How to Control Robots Interacting with Dynamic Environment

The goal of this paper is to shed light on the control problem of constrained robot motion from the aspect of the dynamical nature of the environment with which the robot is in contact. Therefore, the criticism of traditional hybrid control which allows position/force feedback loops to split into independent control with respect to position and force, is not the main point we want to make. Reference to the papers written by the founders of hybrid control and their numerous followers served only to better understand the reason and motivation for suggesting a different approach to control of robots interacting with environment.The paper has a predominantly review character, based on recently published work. It also contains some new, unpublished results in the framework of the unified approach to the position/force control of robots, proposed by the present author and his co-workers. By pointing to the possibility of introducing an environment dynamics in the contact tasks of the machining type, the author emphasizes that the proposed dynamically interactive control can be applied to a completely different class of tasks, in which a contact is made between the system (constructions or structure) and very specific kinds of dynamic environments.     

Impedance Control as a Particular Case of the Unified Approach to the Control of Robots Interacting with a Dynamic Known Environment

This paper investigates the problem of impendance control using a unified approach to contact tasks control in robotics, where the interpretation of the contact between the robot and its known environment is based on a sufficiently correct treating of interaction between the environment and robot dynamics. Apart from brief survey of all more important results in the field of impedance control, it will be shown that, from the standpoint of the active compliance method which considers the control with respect to position and force simultaneously, impedance control can be considered as one particular case. The direct aim of the paper is to improve the transient dynamic response immediately after the contact. In that way the performance of impedance control is improved just in the phase in which its quality is of decisive importance.     

Singular Perturbation Model of Robots with Elastic Joints and Elastic Links Constrained by Rigid Environment

A robot with distributed flexibility in the links and lumped flexibility in the joints is considered in this paper. First the model of the system in free motion is formulated as a set of ordinary differential equations, adopting a finite number of modes of the link deformation. Then algebraic constraint equations on the generalized coordinates of the system are added, to account for the loss of degrees of freedom due to the contact with rigid environment. A reduced order model, expressed in the residual degrees of freedom is then derived, based on a coordinate partitioning procedure. The singularly perturbed model of the system is finally computed, and the expression of the fast subsystem is given. The special cases of a robot with rigid joints or rigid links are also addressed.     

含有未驱动关节的空间机器人控制

含有未驱动关节的自由潭浮空间机器人具有不可积分的速度和加速度约束，因而是一个二阶非完整系统，通过分析系统的动力学结构，本文设计了一种全 基于速度控制的方法控制未驱动关节，然后采用多步混合控制策略实现空间机器人的定位跟踪。     

Impedance Control with On-Line Neural Network Compensator for Dual-Arm Robots

A controller design strategy of dual-arm robots is proposed in this paper. The controller consists of a central controller and three force controllers. The central controller is used to calculate each arms force command according to the desired object motion. A force controller is used in each arm to track the commanding force. Another force controller is used to track the desired contact force between the manipulated object and its environment. The force controller can be partitioned into three parts. The computed torque method is used to linearize and decouple the dynamics of a manipulator. An impedance controller is then added to regulate the mechanical impedance between the manipulator and its environment. In order to track a reference force signal, an on-line neural network is used to compensate the effect of unknown parameters of the manipulator and environment. The simulation results are reported to show the performance of the neural network compensator.     

力觉临场感机器人系统中环境动力学模型的研究

通过对力觉临场感机器人系统中环境的动力学研究，提出了分段描述环境动力学特征的观点，并进一步讨论了不同工作区中环境的动力学模型，分析了不同作业方式下，动力学的变化情况，阐述了在该系统中，环境的等效阻抗具有非线性，时实性，对系统的稳定性分析，控制算法和虚拟环境技术中的虚拟力觉反馈的准确再现具有重要意义。     

动态双足机器人的控制与优化研究进展

对动态双足机器人的可控周期步态的稳定性、鲁棒性和优化控制策略的国内外研究现状与发展趋势进行了探讨.首先,介绍动态双足机器人的动力学数学模型,进一步,提出动态双足机器人运动步态和控制系统原理;其次,讨论动态双足机器人可控周期步态稳定性现有的研究方法,分析这些方法中存在的缺点与不足;再次,研究动态双足机器人的可控周期步态优化控制策略,阐明各种策略的优缺点;最后,给出动态双足机器人研究领域的难点问题和未来工作,展望动态双足机器人可控周期步态与鲁棒稳定性及其应用的研究思路.     

Dynamics and Control of Elastic Joint Manipulators

The investigations presented in this paper are based on our previousstudies where the modeling and control problems of rigid body manipulatorswere treated through the so-called vector-parametrization of the SO(3)group. The nice property of this parametrization, which also displays a Liegroup structure, is that it drastically simplifies some considerations andreduces the computational burden in solving direct kinematic problems,inverse kinematic problems and dynamic modeling by more than 30 hitherto.This statement, which is valid for models built through vector-parameter,becomes stronger in pure vector-parameter considerations. It is provedadditionally that the computational effectiveness of the vector-parameterapproach increases with the increasing number of the revolute degrees offreedom. Here we show that this can be used successfully in the problems ofelastic joint manipulators where, besides the real n links,nfictious links are included and an additional nrevolute degrees of freedom are involved. The present paper also considersthe role of group representations of the rotation motions in the modelingand control of manipulators with elastic joints. Dynamic modelsthrough vector-parameter and in purevector-parameter form are developed and the inverse dynamic problem isdiscussed. It is shown that the nonlinear equations of motion are globallylinearizable by smooth invertible coordinate transformation and nonlinear state feedback.     

基于UKF的移动机器人主动建模及模型自适应控制方法

利用基于无色卡尔曼滤波（Unscented Kalman Filter, UKF）的状态和参数联合估计方法对移动机器人进行在线主动建模,基于该主动模型的逆动力学控制方法,实现了移动机器人对其自身不确定因素的自主性. 在针对全方位移动机器人的仿真实验中,验证了UKF对时变的状态和参数的收敛性和跟踪能力,并给出了不确定界. 基于主动建模的逆动力学控制方法与常值PID控制方法的比较结果,验证了该方法的有效性.     

Dynamic Feedback Control of XYnR̄ Planar Robots with n Rotational Passive Joints

We consider the problem of trajectory planning and control for an XYnR? Planar robot with the first two joints (rotational or prismatic) actuated and n rotational passive joints, moving both in the presence and the absence of gravity. Under the assumption that each passive link is attached at the center of percussion of the previous passive link, dynamics of the system can be expressed through the behavior of n special points of the plane. These points are called link‐related acceleration points (LRAP) since their instantaneous acceleration is oriented as the axis of the related passive links. Moreover, LRAP dynamics present a backward recursive form which can be exploited to recursively design a dynamic feedback that completely linearizes the system equations. We use this approach to solve trajectory planning and tracking problems and report simulation results obtained for an RR2R? robot having the first two rotational joints actuated. © 2003 Wiley Periodicals, Inc.     

Position-Based Fuzzy Force Control for Dual Industrial Robots

In this paper, a fuzzy force control framework is proposed for dual-industrial robot systems. The master/slave control method is used in dual-robot systems. Two MITSUBISHI MELFA RV-M1 industrial robots, one is equipped with an BL Force/Torque sensor and the other is not, are utilized for implementing the dual-arm system. In order to adapt various stiffness of the holding object, an adaptable fuzzy force control scheme has been proposed to improve the performance. The ability of the adaptable force control system is achieved by tuning the scaling factor of the fuzzy logic controller. Successful experiments are carried out for the dual-robot system handling an object.     

Neural Network Force Control for Industrial Robots

In this paper, we present a hierarchical force control framework consisting of a high level control system based on neural network and the existing motion control system of a manipulator in the low level. Inputs of the neural network are the contact force error and estimated stiffness of the contacted environment. The output of the neural network is the position command for the position controller of industrial robots. A MITSUBISHI MELFA RV-M1 industrial robot equipped with a BL Force/Torque sensor is utilized for implementing the hierarchical neural network force control system. Successful experiments for various contact motions are carried out. Additionally, the proposed neural network force controller together with the master/slave control method are used in dual-industrial robot systems. Successful experiments are carried out for the dual-robot system handling an object.     

Hybrid Controller for Adaptive Link Control of Industrial Robots

This paper presents a new adaptation mechanism for a cascaded positioncontroller. The cascaded position controller consists of P.I.D. controllersthe parameters of which are changed by a fuzzy logic adaptation mechanism.The proposed fuzzy logic adaptation mechanism is tested using thesix-degree-of-freedom-robot RV 15, manufactured by Reis Robotics. Using thefuzzy logic adaptation mechanism, the cartesian position error of the toolcenter point can be significantly reduced by 50 %. Anotherenhancement of the dynamic behaviour, which can be achieved by the fuzzylogic adaptation mechanism, is to lessen the influence of different loads onthe cartesian position error.     

基于自适应动态规划的移动机器人视觉伺服跟踪控制

针对移动机器人视觉伺服跟踪控制问题, 提出一种基于自适应动态规划(Adaptive dynamic programming, ADP) 的控制方法. 通过移动机器人上的相机拍摄共面特征点的当前图像、期望图像以及参考图像, 利用单应性技术得到移动机器人当前的位姿信息与期望的位姿信息(即平移量与旋转角度), 从而通过当前与期望的平移旋转之间差值得到系统的开环误差模型. 进而, 针对此系统设计最优控制器, 同时做合适的控制输入变换. 在此基础上设计一个基于ADP的视觉伺服控制方法以保证移动机器人完成轨迹跟踪任务. 为求出最优控制输入, 采用一个评价神经网络近似值函数, 通过不断学习逼近哈密顿−雅可比−贝尔曼(Hamilton-Jacobi-Bellman, HJB)方程的解. 与以往不同的是, 由于系统存在时变项, 导致HJB方程也含有时变项, 因此需要设计具有时变权值结构的神经网络近似值函数. 最终证明在所设计的控制方法作用下, 闭环系统是一致最终有界的.     

航空发动机转子弹性支承动应力测试技术

对带弹性支承航空发动机转子的一种振动测试技术进行了研究,阐述了利用电阻应变电测法通过在转子鼠笼式弹性支承的弹条根部粘贴应变计进行动应力测试,从而获取转子振动信号的测试原理和测试方法.通过弹性支承动应力测试技术在转子动力特性试验和转子故障诊断中的应用,论证了该测试技术是转子振动测试的一种有效方式,得出了弹性支承动应力测试技术不仅能作为航空发动机带弹性支承转子动特性的常规测试手段,亦能为转子系统故障诊断提供故障识别依据.     

一种混合结构的移动机器人导航控制策略

研究了未知环境下移动机器人实时的导航控制问题.采用分布式系统将反射式行为、反应式行为与慎思规划相结合,设计了移动机器人导航控制策略.根据激光雷达传感器信息设计了基于栅格的实时避障算法和解锁策略.通过慎思规划解决了复杂环境下的局部势能陷阱问题.通过自行研制的移动机器人IMR01的实验验证了导航策略的有效性.     

Hybrid Dynamic Control Algorithm for Humanoid Robots Based on Reinforcement Learning

In this paper, hybrid integrated dynamic control algorithm for humanoid locomotion mechanism is presented. The proposed structure of controller involves two feedback loops: model-based dynamic controller including impart-force controller and reinforcement learning feedback controller around zero-moment point. The proposed new reinforcement learning algorithm is based on modified version of actor-critic architecture for dynamic reactive compensation. Simulation experiments were carried out in order to validate the proposed control approach.The obtained simulation results served as the basis for a critical evaluation of the controller performance.     

基于混合逻辑动态的列车运行调度模型

通过对列车运行调度问题的分析,指出列车运行过程中存在正常事件、客观事件和主观事件三种类型事件,调度的本质是主观事件通过改变列车的运行速度来克服客观事件对列车造成的影响,是典型的混杂系统.在考虑车站股道约束和区间容量两个约束条件的基础上,采用混合逻辑动态理论建立了列车运行调度模型,仿真结果表明了模型的有效性.     

网格环境下的一种动态跨域访问控制策略

针对网格环境下传统的基于角色的访问控制方式中资源共享的可扩放性和欺骗问题,提出了一种动态的访问控制方式．这种新型的访问控制方式可以根据用户的行为动态调整他的角色,在用户的权限与他的行为之间建立了联系．将该访问控制方式与信任模型结合,引入转换因子和动态角色的概念,应用到虚拟组织中,形成了基于动态角色的跨域访问控制系统．仿真结果显示,该系统能有效地实现访问控制,遏制欺骗,并具有良好的可扩放性．     

一种改进的未知动态环境下机器人混合路径规划方法

动态未知环境下的机器人路径规划是机器人导航领域的重要课题之一,采用传统的方法求解并不理想。针对这个问题,提出一种改进的机器人混合路径规划方法。首先利用改进的文化基因算法规划出较优的全局路径,指引机器人沿着全局路径行走,然后根据传感器探测到的局部环境信息,利用Morphin算法进行局部路径实时规划,使机器人有效地躲避动态障碍物。仿真实验表明,该算法在未知动态路径规划中具有良好的效果。