软体机械臂水下自适应鲁棒视觉伺服

水下仿生软体机器人在水底环境勘测, 水下生物观测等方面具有极高的应用价值. 为进一步提升仿章鱼臂软体机器人在特殊水下环境中控制效果, 提出一种自适应鲁棒视觉伺服控制方法, 实现其在干扰无标定环境中的高精度镇定控制. 基于水底动力学模型, 设计保证动力学稳定的控制器; 针对柔性材料离线标定过程繁琐、成本高, 提出材料参数自适应估计算法; 针对水下特殊工作条件, 设计自适应鲁棒视觉伺服控制器, 实现折射效应的在线补偿, 并通过自适应未知环境干扰上界, 避免先验环境信息的求解. 所提算法在软体机器人样机中验证其镇定控制性能, 为仿生软体机器人的实际应用提供理论基础.     

Reference Trajectory-Based Visual Predictive Control

Abstract

In this paper we present an image predictive controller for an eye-in-hand-type servoing architecture, composed of a 6-d.o.f. robot and a camera mounted on the gripper. A novel architecture for integrating reference trajectory and image prediction is proposed for use in predictive control of visual servoing systems. In the proposed method, a new predictor is developed based on the relation between the camera velocity and the time variation of the visual features given by the interaction matrix. The image-based predictor generates the future trajectories of a visual feature ensemble when past and future camera velocities are known. In addition, a reference trajectory is introduced to define the way how to reach the desired features over the prediction horizon starting from the current features. The advantages of the new architecture are the reference trajectory used for the first time in the sense of the predictive control and the predictor based on a local model. Simulations reveal the efficiency of the proposed architecture to control a 6-d.o.f. robot manipulator.     

基于散焦图像特征的微装配机器人深度运动显微视觉伺服

为了描述微操作手深度运动,采用灰度方差聚焦评价算子计算机械手散焦图像特征．散焦特征曲线理论上为单峰分布,峰值点对应显微光学焦平面深度位置．实际提取的散焦特征含有大量随机噪声,利用非线性跟踪微分器抑制噪声实现对机械手散焦图像特征及其微分信号的无颤振光滑逼近．依据散焦微分信号设计粗—精两级自寻优视觉控制器,完成微操作手对装配平面深度的精确定位．微装配深度运动实验验证了本文方法的有效性,机械手深度伺服误差为75 μm．     

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.     

Nonlinear Adaptive Model Predictive Control of Constrained Systems with Offset‐Free Tracking Behavior

In this paper, a nonlinear model‐based predictive control strategy for constrained systems based on an adaptive neural network (NN) predictor is proposed. The proposed controller is robust against the model uncertainties and external bounded disturbances. Moreover, it provides offset‐free tracking behavior using the adaptive structure in the model. Based on the uncertainties bounds, the restriction of the system constraints causes robust feasibility and stability of the closed‐loop system. It is shown that the output of the NN predictor converges to the system output. Moreover, offset‐free behavior of the closed‐loop system is investigated using the Lyapunov theorem. Simulation results show the effectiveness of the proposed method as compared to the recently proposed model predictive control methods in the literature.     

基于状态观测器的约束鲁棒模型预测控制

模型不确定情况下的鲁棒问题是模型预测控制的一个根本问题。本文采用线性矩阵不等式(LMI)，研究多模型不确定性描述情况下的鲁棒模型预测控制问题。在输入输出约束条件下，最小化最坏情况下的无穷时域目标函数，获得保证系统稳定的基于状态观测器的状态反馈增益并且给出观测器增益的设计方法。实例说明算法可行且保证闭环系统渐近稳定。     

一种新的双环结构机器人无标定自抗扰视觉伺服控制方法

在研究基于自抗扰控制器的机器人无标定视觉伺服方法的基础上,提出了一种新的双环结构机器人无标定自抗扰视觉伺服控制方法．内环采用Kalman滤波算法进行图像雅可比矩阵的在线辨识,可较好地逼近真实模型;外环采用自抗扰控制器,利用非线性观测器实时估计系统相对于当前估计模型的总扰动,并在控制中加以动态补偿．针对六自由度工业机器人进行了二维运动目标的跟踪实验,实验结果表明了该方法的可行性和有效性．     

Visual Servoing Path Planning for Cameras Obeying the Unified Model

Abstract

This paper proposes a path planning visual servoing strategy for a class of cameras that includes conventional perspective cameras, fisheye cameras and catadioptric cameras as special cases. Specifically, these cameras are modeled by adopting a unified model recently proposed in the literature and the strategy consists of designing image trajectories for eye-in-hand robotic systems that allow the robot to reach a desired location while satisfying typical visual servoing constraints. To this end, the proposed strategy introduces the projection of the available image features onto a virtual plane and the computation of a feasible image trajectory through polynomial programming. Then, the computed image trajectory is tracked by using an image-based visual servoing controller. Experimental results with a fisheye camera mounted on a 6-d.o.f. robot arm are presented in order to illustrate the proposed strategy.     

未知环境下的机器人视觉/力觉混合控制

在实际的接触型作业任务中,需要在控制位置的同时控制末端执行器与环境之间的接触力.针对这一问题,通过力反馈信息对未知环境中的法线方向进行估计,并采用最小二乘方法估计图像雅可比矩阵.提出一种基于视觉/力觉的混合控制算法,给出了视觉/力觉混合控制的约束条件,对视觉采用变结构控制器,力控制采用PI控制器.实验结果表明,该策略具有较高的力控制精度和曲线跟踪能力.     

Visual Object Tracking and Servoing Control of a Nano-Scale Quadrotor: System,Algorithms, and Experiments

There are two main trends in the development of unmanned aerial vehicle(UAV)technologies:miniaturization and intellectualization,in which realizing object tracking capabilities for a nano-scale UAV is one of the most challenging problems.In this paper,we present a visual object tracking and servoing control system utilizing a tailor-made 38 g nano-scale quadrotor.A lightweight visual module is integrated to enable object tracking capabilities,and a micro positioning deck is mounted to provide accurate pose estimation.In order to be robust against object appearance variations,a novel object tracking algorithm,denoted by RMCTer,is proposed,which integrates a powerful short-term tracking module and an efficient long-term processing module.In particular,the long-term processing module can provide additional object information and modify the short-term tracking model in a timely manner.Furthermore,a positionbased visual servoing control method is proposed for the quadrotor,where an adaptive tracking controller is designed by leveraging backstepping and adaptive techniques.Stable and accurate object tracking is achieved even under disturbances.Experimental results are presented to demonstrate the high accuracy and stability of the whole tracking system.     

基于区间控制的约束预测控制及约束影响

在实际被控过程中往往存在着很多约束条件,这使得预测控制的在线优化问题表现为非线性,难以获得控制律的具体表达式,为约束预测控制的分析造成困难基于Newton控制框架,针对线性系统离散状态空间的动态模型,考虑具有输入、输出区间约束条件下,基于区间控制思想的预测控制律的解析表达式,分别得到无约束和有约束情况下状态反馈控制律的...     

单目视觉伺服研究综述

视觉伺服是机器人视觉领域的研究热点之一,具有十分广泛的应用前景.本文针对单目视觉系统,从视觉伺服的运动映射关系、误差表征、控制律设计、关键影响因素等多个层面,对视觉伺服的研究现状进行了论述,并分析了不同视觉伺服方法的特点,给出了视觉伺服在不同领域的典型应用.最后,指出了视觉伺服未来的主要发展方向.     

曲线焊缝跟踪的视觉伺服协调控制

为实现工业机器人自动跟踪曲线焊缝,提出了协调焊枪运动和视觉跟踪的视觉伺服控制方法．建立了特征点的数学模型,并在此基础上确定机器人运动的旋转轴．设计了一种双层结构的模糊视觉伺服控制器,通过动态确定控制量有效范围来保证图像特征存在于视场中．为准确确定有效范围,设计了带模型动态补偿的Kalman滤波器．曲线焊缝的自动跟踪实验验证了所提方法的有效性．     

Robust Constrained Model Predictive Control for Discrete‐Time Uncertain System in Takagi‐Sugeno's Form

In this paper, we investigate a robust constrained model predictive control synthesis approach for discrete‐time Takagi‐Sugeno's (T‐S) fuzzy system with structured uncertainty. The key idea is to determine, at each sampling time, a state feedback fuzzy predictive controller that minimizes the performance objective function in the infinite time horizon by solving a class of linear matrix inequalities (LMIs) optimization problem. To do this, the fuzzy predictive controller is designed on the basis of non‐parallel distributed compensation (non‐PDC) control law, relaxed stability conditions of the closed‐loop fuzzy system are developed by employing an extended nonquadratic Lyapunov function and introducing additional slack and collection matrices. In addition, the presented approach is capable of ensuring the robust asymptotic stability as well as the recursive feasibility of the closed‐loop fuzzy system. Simulations on a highly nonlinear continuous stirred tank reactor (CSTR) are eventually presented to demonstrate the effectiveness of the developed theoretical approach.     

基于视觉伺服反馈的不确定非完整动态移动机器人的自适应镇定

研究了带有固定在天花板上的摄像机系统的非完整动态移动机器人的镇定问题. 首先, 利用针孔摄像机模型引入了基于摄像机目标的视觉伺服运动学模型,并针对该运动学模型给出了一个运动学镇定控制器. 然后,在摄像机参数不确定的情形下设计了一个自适应滑模控制器实现了不确定动态移动机器人的镇定. 提出的控制器不仅对结构不确定性如质量变化, 而且对无结构不确定性如外部扰动都具有鲁棒性. 通过Lyapunov方法严格证明了提出的控制系统的稳定性和估计参数的有界性. 仿真结果证实了控制律的有效性.     

Alignment Motion Control for an Automated Human Ear Surgery via Vision‐Servoing

To treat a worldwide common ear disease called Otitis Media with Effusion, a robotic device allowing fast and automatic grommet tube insertion has been designed in our earlier works. However, the previous version has to be manually placed close to the tympanic membrane before the insertion procedures. For the purpose of realizing a fully automated surgical process, locating and realizing a suitable insertion path from outside the ear forms a crucial step. It is then desirable to control the working channel to be aligned to the axial direction of auditory canal from the vision channel. In this paper, a fast and robust vision‐based servomechanism is proposed to achieve the planar alignment. To detect and track the region of auditory canal through the image sequences, an image segmentation algorithm based on the phase information and combining with the hough transformation technique is proposed. With the help of Kalman filter, a new look‐and‐move servomechanism can be achieved by utilizing the visual and motion measurements simultaneously, resulting in an effective and robust servoing performance.     

Discrete‐Valued Model Predictive Control Using Sum‐of‐Absolute‐Values Optimization

In this paper, we propose a new design method of discrete‐valued model predictive control for continuous‐time linear time‐invariant systems based on sum‐of‐absolute‐values (SOAV) optimization. The finite‐horizon discrete‐valued control design is formulated as an SOAV optimal control, which is an expansion of L¹ optimal control. It is known that under the normality assumption, the SOAV optimal control exists and takes values in a fixed finite alphabet set if the initial state lies in a subset of the reachable set. In this paper, we analyze the existence and discreteness property for systems that do not necessarily satisfy the normality assumption. Then, we extend the finite‐horizon SOAV optimal control to infinite‐horizon model predictive control (MPC). We give sufficient conditions for the recursive feasibility and the stability of the MPC‐based feedback system in the presence of bounded noise. Simulation results show the effectiveness of the proposed method.     

Offline Robust Model Predictive Control for Lipschitz Non‐Linear Systems Using Polyhedral Invariant Sets

In this paper the concept of maximal admissible set (MAS) for linear systems with polytopic uncertainty is extended to non‐linear systems composed of a linear constant part followed by a non‐linear term. We characterize the maximal admissible set for the non‐linear system with unstructured uncertainty in the form of polyhedral invariant sets. A computationally efficient state‐feedback RMPC law is derived off‐line for Lipschitz non‐linear systems. The state‐feedback control law is calculated by solving a convex optimization problem within the framework of linear matrix inequalities (LMIs), which leads to guaranteeing closed‐loop robust stability. Most of the computational burdens are moved off‐line. A linear optimization problem is performed to characterize the maximal admissible set, and it is shown that an ellipsoidal invariant set is only an approximation of the true stabilizable region. This method not only remarkably extends the size of the admissible set of initial conditions but also greatly reduces the on‐line computational time. The usefulness and effectiveness of the method proposed here is verified via two simulation examples.     

A Modular Scheme for Controller Design and Performance Evaluation in 3D Visual Servoing

In this paper we present a modular scheme for designing and evaluating different control systems for position based dynamic look and move visual servoing systems. This scheme is particularly applied to a 6 DOF industrial manipulator equipped with a camera mounted on its end effector. The manipulator with its actuators and its current feedback loops can be modeled as a Cartesian device commanded through a serial line. In this case the manipulator can be considered as a decoupled system with 6 independent loops. The use of computer vision as feedback transducer strongly affects the closed loop dynamics of the overall system, so that a visual controller is required for achieving fast response and high control accuracy. Due to the long delay in generating the control signal, it is necessary to carefully select the visual controller. In this paper we present a framework that allows the study of some conventional and new techniques to design this visual controller. Besides an experimental setup has been built and used to evaluate and compare the performance of the position based dynamic look and move system with different controllers. Some criterions for selecting the best strategy for each task are established. Quite a lot of results relative to different trajectory tracking control strategies are presented, showing both simulation and real platform responses.