智轨电车多源环境感知系统

智轨电车的多源环境感知系统是车载平台与运行环境的交互纽带,其包括基于激光雷达的障碍物感知子系统、基于毫米波雷达的前侧向障碍物感知子系统以及基于多摄像头的360度环视子系统。基于激光雷达的障碍物感知子系统采用地面分割算法、点云聚类算法和数据关联算法,实现了对运行前方障碍物的检测和跟踪;基于毫米波雷达的前侧向障碍物感知子系统采用目标检测算法和跟踪算法,实现侧向以及前向障碍物探测;基于分布式鱼眼摄像头的360度环视子系统运用图像拼接算法,实现智轨电车周围障碍物感知和预警。实车试验结果表明,该环境感知系统可有效地提高智轨电车的运行安全系数,为车辆智能驾驶提供了全面的环境信息。     

基于激光点云的道路可通行区域检测方法

以车载激光雷达获取的点云数据为研究对象,针对无人车道路环境感知的关键技术展开研究。为解决无人驾驶中道路可通行区域检测存在的地面不平整、缓坡、障碍物单一等问题,提出基于激光点云数据的道路可通行区域检测方法。通过基于分段校准的RANSAC算法进行地面分割,解决地面不平整导致的欠分割问题。使用多特征复合判据,利用基于体素化的DBSCAN聚类算法和基于结构特征的障碍物识别方法完成障碍物的分割与识别。结合道路结构以及数据高程突变特征,提取道路边界候选点并拟合得到完整的道路边界线。将道路区域栅格化,根据道路边界悬空障碍物判断并更新可通行区域,实现可通行区域的准确检测。实验结果表明,该方法在复杂道路场景中的边界检测准确率高于95%,可有效检测出障碍物及道路的可通行区域,具有良好的实时性与鲁棒性。     

基于改进光流法的旋转运动背景下对地运动目标实时检测

针对战机对地侦查视频图像中地面旋转运动背景下运动目标检测高虚警、低实时性的问题,提出了一种基于改进光流法的旋转运动背景下对地运动目标实时检测算法。首先提取图像的特征点,在特征点处计算光流运动矢量,并通过光流矢量场估算背景运动矢量。根据战机飞行高度自适应计算目标像素尺寸,网格化分块待检测图像;然后将各个特征点光流矢量与背景运动矢量相比较,获得备选目标特征点。最后统计分块备选目标特征点密度,判断目标位置区域。对2组实验视频中央360像素×432像素区域进行目标检测实验,结果表明该算法能够准确地检测出地面运动目标,虚警率低。平均每帧检测耗时分别为29.460 ms和31.505 ms,满足战机对地运动目标检测的实时性。     

基于单目视觉的障碍物检测方法研究

为了解决车辆的碰撞问题,提出了一种基于单目视觉的车道标识线二维重建及障碍物检测与跟踪的方法.主要采用最大类间方差法对初始图像进行分割,给出一种新的车道标识线特征点搜索策略,用统计模型的方法获取车道线参数.利用障碍物(前方车辆)在道路中留下的阴影,检测车辆边缘并确认车辆存在,运用卡尔曼滤波方法跟踪车辆具体位置.所设计的方法能够准确地检测跟踪车道线及前方障碍物.实验结果表明:方法满足车辆安全行驶的前提需要,具有较高的准确性和实时性.     

半结构化环境稀疏点云可通行区域检测方法

传统的激光雷达可通行区域检测算法实时性好,但算法通常对点云数据的高度特征依赖较强,半结构化环境中斜坡等区域高度特征不稳定,易降低算法的性能。基于半结构化环境下三维稀疏点云数据,提出了一种基于直线特征的可通行区域实时检测算法,预处理原始点云数据,并从中速提取直线特征;对直线聚类和筛选,从而提取有效的直线特征;使用直线特征检测结构化障碍物和非结构化障碍物;标记出可通行区域,并构建环境地图。实验结果表明,在校园半结构化环境中,该算法可以较稳定地检测可通行区域,在检测路缘石等高度较低的障碍物时表现出良好的性能,并且适应斜坡、颠簸、负障碍等地面。     

地铁站场景下的可行驶区域检测

在室内环境下的机器人视觉导航任务中,可行驶区域检测是不可或缺的一部分,这是保证自动驾驶任务实现的基础.目前较多的解决方法是对数据集中出现过的障碍物进行识别来检测可行驶区域,缺乏灵活性,因此本文提出了一种针对地铁站等室内平坦地面的可行驶区域检测方法,提高实用性.本文采用经典的MobileNetV3网络对采集到的前方图像进行分类,判断是否为地面区域.由于室内地面的地标、箭头等贴纸的影响,因此需要对非地面区域进一步判断,与常规的立体障碍物进行区分.本文利用连续帧之间的特征点匹配获得相机移动距离,并利用直线拟合计算斜率的方法达到区分立体障碍物与平面地标的目的.实验表明,本文提出的方法能较好地检测机器人前方可行驶区域,具有较高的实用价值.     

基于单目视觉的车辆检测算法研究

本文在全面总结现有的国内外前方行驶车辆的视觉检测算法的基础上,利用由于光照因素使得前方车辆在图像内形成的底部阴影这一先验知识,建立了基于车辆阴影区域检测的前方障碍物视觉检测算法。     

基于运动矢量的行车障碍自动检测算法研究

为了实现对车辆前方行人及车辆等威胁车辆正常安全行驶的危险障碍的检测,达到保证行车安全的目的,文章根据MPEG视频码流中运动矢量的特点,提出了一种新的行车障碍自动检测算法。该算法利用成熟的MPEG编解码技术对车辆前端摄像机所采集的视频图像序列进行编解码,输出MPEG码流格式的视频图像序列,通过分析解码的MPEG视频码流中运动矢量的规律,来制定判别行车前方障碍物的规则,并最终确定危险区域的范围。算法仿真结果表明,该算法具有较好的实践效果和一定的实用价值。     

基于图像处理的前方行驶车辆速度测量方法

车辆超速行驶是造成高速公路交通事故的主要原因之一,依赖于固定摄像机的传统视频测速系统测速区域十分有限.通过车载双目电荷耦合器件(CCD)摄像头获取车辆行驶过程中前方车辆的行驶状态,提出了一种测量前方行驶车辆速度的方法.利用改进Hough变换识别车道线,提取感兴趣区域,以车底阴影特征为基础完成车辆检测,通过在车载视频图像中选取适当的图像帧,获得车辆的相对位移及对应的时间间隔,获得前方车辆的行驶速度.经测试,算法能得到较高精度的速度测量结果.     

基于机器视觉的轻量级驾驶辅助系统

为了解决计算机视觉应用中数据量大、算法复杂的问题,根据道路结构特征和车辆行为特征,采用单个摄像头作为传感器,实现了一种轻量级的安全辅助驾驶系统。首先采用改进的边缘提取算法和车道线检测算法对摄像机内外参数进行离线标定;接着根据标定结果在二维平面图像上采用标识出实际空间距离的多窗口划分方法,并按不同的车间距将不同窗口划分为不同安全系数的区域,以赋予道路视觉检测的几何先验知识;当区域中出现障碍物时发出相应警示信息进行安全驾驶辅助,能为智能辅助驾驶提供轻量级的视觉检测平台。以便携式计算机和固定在车内的摄像头作为实验装置,在城市道路上进行车载实验。系统在车载实验中能够快速地提取车辆两侧的车道线,并利用离线标定的结果快速生成不同安全系数的警示区域,其中车辆在车道内正常行驶时的误检率和漏检率很小,可以忽略不计。与传统的驾驶辅助系统相比,本系统计算量大大降低,检测流程得到简化,可实现轻量级的车道和车辆检测,为系统在嵌入式系统上的实现奠定基础。     

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.