室外自主移动机器人AMOR的导航技术

在非结构化环境,移动机器人行驶运动规划和自主导航是非常挑战性的问题。基于实时的动态栅格地图,提出了一个快速的而又实效的轨迹规划算法,实现机器人在室外环境的无碰撞运动导航。AMOR是自主研发的室外运动移动机器人,它在2007年欧洲C-ELROB大赛中赢得了野外自主侦察比赛的冠军。它装备了SICK的激光雷达,用来获取机器人运动前方的障碍物体信息,建立实时动态的环境地图。以A*框架为基础的改造算法,能够在众多的路径中快速地找到最佳的安全行驶路径,实现可靠的自主导航。所有的测试和比赛结果表明所提方案是可行的、有效的。

基于立体视觉的室外非结构化环境障碍物检测方法研究

随着智能机器人系统的发展，机器人的在线感知能力日益受到重视。障碍物检测能力是机器人在线感知能力的一个重要组成部分。因视觉传感器具有独特优势，基于视觉的障碍物检测方法成为目前关注的重点。 室外非结构化环境因结构复杂，机器人缺乏可有效利用的先验知识描述，导致众多障碍物检测系统在该环境中不能有效工作。本文采用全局-局部策略对场景进行由粗到精的分析，弥补室外非结构化环境先验知识不足的难题，提高机器人的在线感知能力。根据该策略，本文在基于视差图的障碍物检测系统框架中，引入视差投影图模块，提出了基于视差投影图的障碍物检测系统框架。该框架在视差投影图模块中全局分析场景视差分布水平，在立体匹配模块中局部分析场景前景目标的几何轮廓信息。依据该框架，针对实际应用中遇到的各种问题，提出了工作于室外非结构化环境的障碍物检测算法。该算法具有如下特点： 1、通过分析视差投影图的地面关联线信息，获得场景的视差分布水平。该信息一方面用来动态更改匹配算法的视差搜索范围，增强算法的实时性和鲁棒性；另一方面用来移除背景地表，简化障碍物分割过程； 2、采用双域滤波抑制噪声，获得清晰的边缘特征，降低立体匹配算法在深度不连续性区域的匹配难度； 3、借助逆向重投影的思想重采样扫描图像，在立体匹配前等效地实现了立体匹配过程中动态变更视差搜索范围的操作； 4、采用基于连通成分的扩散方法替代传统的SAD局部匹配算法，获得高质量的视差图，最终改善障碍物检测的精确性。 在室外非结构化环境中，本文对该算法进行了实验验证。通过设置不同的基线长度，验证了算法在不同的感知距离内的有效性。经实验证明，本算法在一定距离范围内能够有效的检测出障碍物。

一种基于区域分割的多级环境建模方法

针对现有移动机器人路径规划中各种环境建模方法存在使用范围有限、复杂问题处理能力不足和运行效率低、缺乏灵活性等问题，结合二维半描述和知识利用原理，提出了一种可以比较圆满地解决诸如建筑物内不同楼层连接、室内室外环境交替出现等实用结构性空间问题的基于区域分割的多级环境建模方法。

越野移动机器人自动驾驶专家系统的研究

本文研究越野移动机器人驾驶专家系统等有关问题．首先介绍了系统的硬件支持环境，然后阐述了自动驾驶专家系统的总体结构，有关知识库的内容以及使用知识的各功能模块的作用与运行机理．该系统已部分得以应用，能够完全代替驾驶员完成各种驾驶操作，并能进行自主导航、运动规划、自动绕障、动态跟踪目标、原路返回以及示教再现等复杂任务。

非饱和膨胀土力学特性及其工程处置研究

The unsaturated expansive soil is a hotspot and difficulty in soil mechanics inland and outland. The expansive soil in our China is one of the widest in distributing and greatest in area, and the disaster of expansive soil happens continually as a result. The soil mechanics test, monitor, numerical simulation and engineering practice are used to research swell and shrinkage characteristic, edge strength characteristic and unsaturated strength characteristic of Mengzi expansive soil. The seep and stability of the slope for expansive soil associated with fissure are analyzed and two kinds of new technique are put forward to be used in expansive soil area, based on disaster mechnics proposed of the slope.The technique of reinforcement in road embankment is optimized also. Associated with engineering geology research of Mengzi expansive soil, mineral composition, chemical composition, specific area and cation content, dissolubility salt and agglutinate, microcosmic fabric characteristic, cause of formation and atmosphere effect depth are analyzed to explain the intrinsic cause and essence of swell and shrinkage for expansive soil. The rule between swell-shrinkage and initial state, namely initial water content, initial dry density and initial pressure, can be used to construction control. Does Response model is fit to simulate the rule, based on ternary regression analysis. It has great meaning to expansive soil engineering in area with salt or alkali. The mechanics under CD, CU and GCU of expansive soil is researched by edge surface theory to explain the remarkable effect of consolidation pressure, initial dry density, initial water content, cut velocity, drainage and reinforcement to the edge strength characteristic. The infirm hardening stress strain curves can be fitted with hyperbola model and the infirm softening curves can be fitted with exponential model. The normalization theory can be used to reveal the intrinsic unity of the otherness which is brought by different methods to the shear strength of the same kinds of samples. The unsaturated strain softening characteristic and strength envelope of remolding samples are researched by triaxial shear test based on suction controlled, the result of which is simulated by exponential function. The strength parameters of the unsaturated samples are obtained to be used in the unsaturated seep associated with rainfall. The elasticity and plasticity characters of expansive soil are researched to attain the model parameters by using modified G-A model. The humidification destroy characteristic of expansive soil is discussed to research the disaster mechanism of the slope with the back pressure increasing and suction decreasing under bias pressure consolidation. The indoor and outdoor SWCCs are measured to research the effect factors and the rule between different stress and filling environment. The moisture absorption curves can express the relationship between suction and water content in locale. The SWCCs of Mengzi expansive soil are measured by GDS stress path trixial system. The unsaturated infiltration function is gained to research seep and stability of the slope of expansive soil. The rainfall infiltration and ability of slope considering multifarious factors are studied by analyzing fissure cause of Mengzi expansive soil. The mechanism of the slope disaster is brought forward by the double controlling effect between suction and fissure. Two new kinds of technique are put forward to resolve disaster of expansive soil and the technique of reinforcement on embankment is optimized, which gives a useful help to solving engineering trouble.

基于GIS的高速公路养护管理信息系统的设计与开发

China is experiencing a rapid development of highway ever since 1990s. By the end of 2004, the total length of the highway summed up to 33 thousand kilometers, ranking 2n in the world. After the open of highway, the accumulation of time and traffic causes the decrease of its capability. To ensure its good quality, security and operation functions, we should take some reasonable measures to maintain it periodically. At present, a big problem is that the traditional maintain measures can no longer meet the increasing requirements. Due to the characters of highway, the relationship of various maintenance data and geographic positions is even closer than any others. If we wan to improve the quality and efficiency of the maintenance work, particularly when there is need for decision-making, a great number of data that is related to geographic positions are absolutely necessary. Evidently, Geographical Information System (GIS) has incomparably advantages in dealing with these spatial information. As a result, a management system for highway maintenance work based on GIS became inevitable for the development of the maintenance of highway. The purpose of this paper is to establish a management system for highway maintenance work base on Geographical Information System (GIS), Global Positioning System (GPS) and spatial database, to manage all kinds of problems encountered in the work, and to provide support on information and methods. My study mainly includes: (1) Analysis on the current status of the maintenance and management work; overview on the history of domestic and international highway maintenance management systems; identifying the necessity and importance for establishing a management system for highway maintenance work based on GIS. (2) Based on the requirement analysis, I proposed a general design for this management system, and discussed the objective, design principles, framework, systematical structure and function design. (3) Outdoor data collection is not only a prime way to understand the current situation of the road, but also an important method for data update after the system is put into use. This paper also intends to establish a set of plan to collect data efficiently and precisely which is based on GIS and GPS technologies. (4) The maintenance management database is a supporting platform for various maintenance decision-makings. Such decisions need the support of a great amount of data, which would cause other problems, such as the diversity of the data source, difference of data formats. This paper also discussed how to deal with these problems and establish such a database. (5) To propose an approach to assess the condition of pavement, based on GIS and related maintenance models. Among all the maintenance models, the two for assessing and forecasting pavement condition are the most important and mature. This paper also analyzed these two models and introduced them in terms of the integration of models. (6) This paper took the Guangshen Highway for example, explaining how to realize a GIS for management of highway maintenance work.

How do Humans Determine Reflectance Properties under Unknown Illumination?

Under normal viewing conditions, humans find it easy to distinguish between objects made out of different materials such as plastic, metal, or paper. Untextured materials such as these have different surface reflectance properties, including lightness and gloss. With single isolated images and unknown illumination conditions, the task of estimating surface reflectance is highly underconstrained, because many combinations of reflection and illumination are consistent with a given image. In order to work out how humans estimate surface reflectance properties, we asked subjects to match the appearance of isolated spheres taken out of their original contexts. We found that subjects were able to perform the task accurately and reliably without contextual information to specify the illumination. The spheres were rendered under a variety of artificial illuminations, such as a single point light source, and a number of photographically-captured real-world illuminations from both indoor and outdoor scenes. Subjects performed more accurately for stimuli viewed under real-world patterns of illumination than under artificial illuminations, suggesting that subjects use stored assumptions about the regularities of real-world illuminations to solve the ill-posed problem.

Monitoring Activities from Multiple Video Streams: Establishing a Common Coordinate Frame

Passive monitoring of large sites typically requires coordination between multiple cameras, which in turn requires methods for automatically relating events between distributed cameras. This paper tackles the problem of self-calibration of multiple cameras which are very far apart, using feature correspondences to determine the camera geometry. The key problem is finding such correspondences. Since the camera geometry and photometric characteristics vary considerably between images, one cannot use brightness and/or proximity constraints. Instead we apply planar geometric constraints to moving objects in the scene in order to align the scene"s ground plane across multiple views. We do not assume synchronized cameras, and we show that enforcing geometric constraints enables us to align the tracking data in time. Once we have recovered the homography which aligns the planar structure in the scene, we can compute from the homography matrix the 3D position of the plane and the relative camera positions. This in turn enables us to recover a homography matrix which maps the images to an overhead view. We demonstrate this technique in two settings: a controlled lab setting where we test the effects of errors in internal camera calibration, and an uncontrolled, outdoor setting in which the full procedure is applied to external camera calibration and ground plane recovery. In spite of noise in the internal camera parameters and image data, the system successfully recovers both planar structure and relative camera positions in both settings.

Herod Wielki i „nowa” Jerozolima

Summary: Herod the Great (73-4 B.C.E.) was a Roman client king of the small Jewish state Judaea in the last three decades before the common era. An essential aspect of Herod's reign was his role as a builder. Remarkably innovative, he created an astonishing record of architectural achievement, not only in Judaea but also throughout Greece and the Roman East. Herod’s own inclinations caused him to engage in a building program that paralleled that of his patron, Augustus. The most famous and ambitious project was the expansion of Jerusalem and rebuilding of the Second Temple. Josephus Flavius, a 1st-century Jewish historian, in his descriptions of the visual structure of Jerusalem delivers the picture of the Jewish society in the latter Second Temple Judaea, who were fundamentally antagonistic toward images. For Josephus, Roman iconography, such as Herod’s eagle from the Jerusalem Temple, represents not only political domination but also an unambiguous religious abomination. Visual conservatism in the public realm finds important verification in the excavated remains of Jerusalem’s Temple Mount and the Herodian Quarter (Upper City). Geometric patterns and forms predominate on the floor mosaic, stone furniture, in architectural detail and funerary remains. No human imagery is present in the Jewish context. However, Herodian structures in Jerusalem reflect the architectural and visual vocabulary of their time which contains popular elements of Roman domination in the ancient world.

Qualidade do ar interior e os requisitos de ar novo numa unidade hospitalar

Dissertação apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do Grau de Mestre em Engenharia e Gestão Ambiental, ramo de Sistemas Industriais

PROPAGATION OF SONIC BOOMS THROUGH A REAL, STRATIFIED ATMOSPHERE

Sonic boom propagation in a quiet) stratified) lossy atmosphere is the subject of this dissertation. Two questions are considered in detail: (1) Does waveform freezing occur? (2) Are sonic booms shocks in steady state? Both assumptions have been invoked in the past to predict sonic boom waveforms at the ground. A very general form of the Burgers equation is derived and used as the model for the problem. The derivation begins with the basic conservation equations. The effects of nonlinearity) attenuation and dispersion due to multiple relaxations) viscosity) and heat conduction) geometrical spreading) and stratification of the medium are included. When the absorption and dispersion terms are neglected) an analytical solution is available. The analytical solution is used to answer the first question. Geometrical spreading and stratification of the medium are found to slow down the nonlinear distortion of finite-amplitude waves. In certain cases the distortion reaches an absolute limit) a phenomenon called waveform freezing. Judging by the maturity of the distortion mechanism, sonic booms generated by aircraft at 18 km altitude are not frozen when they reach the ground. On the other hand, judging by the approach of the waveform to its asymptotic shape, N waves generated by aircraft at 18 km altitude are frozen when they reach the ground. To answer the second question we solve the full Burgers equation and for this purpose develop a new computer code, THOR. The code is based on an algorithm by Lee and Hamilton (J. Acoust. Soc. Am. 97, 906-917, 1995) and has the novel feature that all its calculations are done in the time domain, including absorption and dispersion. Results from the code compare very well with analytical solutions. In a NASA exercise to compare sonic boom computer programs, THOR gave results that agree well with those of other participants and ran faster. We show that sonic booms are not steady state waves because they travel through a varying medium, suffer spreading, and fail to approximate step shocks closely enough. Although developed to predict sonic boom propagation, THOR can solve other problems for which the extended Burgers equation is a good propagation model.

Automated Placement of Cameras in a Floorplan to Satisfy Task-Specific Constraints

In many multi-camera vision systems the effect of camera locations on the task-specific quality of service is ignored. Researchers in Computational Geometry have proposed elegant solutions for some sensor location problem classes. Unfortunately, these solutions utilize unrealistic assumptions about the cameras' capabilities that make these algorithms unsuitable for many real-world computer vision applications: unlimited field of view, infinite depth of field, and/or infinite servo precision and speed. In this paper, the general camera placement problem is first defined with assumptions that are more consistent with the capabilities of real-world cameras. The region to be observed by cameras may be volumetric, static or dynamic, and may include holes that are caused, for instance, by columns or furniture in a room that can occlude potential camera views. A subclass of this general problem can be formulated in terms of planar regions that are typical of building floorplans. Given a floorplan to be observed, the problem is then to efficiently compute a camera layout such that certain task-specific constraints are met. A solution to this problem is obtained via binary optimization over a discrete problem space. In preliminary experiments the performance of the resulting system is demonstrated with different real floorplans.

Automated Camera Layout to Satisfy Task-Specific and Floorplan-Specific Coverage Requirements

In many multi-camera vision systems the effect of camera locations on the task-specific quality of service is ignored. Researchers in Computational Geometry have proposed elegant solutions for some sensor location problem classes. Unfortunately, these solutions utilize unrealistic assumptions about the cameras' capabilities that make these algorithms unsuitable for many real-world computer vision applications: unlimited field of view, infinite depth of field, and/or infinite servo precision and speed. In this paper, the general camera placement problem is first defined with assumptions that are more consistent with the capabilities of real-world cameras. The region to be observed by cameras may be volumetric, static or dynamic, and may include holes that are caused, for instance, by columns or furniture in a room that can occlude potential camera views. A subclass of this general problem can be formulated in terms of planar regions that are typical of building floorplans. Given a floorplan to be observed, the problem is then to efficiently compute a camera layout such that certain task-specific constraints are met. A solution to this problem is obtained via binary optimization over a discrete problem space. In experiments the performance of the resulting system is demonstrated with different real floorplans.

3D Trajectory Recovery for Tracking Multiple Objects and Trajectory Guided Recognition of Actions

A mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture of Gaussian classifier. The system was tested in recognizing various dynamic human outdoor activities; e.g., running, walking, roller blading, and cycling. Experiments with synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.

Trajectory Guided Tracking and Recognition of Actions

A combined 2D, 3D approach is presented that allows for robust tracking of moving people and recognition of actions. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. Low-level features are often insufficient for detection, segmentation, and tracking of non-rigid moving objects. Therefore, an improved mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object that are then used as input to action recognition modules. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture-of-Gaussians classifier. The system was tested in recognizing various dynamic human outdoor activities: running, walking, roller blading, and cycling. Experiments with real and synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.