Intelligent mobile manipulator navigation using adaptive neuro-fuzzy systems

The work presented in this paper deals with the problem of autonomous and intelligent navigation of mobile manipulator, where the unavailability of a complete mathematical model of robot systems and uncertainties of sensor data make the used of approximate reasoning to the design of autonomous motion control very attractive.A modular fuzzy navigation method in changing and dynamic unstructured environments has been developed. For a manipulator arm, we apply the robust adaptive fuzzy reactive motion planning developed in [J.B. Mbede, X. Huang, M. Wang, Robust neuro-fuzzy sensor-based motion control among dynamic obstacles for robot manipulators, IEEE Transactions on Fuzzy Systems 11 (2) (2003) 249-261]. But for the vehicle platform, we combine the advantages of probabilistic roadmap as global planner and fuzzy reactive based on idea of elastic band. This fuzzy local planner based on a computational efficient processing scheme maintains a permanent flexible path between two nodes in network generated by a probabilistic roadmap approach. In order to consider the compatibility of stabilization, mobilization and manipulation, we add the input of system stability in vehicle fuzzy navigation so that the mobile manipulator can avoid stably unknown and/or dynamic obstacles. The purpose of an integration of robust controller and modified Elman neural network (MENN) is to deal with uncertainties, which can be translated in the output membership functions of fuzzy systems.     

Neural networks to determine task oriented dexterity indices for an underwater vehicle-manipulator system

A method for the fast approximation of dexterity indices for given underwater vehicle-manipulator systems (UVMS) configurations is presented. Common underwater tasks are associated with two well-known dexterity indices and two types of neural networks are designed and trained to approximate each one of them. The method avoids the lengthy calculation of the Jacobian, its determinant and the computationally expensive procedure of singular value decomposition required to compute the dexterity indices. It provides directly and in a considerably reduced computational time the selected dexterity index value for the given configuration of the system. The full kinematic model of the UVMS is considered and the NN training dataset is formulated by the conventional calculation of the selected dexterity indices. A comparison between the computational cost of the analytical calculation of the indices and their approximation by the two NN is presented for the validation of the proposed approach. This paper contributes mainly on broadening the applications of NN to a problem of high complexity and of high importance for UVMS high performance intervention.     

A kinetostatic index to measure the task-executing ability of robotic manipulators with limit-driven characteristics of actuators

Dexterity is an important issue for the design, trajectory planning and control of robotic manipulators. However, even though a lot of robot manipulators are driven by DC motors, no dexterity measures were introduced to evaluate how efficient a manipulator system is for performing a required task in the case of taking the limit-driven characteristics of the DC motor into consideration. In this study, we introduce a new kinetostatic dexterity index to measure the task-executing ability of robotic manipulators where the possible maximum velocity and force of the required task are derived subject to the heat-converted power limit of the DC motor. The measure is to evaluate how efficient a manipulator system is to execute a required task, while the limit-driven characteristics of its actuators are taken into consideration. Two examples are used to show that the proposed dexterity index is task-dependent and changed due to the tasks.     

Fuzzy sliding-mode control with rule adaptation for nonlinear systems

Abstract: A fuzzy sliding-mode control with rule adaptation design approach with decoupling method is proposed. It provides a simple way to achieve asymptotic stability by a decoupling method for a class of uncertain nonlinear systems. The adaptive fuzzy sliding-mode control system is composed of a fuzzy controller and a compensation controller. The fuzzy controller is the main rule regulation controller, which is used to approximate an ideal computational controller. The compensation controller is designed to compensate for the difference between the ideal computational controller and the adaptive fuzzy controller. Fuzzy regulation is used as an approximator to identify the uncertainty. The simulation results for two cart–pole systems and a ball–beam system are presented to demonstrate the effectiveness and robustness of the method. In addition, the experimental results for a tunnelling robot manipulator are given to demonstrate the effectiveness of the system.     

A general formulation and approach to constrained,continuum manipulation

A continuum manipulator is particularly suitable for performing tasks in cluttered environments with limited space for maneuvering and is even more flexible with a mobile base. However, to perform a task, the motion of a continuum manipulator must not only avoid obstacles, i.e. subject to environment constraints, but also satisfy certain position and orientation constraints imposed by the task. An important open issue is how to enable a (mobile) continuum manipulator to perform a task-constrained motion while avoiding obstacles. In this paper, we introduce a general formulation of the problem and an approach to automatic planning of mobile continuum manipulation under general task and environmental constraints. The effectiveness of the approach is verified by simulation and real experiments.     

Kinematic Analysis of a Macro–Micro Redundantly Actuated Parallel Manipulator

In this paper the kinematic and Jacobian analysis of a macro–micro parallel manipulator is studied in detail. The manipulator architecture is a simplified planar version adopted from the structure of the Large Adaptive Reflector (LAR), the Canadian design of the next generation of giant radio telescopes. This structure is composed of two parallel and redundantly actuated manipulators at the macro and micro level, which both are cable-driven. Inverse and forward kinematic analysis of this structure is presented in this paper. Furthermore, the Jacobian matrices of the manipulator at the macro and micro level are derived, and a thorough singularity and sensitivity analysis of the system is presented. The kinematic and Jacobian analysis of the macro–micro structure is extremely important to optimally design the geometry and characteristics of the LAR structure. The optimal location of the base and moving platform attachment points in both macro and micro manipulators, singularity avoidance of the system in nominal and extreme maneuvers, and geometries that result in high dexterity measures in the design are among the few characteristics that can be further investigated from the results reported in this paper. Furthermore, the availability of the extra degrees of freedom in a macro–micro structure can result in higher dexterity provided that this redundancy is properly utilized. In this paper, this redundancy is used to generate an optimal trajectory for the macro–micro manipulator, in which the Jacobian matrices derived in this analysis are used in a quadratic programming approach to minimize performance indices like minimal micro manipulator motion or singularity avoidance criterion.     

移动机械手鲁棒自适应模糊控制

基于旋量理论建立了非完整移动机械手系统的动力学模型,通过反步控制技术,应用非线性参数化模糊逻辑系统设计了移动机械手的鲁棒自适应模糊控制器.该控制器放松了移动机械手控制器设计中斜对称性的要求,对移动机械手系统中存在的参数或外界扰动等不确定性具有较强的鲁棒性和自适应能力.理论证明和仿真结果表明,所设计的控制器是有效的.     

An Adaptive Fuzzy Control Model for Multi-Joint Manipulators

Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics, random disturbances and load variations. To account for uncertain disturbances in the operation of manipulators, we propose an adaptive manipulator control method based on a multi-joint fuzzy system, in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable. The control algorithm of the system is a MIMO (multi-input-multi-output) fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error. It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required. Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity, coupling and uncertainty. Therefore, the proposed algorithm has good practical application prospects and promotes the development of complex control systems.     

Performance evaluation of dynamically linearized and kinematically redundant planar manipulators

The objective of this research is to investigate the feasibility of a theoretical development which could lead to advanced manipulator concepts offering fast dynamic and control features. Specifically, the application of “dynamic linearization” to a kinematically redundant planar manipulator is studied. In comparing such a manipulator with a standard non-linear, non-redundant design it is shown that in addition to the expected merits in linearity, dexterity, and computational simplicity, savings in actuator energy consumption can also be realized using a relative simple trajectory optimization scheme.     

Redundancy modelling and resolution for robotic mobile manipulators: a general approach

In this work the topic of kinematic redundancy modelling and resolution for robotic mobile manipulators is considered. A set of redundancy parameters is introduced to define a general inverse kinematic procedure for mobile manipulators. Then, redundancy is treated as a non-linear optimization problem with the purpose of finding robot configurations that maximize the designed metric measures. Some strategies to design the optimization objective function are introduced in order to achieve desirable redundant behaviours, such as obstacles avoidance, mobile base motions reductions and dexterity optimization. Moreover, the robot controller has been developed following an object-oriented software architecture principle that allows to keep it general and robot independent. As a prove of reliability and generality of our approach, the same controller has been used to control several different mobile manipulators in a simulation environment, as well as a real KUKA youBot robot.     

Optimization design of general triglide parallel manipulators

Optimization design of parallel manipulators has attracted much interest from researchers in recent years. The reported methodologies attempted to achieve optimal design of parallel manipulators considering several properties, such as dexterity, stiffness, and space utilization, which are important parameters to be considered. However, stiffness analysis considered by many researchers generally ignores the deformation of the mobile platform. For space utilization, there is no reported method to consider the variation in the physical size caused by different postures of the manipulator. Additionally, although optimization of a linear delta and an orthoglide has been presented by several researchers, optimization of a general triglide has not been reported. In order to address these issues, this paper presents a multi-objective optimization addressing dexterity, stiffness, and space utilization of a general triglide. Its stiffness matrix is obtained considering the deformation of mobile platform, limbs, and actuators. A novel stiffness index is used to evaluate its stiffness property considering external wrench applied on the manipulator. The physical size of the triglide is represented using both a constant size and a variable size. Comparing with a reported optimization methodology, it is proven that the proposed method is capable of providing optimal solutions with better properties.     

A 6-DOF adaptive parallel manipulator with large tilting capacity

In this paper, a novel 6 degrees of freedom (DOFs) adaptive parallel manipulator with large tilting capacity is presented. The manipulator consists of four identical peripheral limbs and one center limb connecting the base and the moving platform. Due to the special architecture, the doubly actuated center limb of the manipulator could have infinite inverse solutions. In every configuration of the end-effector, the manipulator can adapt its center limb to the position and orientation with best dexterity. An optimization equation for obtaining the optimized dexterity of the manipulator is introduced to solve this nonholonomic problem, which also makes the manipulator capable of large tilting capacity. Targeting for the application of five-face machining, the detailed kinematic analysis of the manipulator is developed, which includes the closed-form solutions of inverse position problems, the singularity, dexterity, workspace and tilting capability. The analysis developed in this paper shows that the proposed manipulator has large tilting capacity and thus a suitable candidate for five-face machining.     

Design optimization of a spatial six degree-of-freedom parallel manipulator based on artificial intelligence approaches

Optimizing the system stiffness and dexterity of parallel manipulators by adjusting the geometrical parameters can be a difficult and time-consuming endeavor, especially when the variables are diverse and the objective functions are excessively complex. However, optimization techniques that are based on artificial intelligence approaches can be an effective solution for addressing this issue. Accordingly, this paper describes the implementation of genetic algorithms and artificial neural networks as an intelligent optimization tool for the dimensional synthesis of the spatial six degree-of-freedom (DOF) parallel manipulator. The objective functions of system stiffness and dexterity are derived according to kinematic analysis of the parallel mechanism. In particular, the neural network-based standard backpropagation learning algorithm and the Levenberg–Marquardt algorithm are utilized to approximate the analytical solutions of system stiffness and dexterity. Subsequently, genetic algorithms are derived from the objective functions described by the trained neural networks, which model various performance solutions. The multi-objective optimization (MOO) of performance indices is established by searching the Pareto-optimal frontier sets in the solution space. Consequently, the effectiveness of this method is validated by simulation.     

Performance Analysis and Application of a Redundantly Actuated Parallel Manipulator for Milling

This paper deals with the performance analysis of a 3-degree-of-freedom (3-DOF) planar parallel manipulator with actuation redundancy. Closed-form solutions are developed for both the inverse and direct kinematics about the redundant parallel manipulator. In performance analysis phase, the dexterity is analyzed, three kinds of singularities are investigated, and the stiffness is estimated. Compared with the corresponding non-redundant parallel manipulator with the redundant link removed, the redundantly actuated one has better dexterity, litter singular configurations and higher stiffness. The redundantly actuated parallel manipulator was applied to the design of a 4-DOF hybrid machine tool which also includes a feed worktable to demonstrate its applicability.     

Automatic visual guidance of a forklift engaging a pallet

This paper presents the development of a prototype vision-guided forklift system for the automatic engagement of pallets. The system is controlled using the visual guidance method of mobile camera-space manipulation, which is capable of achieving a high level of precision in positioning and orienting mobile manipulator robots without relying on camera calibration. The paper contains development of the method, the development of a prototype forklift as well as experimental results in actual pallet engagement tasks. The technology could be added to AGV systems enabling them to engage arbitrarily located pallets. It also could be added to standard forklifts as an operator assist capability.     

Direct adaptive fuzzy control for a class of MIMO nonlinear systems

This article presents a direct adaptive fuzzy control scheme for a class of uncertain continuous-time multi-input multi-output nonlinear (MIMO) dynamic systems. Within this scheme, fuzzy systems are employed to approximate an unknown ideal controller that can achieve control objectives. The adjustable parameters of the used fuzzy systems are updated using a gradient descent algorithm that is designed to minimize the error between the unknown ideal controller and the fuzzy controller. The stability analysis of the closed-loop system is performed using a Lyapunov approach. In particular, it is shown that the tracking errors are bounded and converge to a neighborhood of the origin. Simulations performed on a two-link robot manipulator illustrate the approach and exhibit its performance.     

基于自适应动态规划的移动装弹机械臂轨迹控制

针对移动装弹机械臂系统非线性、强耦合、受多种不确定因素影响的问题,本文基于自适应动态规划方法,提出了仅包含评价网络结构的轨迹跟踪控制方法,有效减小了系统跟踪误差.首先,考虑到系统非线性特性、变量间强耦合作用及重力因素的影响,通过拉格朗日方程建立了移动装弹机械臂的动力学模型.其次,针对系统存在不确定性上界未知的问题,建立单网络评价结构,通过策略迭代算法,求解哈密顿–雅可比–贝尔曼方程,基于李雅普诺夫稳定性理论,设计了自适应动态规划轨迹跟踪控制方法.最后,通过仿真实验将该控制方法与自适应滑模控制方法进行了对比,进一步检验了所设计控制方法的有效性.     

移动机械手的T-S模糊控制系统

对移动机械手进行动力学分析,给出了统一的移动机械手整体动力学建模方法;针对移动机械手的非线性特点,提出T-S模糊控制算法,将复杂的非线性强耦合系统转化为若干线性问题的组合;利用线性矩阵不等式方法为该系统设计了状态反馈控制器,并给出了整体系统的稳定性证明。仿真实验证明该控制器具有良好的控制效果和稳定性。     

A family of stewart platforms with optimal dexterity

Stewart platform configurations (architectures and poses) optimizing local dexterity are investigated. The condition number of the Jacobian matrix is used to quantify the dexterity of the manipulator. For a platform-centered Jacobian reference location and a given characteristic length for scaling purposes, a two-parameter family of optimal configurations is shown to exist. Two suitable architectural parameters defining the family are identified and properties of the optimal configurations are discussed. The optimization results are shown to be easily extended for other Jacobian reference locations and for other singular value-based local dexterity measures. It is suggested that the existence of a two-parameter family of optimal local configurations could be exploited to aid in the resolution of optimal architectures for global measures.     

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。