Mobility and Learning: Engaging People in Design of their Everyday Environments Arne Svensk1*, Bodil J?nsson1, Lone Malmborg2^ 1 Design Sciences, Lund University, Sweden. 2 Arts and Communication, Malm? University, Sweden. *Address for correspondence: Arne Svensk, Certec, LTH, P.O. Box 118, SE-22100, Lund, Sweden. Tel.: +46 46 222 46 94; Fax: +46 46 222 44 31; E-mail: arne.svensk@certec.lth.se . ^Lone Malmborg, Arts & Communication, Malm? University, Beijerskajen 8, SE-205 06 Malm?, Sweden. E-mail: lone.malmborg@k3.mah.se Abstract “Mobility and Learning Environments” is a three-year project in which we have collaborated with people with cognitive difficulties at a day activity centre in Lund, Sweden and college students at Arts and Communication (K3), Malm? University, Sweden. The project is based on the participants themselves being engaged in the design of their everyday environments. For people with considerable difficulties in communicating, a new means of expressing their dreams was required. This paper describes how we used cultural probes to inspire, inform and surprise those of us who took part in the design process. Keywords: cultural probes, inspiration, cognitive abilities, engaging users Introduction In recent years we have seen a change in attitude from considering people with disabilities and older people as special cases requiring special design solutions, to involving them in their everyday life routines through a more inclusive
Variable Pallet Pick-Up for Automatic Guided Vehicles in Industrial Environments Daniel Lecking, Oliver Wulf, Bernardo Wagner Institute for Systems Engineering, Real Time Systems Group University of Hannover Hannover, Germany {lecking,wulf,wagner}@rts.uni-hannover.de Abstract - This paper presents two laser scanner based approaches to locate and pick-up pallets with the aim of automating forklift trucks. In contrast to camera based systems our approaches are independent of luminance conditions which can be highly variable in industrial environments. Whereas one approach uses pallets modified with adhesive reflectors which enables very flexible handling of pallets, the second approach detects pallets based on geometric characteristics without any modifications to the environment. Experimental results are also reported including a run of an autonomous fork-lift truck presented at the logistics fair CeMAT 2005 in Hannover. I. I NTRODUCTION Automatic guided vehicle systems (AGVS) to engage pallets typically require that the location of the pallets be known a priori and that the pallets are accurate positioned. To perform pallet handling also when the pallet position is not precisely known in advance, e.g. when the loads are handled and placed by a human driver, only a few solutions have been presented. Most of these approaches are based on visual features extracted by image camera data. In reference [1] an image segmentation method based on color and the geometric characteristics of the pallet is proposed. For this approach a camera calibration algorithm and a good illumination system is required. A system which does not require to maintain a strict camera calibration is presented in [2]. Therefore fiducials are used, which are artificial visual features placed on the pallets. A model-based vision algorithm without any artificial illumination support has been implemented in [3], the algorithm based on the identification of the central cavities of the pallets. In [4] a combination of range camera and a video camera are used to detect pallets. In our approach we use laser range scanner to localize and pick-up pallets in variable positions and at variable heights. In contrast to camera based systems our approach does not suffer with distortion and illumination problems or object scaling problems which can result in misdetection or false detection of important features [5]. The only other system based on a laser scanner that the authors are aware of is the so called “Pallet Finder” which is being developed at the EADS SPACE Transportation GmbH [6]. Unfortunately, there is no public information available that describes the methods employed for pallet recognition. This paper presents two approaches to localize and pick-up pallets in an industrial environment. The first approach uses reflectors to calculate the position and orientation of a pallet whereas the second approach uses only geometrical characteristics. The two approaches are described in section II. Section III gives a description of the trajectory generation as well as the tracking and docking system to fork the pallet. Experimental results are presented in section IV e.g. a working forklift truck as shown in Fig.1. Fig. 1. Autonomous fork-lift truck II. P ALLET R ECOGNITION The sensors that have been employed for the experiments is a SICK 2D laser scanner S3000 to recognize pallets at ground plane and in addition a SICK 2D laser scanner LMS200 to recognize pallets at variable heights additional. The main advantage of using the S3000 laser scanner based on the additive use to fulfill requirements defined in the standards for autonomous mobile systems in industrial automation and services [7]. The following two approaches are described to identify and locate a standard Euro pallet of size 1200x800mm.
Protection against cold environments Personnel at mines or other facilities that are located in cold climates or at high altitudes may be subjected to low temperatures for at least part of the year. Even in the more temperate zones, workers in main intake airways may suffer from cold discomfort during winter seasons. It is, therefore, appropriate that we include the effects of cold environments on the human body. Heat loss from the clothed body in cold surroundings is mainly by convection with lesser amounts by radiation and respiration. The most important climatic parameters in these circumstances are ambient (dry bulb) temperature and air velocity. These may be combined into an equivalent wind chill temperature. As heat loss occurs, the initial behavioural response is to don additional clothing and to increase metabolic heat production by conscious muscular activity. Involuntary physiological reaction is initiated by reductions in either the body core temperature or mean skin temperature and consists of an increase in muscular tension. In skin tissues, this causes the familiar "gooseflesh" and progresses into shivering within localized muscle groups. The generation of metabolic heat may be raised by up to 120 W/m2. With further cooling, the degree of shivering increases to encompass the whole body, producing some 300 W/m2 of metabolic heat and effectively incapacitating the person. If the core temperature falls below 35°C, the body thermoregulation system will be affected. Core temperatures of less than 28°C can prove fatal, although successful recovery of individuals has been achieved from core temperatures of less than 20°C. The subjective feeling of comfort depends upon the mean skin temperature and also the surface temperature of the extremities. However, the increased blood flow caused by a medium or hard work rate can render these reduced values of mean skin temperature acceptable. The large surface to volume ratio of fingers, toes, and ears maximizes heat loss while the influence of vasoconstriction is particularly effective in reducing blood flow to those areas. The latter is a natural reaction to protect, preferentially, the vital organs within the body core. However, it can give rise to severe discomfort and tissue (frost) damage to the extremities. The first line of defence against any potentially adverse environment in the subsurface is the initial design and subsequent control of the ventilation and air conditioning systems. Methods of heating
ASTM美国材料标准中文版 ASTM A488/A488-2007 钢铸件焊接工艺和人员资格评定的标准实施规程（Standard Practice for Steel Castings, Welding, Qualifications of Procedures and Personnel） ASTM A802/A 802M-1995(R2006重新审批) 视觉检测铸钢表面验收标准规程（STANDARD PRACTICE FOR STEEL CASTINGS, SURFACE ACCEPTANCE STANDARDS, VISUAL EXAMINATION） ASTM B108-2006 铝合金永久型铸件标准规（STANDARD SPECIFICATION FOR ALUMINUM-ALLOY PERMANENT MOLD CASTINGS） ASTM B179-2006 铸造用铝合金原锭及熔融锭在各铸造过程的标准技术规（STANDARD SPECIFICATION FOR ALUMINUM ALLOYS IN INGOT AND MOLTEN FORMS FOR CASTINGS FROM ALL CASTING PROCESSES） ASTM B26/B26M-2005 铝合金砂铸件标准规（STANDARD SPECIFICATION FOR ALUMINUM-ALLOY SAND CASTINGS） ASTM D256-2006 测定塑料抗悬臂梁摆锤冲击性的标准试验方法（STANDARD TEST METHODS FOR DETERMINING THE IZOD PENDULUM IMPACT RESISTANCE OF PLASTICS） ASTM D2794-1993(R2004) 有机涂层抗快速形变(冲击)作用的标准试验方法（STANDARD TEST METHOD FOR RESISTANCE OF ORGANIC COATINGS TO THE EFFECTS OF RAPID DEFORMATION (IMPACT) ） ASTM D3359-2008 胶带试验用测定粘合性的标准试验方法（STANDARD TEST METHODS FOR MEASURING ADHESION BY TAPE TEST） ASTM D3363-2005 铅笔试验法测定涂膜硬度的标准试验方法（STANDARD TEST METHOD FOR FILM HARDNESS BY PENCIL TEST） ASTM D4060-2007 用泰伯尔磨蚀机测定有机涂层耐磨性的标准试验方法（STANDARD TEST METHOD FOR ABRASION RESISTANCE OF ORGANIC COATINGS BY THE TABER ABRASER） ASTM D4674-2002A 暴露在室办公室环境下的塑料颜色稳定性加速试验的标准实施规（STANDARD TEST METHOD FOR ACCELERATED TESTING FOR COLOR STABILITY OF PLASTICS EXPOSED TO INDOOR OFFICE ENVIRONMENTS） ASTM D4752-2003 用溶剂擦试法测定硅酸乙酯(无机)富锌底漆耐甲乙酮的标准试验方法（STANDARD TEST METHOD FOR MEASURING MEK RESISTANCE OF ETHYL SILICATE (INORGANIC) ZINC-RICH PRIMERS BY SOLVENT RUB） ASTM D4828-1994E1(R2003) 有机覆层实际可洗性的标准试验方法（STANDARD TEST METHODS FOR PRACTICAL WASHABILITY OF ORGANIC COATINGS） ASTM D638-2003 塑料拉伸性能标准测试方法（STANDARD TEST METHOD FOR TENSILE PROPERTIES OF PLASTICS）
Motion Planning in Urban Environments:Part I Dave Ferguson Intel Research Pittsburgh Pittsburgh,PA dave.ferguson@https://www.doczj.com/doc/0314173846.html, Thomas M.Howard Carnegie Mellon University Pittsburgh,PA thoward@https://www.doczj.com/doc/0314173846.html, Maxim Likhachev University of Pennsylvania Philadelphia,PA maximl@https://www.doczj.com/doc/0314173846.html, Abstract—We present the motion planning framework for an autonomous vehicle navigating through urban environments. Such environments present a number of motion planning chal-lenges,including ultra-reliability,high-speed operation,com-plex inter-vehicle interaction,parking in large unstructured lots,and constrained maneuvers.Our approach combines a model-predictive trajectory generation algorithm for computing dynamically-feasible actions with two higher-level planners for generating long range plans in both on-road and unstructured areas of the environment.In this Part I of a two-part paper, we describe the underlying trajectory generator and the on-road planning component of this system.We provide examples and results from“Boss”,an autonomous SUV that has driven itself over3000kilometers and competed in,and won,the Urban Challenge. I.I NTRODUCTION Autonomous passenger vehicles present an incredible op-portunity for the?eld of robotics and society at large.Such technology could drastically improve safety on roads,provide independence to millions of people unable to drive because of age or ability,revolutionize the transportation industry,and reduce the danger associated with military convoy operations. However,developing robotic systems that are sophisticated enough and reliable enough to operate in everyday driving scenarios is tough.As a result,up until very recently,au-tonomous vehicle technology has been limited to either off-road,unstructured environments where complex interaction with other vehicles is non-existent[1],[2],[3],[4],[5],[6],or very simple on-road maneuvers such as highway-based lane following[7]. The Urban Challenge competition was designed to extend this technology as far as possible towards the goal of unre-stricted on-road driving.The event consisted of an autonomous vehicle race through an urban environment containing single and multi-lane roads,traf?c circles and intersections,open areas and unpaved sections,road blockages,and complex parking tasks.Successful vehicles had to travel roughly90 kilometers,all in the presence of other human-driven and autonomous vehicles,and all while abiding by speed limits and California driving rules. This challenge required signi?cant advances over the state of the art in autonomous vehicle technology.In this paper,we describe the motion planning system developed for Carnegie Mellon University’s winning entry into the Urban Challenge,“Boss”.This system enabled Boss to travel extremely quickly through the urban environment to complete its missions;inter-act safely and intelligently with obstacles and other vehicles on roads,at intersections,and in parking lots;and perform sophisticated maneuvers to solve complex parking tasks. In Part I of the paper we introduce very brie?y the software architecture used by Boss and the role of motion planning within that architecture.We then describe the trajectory gen-eration algorithm used to generate every move of the vehicle. In Section V we discuss the motion planning framework used when navigating on roads. In Part II of the paper we discuss the framework used when navigating through unstructured areas or performing complex maneuvers.We then provide results and discussion from hundreds of hours and thousands of kilometers of testing, and describe related work in both on-road and unstructured planning. II.S YSTEM A RCHITECTURE Boss’software system is decomposed into four major blocks (see Figure1).The Perception component fuses and processes data from Boss’sensors to provide key environmental infor-mation,including: ?Vehicle State,globally-referenced position,attitude and speed for Boss; ?Road World Model,globally-referenced geometric infor-mation about the roads,parking zones,and intersections in the world; ?Moving Obstacle Set,an estimation of other vehicles in the vicinity of Boss; ?Static Obstacle Map,a2D grid representation of free, dangerous,and lethal space in the world;and ?Road Blockages,an estimation of clearly impassable road sections. The Mission Planning component computes the fastest route through the road network to reach the next checkpoint in the mission,based on knowledge of road blockages,speed limits,and the nominal time required to make special maneu-vers such as lane changes or u-turns. The Behavioral Executive combines the strategic global information provided by Mission Planning with local traf?c and obstacle information provided by Perception and gen-erates a sequence of local tasks for the Motion Planner.It is responsible for the system’s adherence to various rules of the road,especially those concerning structured interactions
Kevin P.Murphy Computer Science Division University of California Berkeley,CA94720-1776 murphyk@https://www.doczj.com/doc/0314173846.html, Abstract We show how map learning can be formulated as inference in a graphical model,which allows us to handle changing environments in a natural manner.We describe several different approximation schemes for the problem,and illustrate some results on a simulated grid-world with doors that can open and close.We close by brie?y discussing how to learn more general models of(partially observed)environments,which can contain a variable number of objects with changing internal state. 1Introduction Mobile robots need to navigate in dynamic environments:on a short time scale,obstacles, such as people,can appear and disappear,and on longer time scales,structural changes, such as doors opening and closing,can occur.In this paper,we consider how to create models of dynamic environments.In particular,we are interested in modeling the location of objects,which we can represent using a map.This enables the robot to perform path planning,etc.We propose a Bayesian approach in which we view the map as a(matrix-valued)random variable,which can be updated by Bayes rule in just the same way that the other hidden state variables,such as the robot’s pose(position and orientation),are updated in the widely-used techniques of Markov localization[FBT98]and Kalman?ltering. To do Bayesian updating,we must specify the observation model(how the state predicts what the robot should see)and the transition model(how the state changes,both over time and in response to the robot’s actions).We use the formalism of factored POMDPs (Partially Observable Markov Decision Process)[CKK96,KLC98,BDH99];see Section2 for details.We must also provide a mechanism for ef?ciently performing the update equations;we discuss various approximation algorithms for this in Section3.In Section4, we show some results of applying our algorithm to a simulated dynamic environment,and in Section5we conclude and discuss future work. 2The model The three main components of a POMDP are the transition model,the observation model, and the reward model(which induces a policy).In this section,we focus on the transition
Visual Studio环境下联合Intel Math Kernel Library编 程 翻译：Lyra(Godblessmee) 说明： 本文翻译自Intel C++ Composer XE 2011的帮助文档，要实现文中所述功能需要先安装Intel C++ Composer XE 2011以及Visual Studio C++集成模块，与Microsoft Visual Studio 2005/2008/2010。 Visual C++环境下连接MKL配置 对于VS2010： ●依次选择：Project->Properties->Configuration Properties->Intel Performance Libraries； ●改变Use MKL属性设置，方法为：选择Parallel、Sequential或者Cluster； 对于VS2005/2008： ●依次选择：Project->Intel C++ Composer XE 2011->Select Build Components； ●从Use MKL下拉式菜单中，选择Parallel、Sequential或者Cluster。 特殊的MKL库取决于你的项目设置。更多细节请查阅相关文档。 创建、配置、运行Intel C++或VC++ 2008项目 本示例演示如何创建一个包含Intel MKL的VC++项目，环境为VS 2008。 下面的步骤创建了一个Win32/Debug项目，包含Intel MKL的示例。关于如何创建不同类型的VS项目，请参考MSDN。创建步骤如下： 1.创建一个C项目： a)打开VS2008； b)在主菜单中选择File->New->Project，打开New Project窗口； c)选择Project Types->Visual C++->Win32，然后选择Templates->Win32 Console Application，在Name处输入
话题20 周围的环境(The surrounding environments) Ⅰ.重点单词 1．exhibition n．展览 2．desire n．渴望 3．community n．社区 4．harmony n．和谐 5．action n．行为 6．environment n．环境 7．existence n．生存 8．pour v．倾倒 9．citizen n．公民 10．recycle v．(使)再循环 11．wildlife n．野生物 12．desert n．沙漠 13．forest n．森林 14．survival n．生存；残存；幸存 15．fuel n．燃料 Ⅱ.常考短语 1．be reluctant to 不情愿…… 2．private cars 私家车 3．feed on 吃……过日子；用……喂养(鸟兽等) 4．take in 吸收；受骗 5．die out 消灭，死绝 6．give birth to 出生 7．give out 缺乏，用尽 8．in danger 在危险中 9．in ruins 废墟 10．protect...from 保护 Ⅲ.经典句式 1．It is necessary for us to protect our environment. 对我们来说，保护环境是必要的。 2．Some people pay no attention to the environment that they live in. 有些人对于他们居住的环境毫不在意。 3．I think the government should prevent people from driving cars on certain days. 我想政府应该阻止人们在某些天不要开车。 4．We strongly advocate setting up a website where people can get to know more about general ecology. 我们强烈主张设置一个网站，在此网站上人们可以更多地了解一般的生态学。 5．Sadly，it is often only after serious consequences arise that governments will take action to reduce levels of harmful waste. 可悲的是，它往往只有严重后果产生后，政府才将采取行动，去减少有害废物的排放量。Ⅳ.佳作背诵