manipulators has been approached from two directions, Planning and Reactive Control. The dynamic path planning can be used to solve the problem of locomotion of mobile platform, and reactive approaches can be employed to solve the motion planning of the arm. The execution can generate the commands for the servo-systems of the robot so as to follow a given nominal trajectory while reacting in real-time to unexpected events. The execution can be designed as an Adaptive Fuzzy Neural Controller. In real world systems, sensor-based motion control becomes essential to deal with model uncertainties and unexpected obstacles.     

Repetitive motion of redundant robots planned by three kinds of recurrent neural networks and illustrated with a four-link planar manipulator’s straight-line example

In this paper, a dual neural network, LVI (linear variational inequalities)-based primal-dual neural network and simplified LVI-based primal-dual neural network are presented for online repetitive motion planning (RMP) of redundant robot manipulators (with a four-link planar manipulator as an example). To do this, a drift-free criterion is exploited in the form of a quadratic performance index. In addition, the repetitive-motion-planning scheme could incorporate the joint physical limits such as joint limits and joint velocity limits simultaneously. Such a scheme is finally reformulated as a quadratic program (QP). As QP real-time solvers, the aforementioned three kinds of neural networks all have piecewise-linear dynamics and could globally exponentially converge to the optimal solution of strictly-convex quadratic-programs. Furthermore, the neural-network based RMP scheme is simulated based on a four-link planar robot manipulator. Computer-simulation results substantiate the theoretical analysis and also show the effective remedy of the joint angle drift problem of robot manipulators.     

多移动机器人系统研究发展近况

多移动机器人系统具有广泛的应用前景, 也是近年来机器人研究的热门课题之一. 本文对国内外近年来关于多移动机器人系统的研究工作进行了总结和分析, 重点介绍了多机器人系统的任务规划、运动规划、协调控制等问题的研究发展现状. 最后指出了多移动机器人系统研究急需解决的若干重要问题.     

Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach

This paper addresses the robust trajectory tracking problem for a redundantly actuated omnidirectional mobile manipulator in the presence of uncertainties and disturbances. The development of control algorithms is based on sliding mode control (SMC) technique. First, a dynamic model is derived based on the practical omnidirectional mobile manipulator system. Then, a SMC scheme, based on the fixed large upper boundedness of the system dynamics (FLUBSMC), is designed to ensure trajectory tracking of the closed-loop system. However, the FLUBSMC scheme has inherent deficiency, which needs computing the upper boundedness of the system dynamics, and may cause high noise amplification and high control cost, particularly for the complex dynamics of the omnidirectional mobile manipulator system. Therefore, a robust neural network (NN)-based sliding mode controller (NNSMC), which uses an NN to identify the unstructured system dynamics directly, is further proposed to overcome the disadvantages of FLUBSMC and reduce the online computing burden of conventional NN adaptive controllers. Using learning ability of NN, NNSMC can coordinately control the omnidirectional mobile platform and the mounted manipulator with different dynamics effectively. The stability of the closed-loop system, the convergence of the NN weight-updating process, and the boundedness of the NN weight estimation errors are all strictly guaranteed. Then, in order to accelerate the NN learning efficiency, a partitioned NN structure is applied. Finally, simulation examples are given to demonstrate the proposed NNSMC approach can guarantee the whole system's convergence to the desired manifold with prescribed performance.     

Keeping smart, omnidirectional eyes on you [adaptive panoramic stereovision]

An adaptive panoramic stereo approach for two cooperative mobile platform is presented. There are four key features in the approach: 1) omnidirectional stereovision with an appropriate vertical FOV, and a simple camera calibration method; 2) cooperative mobile platforms for mutual dynamic calibration and best view planning; 3) 3D matching after meaningful object (human subject) extraction; and 4) real-time performance. The integration of omnidirectional vision with mutual awareness and dynamic calibration strategies allows intelligent cooperation between visual agents. This provides an effective way to solve the problems of limited resources, view planning, occlusion, and motion detection of movable robotic platforms. Experiments have shown that this approach is quite promising.     

A time controlling neural network for time‐varying QP solving with application to kinematics of mobile manipulators

To obtain the solution for time‐varying quadratic programming (QP), a time controlling neural network (TCNN) is presented and discussed. The traditional recurrent neural networks provide a prospect for real‐time calculations and repeatable trajectory control of the mobile manipulators due to its high executing processing and nonlinear disposal ability. However, the convergent time is still a considerable point for the solution of a dynamic system dealing with synchronism and robustness. In this note, a TCNN model by incorporating an initial rectified term is applied to solve the online calculation problems and the convergent time can be controlled in advance. Theoretical analyses on stability, prespecified time and convergence are rigorously clarified. Finally, effectiveness and precision of the TCNN model for the solution of a QP example have been verified. In addition, a repetitive trajectory planning for a three‐wheel manipulator is introduced to demonstrate the superiority of the TCNN.     

Robust Interaction Control of a Mobile Manipulator – Dynamic Model Based Coordination

This paper discusses the modeling and control of a spatial mobile manipulator which consists of a robotic manipulator mounted upon a wheeled mobile platform. The nonholonomic model, which assumes perfect contact between the wheels and the ground, is obtained using the Lagrange–d'Alembert formulation. Also, the dynamic model, which considers slip of the platform's tires, is developed using the Newton–Euler method and incorporates Dugoff's tire friction model. The complexity of the model is increased by introducing kinematic redundancy which is created when a multi-linked manipulator is used. The kinematic redundancy is resolved by decomposing the mobile manipulator into two subsystems; the mobile platform and the manipulator. Based on the coordination scheme used to resolve the kinematic redundancy, a robust interaction control algorithm, in which suitable controllers are designed for the two subsystems, is developed and applied. The adverse effect of the wheel slip on the tracking of commanded motion is discussed in the simulation. For the dynamic model, a robust control approach is employed to minimize the harmful effect of the wheel slip on the tracking performance. Simulation results show the promise of the developed algorithm.     

Autonomous robotic capture of non-cooperative target using visual servoing and motion predictive control

This paper presents a framework for autonomous capture operation of a non-cooperative mobile target in a 3-dimensional workspace using a robotic manipulator with visual servoing. The visual servoing with an eye-in-hand configuration is based on motion predictive control using Kalman filter for the on-line state and parameter estimation of the target. A transitional decision making process is developed to guide the robotic manipulator between the different phases of the capture operation by employing a custom metric that translates visual misalignments between the end-effector and the target into a guidance measurement. These phases include the target acquisition and approach stage and the alignment and capture phase. Experiments have been carried out on a custom designed and built robotic manipulator with 6 degrees of freedom. The objective is to evaluate the performance of the proposed motion predictive control scheme for the autonomous capturing task and to demonstrate the robustness of the proposed control scheme in the presence of noise and unexpected disturbances in vision system, sensory-motor coordination and constraints for the execution in real environments. Experimental results of the visual servoing control scheme integrated with the motion predictive Kalman filter indicate the feasibility and applicability of the proposed control scheme. It shows that when the target motion is properly predicted, the tracking and capture performance has been improved significantly.     

Unconstrained and constrained motion control of a planar two-link structurally flexible robotic manipulator

Unconstrained and constrained motion control of a planar two-link structurally-flexible robotic manipulator are considered in this study. The dynamic model is obtained by using the extended Hamilton's principle and the Galerkin criterion. A method is presented to obtain the linearized equations of motion in Cartesian space for use in designing the control system. The approach to solving the control problem is to use feedforward and feedback control torques. The feedforward torques maneuver the flexible manipulator along a nominal trajectory and the feedback torques minimize any deviations from the nominal trajectory. The feedforward and feedback torques are obtained by solving the inverse dynamics problem for the rigid manipulator and designing linear quadratic Gaussian with loop transfer recovery (LQG/LTR) compensators, respectively. The LQG/LTR design methodology is exploited to design a robust feedback control system that can handle modeling errors and sensor noise, and operate on Cartesian space trajectory errors. Computer simulated results are presented for an example planar, two-link, structurally flexible robotic manipulator. © 1994 John Wiley & Sons, Inc.     

Elastic roadmaps—motion generation for autonomous mobile manipulation

The autonomous execution of mobile manipulation tasks in unstructured, dynamic environments requires the consideration of various motion constraints. The task itself imposes constraints, of course, but so do the kinematic and dynamic limitations of the manipulator, unpredictably moving obstacles, and the global connectivity of the workspace. All of these constraints need to be updated continuously in response to sensor feedback. We present the elastic roadmap framework, a novel feedback motion planning approach capable of satisfying all of these motion constraints and their respective feedback requirements. This framework is validated in simulation and real-world experiments using a mobile manipulation platform and a stationary manipulator.     

六自由度机械臂约束预测控制系统的设计

本文提出了一种基于约束预测控制的机械臂实时运动控制方法.该控制方法分为两层,分别设计了约束预测控制器和跟踪控制器.其中,约束预测控制器在考虑系统物理约束的条件下,在线为跟踪控制器生成参考轨迹;跟踪控制器采用最优反馈控制律,使机械臂沿参考轨迹运动.为了简化控制器的设计和在线求解,本文采用输入输出线性化的方式简化机械臂动力学模型.同时,为了克服扰动,在约束预测控制器中引入前馈策略,提出了带前馈一反馈控制结构的预测控制设计.因此,本文设计的控制器可以使机械臂在满足物理约束的条件下快速稳定地跟踪到目标位置.通过在PUMA560机理模型上进行仿真实验,验证了预测控制算法的可行性和有效性.     

Different-level two-norm and infinity-norm minimization to remedy joint-torque instability/divergence for redundant robot manipulators

To remedy the joint-torque instability/divergence phenomenon arising in the conventional infinity-norm torque-minimization (INTM) scheme, and prevent the occurrence of high joint-velocity and joint-acceleration as well, a different-level bi-criteria minimization scheme is proposed and investigated in this paper for redundant robot manipulators with physical constraints (e.g., joint-angle limits, joint-velocity limits and joint-acceleration limits) considered. Such a scheme combines the minimum two-norm joint-velocity and infinity-norm joint-torque solutions via a weighting factor, which guarantees the final joint-velocity of the motion to be near zero (more acceptable for engineering application). In addition, the different-level scheme is reformulated as a general quadratic program (QP) and resolved at the joint-acceleration level. Computer-simulation results based on the PUMA560 robot manipulator further demonstrate the effectiveness and advantages of the proposed different-level bi-criteria minimization scheme for robotic redundancy resolution.