空间翻滚目标捕获的双滑模面控制律与地面微重力试验

本文研究了空间翻滚目标捕获任务中的相对姿轨耦合控制问题.为了提高系统在有界干扰、测量误差、控制受限、参数不确定等因素影响下的控制性能,设计了双滑模面姿轨耦合控制律,并证明了该控制律作用下闭环系统的稳定性.通过数学仿真与传统单滑模面控制律进行了对比分析,结果表明双滑模面控制律的能够显著减小稳态偏差和噪声.进一步,构建了地面微重力半物理试验系统,设计了轨道面内对翻滚目标逼近与跟踪的任务场景,通过半物理试验结果验证了双滑模面控制律在姿轨控全系统实时闭环、微重力动力学条件下的有效性.     

基于位置的机械臂视觉伺服预测控制

基于位置的机械臂视觉伺服控制需要解决位姿估计和目标跟踪控制问题.为了克服机械臂运动过程中的运动空间约束,提出了基于滚动时域估计(MHE)的机械臂位姿估计方法.在位姿估计的基础上,利用对偶梯度上升方法以及拉格朗日乘子处理具有控制输入约束的优化问题,并给出了基于迭代线性二次调节(iLQR)的视觉伺服预测控制器设计方法.进一步,采用极点配置方法设计了扩张状态观测器(ESO)用于解决估计误差和线性化误差引起的扰动问题.进而,给出了保证闭环系统稳定的充分条件.最后,通过仿真对比验证了本文所提算法的有效性和优越性.     

接近非合作目标的部分状态反馈姿轨联合控制

飞行器在轨精度跟踪优化问题,根据在轨服务任务需求,针对非合作翻滚目标航天器的自主接近跟踪问题,首先从采用视线坐标系表示的轨道动力学方程和修正罗德里格斯参数表示的姿态动力学方程出发,建立了航天器六自由度类拉格朗日动力学方程;然后仅利用相对位置和相对姿态反馈信息并针对航天器惯性参数不确定性,采用自适应非线性输出反馈控制和神经网络逼近控制方法设计了姿轨联合控制器,并通过Lyapunov直接法证明了该闭环系统的全局渐进稳定性;最后通过仿真验证了采用的方法能够实现对非合作目标的精确跟踪.     

基于图像的双臂模糊自适应轨迹跟踪控制

在固定相机的监视下,随机位姿的目标物体在双臂系统的控制下执行轨迹跟踪控制任务时,既要考虑目标随机位姿引起的运动学和动力学不确定性问题,还要考虑运动学和动力学的协同问题.针对上述问题,分别采用自适应方法估计目标质心和特征点的位置信息,利用模糊逻辑系统逼近系统的动力学模型,使用分散控制策略处理双臂的协同问题,最后基于位置/力混合控制方法设计基于图像的双臂模糊自适应轨迹跟踪控制器,并采用李亚普诺夫方法证明系统的稳定性.仿真实验验证了所设计控制器的有效性.     

一种基于混合视觉伺服的切换控制方法

为解决目标远离摄像机视野问题,本文提出了一种基于混合视觉伺服的切换控制方法,根据目标在图像平面的位置,通过在两种具有不同特性的控制策略之间进行切换完成视觉伺服任务.采用的混合视觉伺服方法实现了平动和转动自由度的解耦,当目标位于图像平面中心区域时,采用控制策略使转动自由度误差指数级减小;当目标位于边界区域时,切换到另一种控制策略,使目标重新回到中心区域,通过切换控制最终完成伺服任务.仿真实验验证了提出的基于混合视觉伺服切换控制方法的有效性.     

自主空中加油多摄像机近距相对导航与控制

针对伸缩套管方式下自主空中加油(AAR)对接与位置保持过程,提出了一个基于多摄像机系统(MCS)的相对导航与控制方案.该方案中的位姿估计算法通过结合3D-3D位姿估计技术和N点透视技术,能够充分利用多摄像机系统的宽视野和冗余测量信息.使用卡尔曼滤波算法对视觉估计数据进行滤波,并与速度测量数据进行融合,以提高视觉导航算法的精度和鲁棒性.为抑制外部风扰动,设计了一个基于动态对策理论的最优相对轨迹跟踪控制律.仿真结果表明提出的方案能够满足空中加油要求.     

架空输电线路巡线机器人越障视觉伺服控制

为解决巡线机器人越障问题,设计了基于图像的越障视觉伺服控制方案．采用傅里叶描述子构造了具有平移、旋转、尺度缩放及起始点不变性的轮廓形状特征向量,实现了驱动轮的识别;进而抽取图像特征和估计驱动轮—相线在图像空间中的相对位姿,并设计了带有死区的比例控制律来实现驱动轮—相线“对中”视觉伺服控制．模拟线路实验结果表明,该方案能可靠地完成巡线机器人驱动轮—相线“对中”控制任务．     

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.     

一种空间非合作目标相对位姿紧耦合估计方法

航天活动中的许多任务如对目标的绕飞观测和逼近停靠等测控任务,其中的关键技术之一是相对位姿估计,而对非合作目标的相对位姿估计更是其中的重点与难点。针对该难点,提出了一种融合单目相机和激光测距仪的空间非合作目标相对位姿紧耦合估计方法。采用单目相机获取目标序列图像,在初始化时利用激光测距仪解决单目相机尺度模糊性问题,构建真实尺度下的世界坐标系,在后续对非合作目标进行连续位姿估计时,使用紧耦合的形式融合相机与激光测距仪数据来优化估计位姿,并且解决估计漂移问题。最后使用Blender软件生成空间非合作目标序列图像,仿真验证了本文算法能稳健地得到较高精度的空间非合作目标的相对位姿,且拥有较好的实时性。     

基于神经网络的机器人视觉伺服控制

视觉伺服可以应用于机器人初始定位自动导引、自动避障、轨线跟踪和运动目标跟踪等控制系统中。传统的视觉伺服系统在运行时包括工作空间定位和动力学逆运算两个过程,需要实时计算视觉雅可比矩阵和机器人逆雅可比矩阵,计算量大,系统结构复杂。本文分析了基于图像的机器人视觉伺服的基本原理,使用BP神经网络来确定达到指定位姿所需要的关节角度,将视觉信息直接融入伺服过程,在保证伺服精度的情况下大大简化了控制算法。文中针对Puma560工业机器人的模型进行了仿真实验,结果验证了该方法的有效性。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.