基于RFID的校园导航系统的设计与实现

随着GIS、LBS技术和移动互联网技术等核心技术的发展,服务于普通大众的个人导航系统成为应用热点。室内行走引导是个人导航系统的核心之一,其中涉及的室内定位技术一直是研究的难点之一。基于固定式RFID标签群,生成室内位置地图,将随身移动式RFID读写器和个人智能手机相结合,完成室内定位、路径计算和导航提醒。基于上述设计方案,完成了一个基于RFID的南京大学校园导航系统,并将其投入了实际使用。     

基于无线定位的个性化导览关键技术及其在博物馆中的应用

本文提出一种基于Wi-Fi无线定位网络能够满足相关应用精度需求的室内导览方法,该方法使用智能手机自身处理能力实时进行信号强度概率分布以及位置指纹匹配计算,使用基于动态权值的方法来对室内环境进行建模,引入加权线性公式组合推荐算法实现基于优化A星算法的路线规划。本文同时给出了该方法应用于构建博物馆个性化导览系统的应用示例,实验结果表明该方法具有较高的定位精度和推荐准确率。本文所提室内导览方法具有通用性好和组网成本低的特点,能够较好满足博物馆等室内导览系统应用需求,具备进一步进行商业化应用的潜力。     

基于ArcGIS Server的移动客户端路径导航系统

大型公共场馆建筑结构复杂,人员密度大,突发灾害事件造成的人员伤亡严重。本文针对大型公共建筑复杂室内环境下导航应用的需求,提出了一种基于Web Service技术的移动终端路径导航系统。根据大型场馆室内环境的特点,使用ArcGIS系列软件进行地图系统设计;结合移动GIS、WebService和无线数据通讯等多项技术,采用面向服务的设计思想,将主要的数据存储和计算过程在服务器端实现,突破了移动客户端存储容量和计算能力的限制,解决了移动终端最优路径分析和导航显示的问题。     

基于视觉的同时定位与地图构建方法综述

基于视觉的自主导航与路径规划是移动机器人研究的关键技术,对基于视觉的计算机导航与同时定位及地图构建（SLAM）方法近三十年的发展进行了总结和展望。将视觉导航分为室内导航和室外导航,并详细阐述了每一种子类型的特点和方法。对于室内视觉导航,列举了经典导航模型和技术方法,探讨了解决SLAM问题的最新进展：HTM-SLAM算法和基于特征的算法;对室外视觉导航,阐述了国际国内目前的研究动态。     

A faster path planner using accelerated particle swarm optimization

The idea of placing small mobile robots to move around in a large building to detect potential intruders has been around for some time. However, there are still two major hurdles to overcome: to locate itself in the environment and to make a decision on how to move around safely and effectively at a reasonable computation cost. This paper describes a mathematical model for developing a scheme for an autonomous low cost mobile robot system using visual simultaneous localization and mapping and accelerated particle swarm intelligent path planner. The results indicated that this system could provide a solution for the problem of indoor mobile robot navigation. Advances in computer technology make this technique a cost effective solution for a future home service robot.     

基于ROS与Kinect的移动机器人同时定位与地图构建

同时定位与地图构建(SLAM)技术一直以来都是移动机器人实现自主导航和避障的核心问题,移动机器人需要借助传感器来探测周围的物体同时构建出相应区域的地图。由于传统的1D和2D传感器,如超声波传感器、声呐和激光测距仪等在建图过程中无法检测出Z轴(垂直方向)上的信息,易增加机器人发生碰撞的概率,同时影响建图结果的精确度。本文利用Kinect作为机器人SLAM的传感器,将其采集到的三维信息转化成二维的激光数据进行地图构建,同时借助机器人操作系统(robot operating system,ROS)进行仿真分析和实际测试。结果表明Kinect可以弥补1D和2D传感器采集信息的不足,同时能够较好的保持建图的完整性和可靠性,适用于室内的移动机器人SLAM实现。     

A model-based sound localization system and its application to robot navigation

This paper describes a mobile robot equipped with a real time sound localization system as well as a sonar system for obstacle detection. The sound localization method is based on a model of the precedence effect of the human auditory system to cope with echoes and reverberations. Sound localization and robot navigation experiments were conducted. The results show that the robot is capable of localizing sounding objects in a reverberant environment and approaching the objects without collisions, even when the objects were behind obstacles. Environment flexibility and error robustness of the system were discussed as well.     

Hybrid indoor and outdoor location services for new generation mobile terminals

In the last years, an increasing interest in location services characterized the market of mobile ubiquitous devices (smartphones, handhelds, etc.). Several technologies and solutions have been developed to determine the position of mobile devices in their operating space, each with its specific degree of precision and accuracy. In this scenario, the ideal location service should be able of tracking the mobile terminal in any place it moves to, both indoors and outdoors. However, while outdoor location services have already achieved a satisfactory degree of technological maturity and effectiveness, a really ubiquitous location service that works satisfactorily in both indoor and outdoor scenarios is not yet available. In order to cope with the above challenge, this work proposes a hybrid location approach designed to choose and switch among multiple positioning technologies supported by the mobile device and available in the surrounding environment, in a dynamic and transparent way during the user movement. It combines signal strength–based fingerprinting techniques for indoor positioning together with traditional GPS-based positioning for the outdoor localization and performs opportunistic technology switching according to a count-and-threshold mechanism. The resulting solution is able to leverage the different features of the wireless networks and of the global positioning technologies, in order to provide ubiquitous location services across indoor and outdoor scenarios, as well as to minimize power consumption of the mobile device.     

单目视觉移动机器人导航算法研究现状及趋势

拥有自主导航能力的移动机器人在救灾、家政等人类生活中使用得愈加广泛。单目视觉导航算法作为机器人视觉导航中的一种,具有成本低、距离不受限的优势,但仍存在尺度不确定性和初始化问题。该综述根据对移动机器人的运动性质研究,主要从障碍检测、空间定位、路径规划三个方面对单目视觉导航技术进行了模块化分析,并以单目视觉导航算法的关键技术迭代与发展为脉络,对各模块的典型算法进行分析,从速度、准确性、鲁棒性等方面对不同算法进行综合性评比,并对算法存在的主要问题与难点进行剖析,结合人类对移动机器人能力的需求和移动机器人的技术状态对单目视觉导航技术的未来发展趋势进行预测。     

基于场景图谱的室内移动机器人目标搜索

在移动机器人执行日常家庭任务时,首先需要其能够在环境中避开障碍物,自主地寻找到房间中的物体。针对移动机器人如何有效在室内环境下对目标物体进行搜索的问题,提出了一种基于场景图谱的室内移动机器人目标搜索,其框架结合了导航地图、语义地图和语义关系图谱。在导航地图的基础上建立了包含地标物体位置信息的语义地图,机器人可以轻松对地标物体进行寻找。对于动态的物体,机器人根据语义关系图中物体之间的并发关系,优先到关系强度比较高的地标物体旁寻找。通过物理实验展示了机器人在语义地图和语义关系图的帮助下可以实现在室内环境下有效地寻找到目标,并显著地减少了搜索的路径长度,证明了该方法的有效性。     

A real-time indoor localization approach integrated with a Geographic Information System (GIS)

Nowadays, accurate maps from mostly anywhere in the world can be obtained for free, with the exception of indoor spaces. However, the evidence seems to suggest that in the next few years indoor maps will be more and more available for anyone. Thus, profiting from the idea of easily obtainable indoor maps, we present a novel approach for real-time mobile robot localization that focuses on spatial reasoning at a high abstraction level. In order to manage and query existing indoor spatial models, we rely on the power of Geographic Information Systems (GIS) and spatial databases. Moreover, to extract symbolic information from the environment, we have developed a door detection system that fuses 2D laser and vision data. We have integrated these two ideas into an extended Kalman filter localization framework. Our proposal has been implemented and tested through autonomous navigation missions in real-world scenarios. Extensive experimental results are provided, which show robustness and accuracy concerning both door detection and localization.     

基于改进双向测距到达时间差定位算法的超宽带定位系统

针对传统无线定位技术在室内定位精度不高的问题,设计实现了一种基于超宽带（UWB）技术的室内定位系统。首先,提出了定位服务器与移动端APP实时交互的系统结构,解决室内移动人员自主定位与导航的问题。其次,在双向测距（TWR）算法中增加一条无线电信息以减小时钟偏移引起的测距误差,从而提高算法性能。最后,将通过到达时间差（TDOA）定位算法得到的双曲面方程组进行线性化处理后结合Jacobi迭代法完成求解,避免了使用标准TDOA定位算法难以直接解算的情况。经测试,该系统在楼道房间等场景中能稳定工作且定位误差控制在30 cm以内,相比基于WiFi、蓝牙等技术的定位系统在定位精度上提高了10倍左右,能够满足在复杂室内环境中的精确移动定位需求。     

Vision for mobile robot navigation: a survey

Surveys the developments of the last 20 years in the area of vision for mobile robot navigation. Two major components of the paper deal with indoor navigation and outdoor navigation. For each component, we have further subdivided our treatment of the subject on the basis of structured and unstructured environments. For indoor robots in structured environments, we have dealt separately with the cases of geometrical and topological models of space. For unstructured environments, we have discussed the cases of navigation using optical flows, using methods from the appearance-based paradigm, and by recognition of specific objects in the environment     

视觉里程计技术综述

视觉里程计是通过视觉信息估计运动信息的技术,其中采用了里程计式的方法。该技术作为一种新的导航定位方式,已成功地运用于自主移动机器人中。首先介绍了常用的两种视觉里程计即单目视觉里程计和立体视觉里程计,然后从鲁棒性、实时性和精确性三个方面详细讨论了视觉里程计技术的研究现状,最后对视觉里程计的发展趋势进行了展望。     

Ubiquitous interaction with positioning and navigation using a novel light sensor-based information transmission system

This paper describes a novel light sensor-based information transmission system for indoor positioning and navigation with particular benefits for mobile and wearable computers. It can seamlessly extend outdoor GPS tracking to the indoor environment. In a novel manner, fluorescent light is used as the medium to transmit information, which is encoded by using a pulse-frequency modulation technique. The user receives the encoded light information through a photo-receiver. The information is passed into the wearable or mobile computer after the data is decoded. This information allows positioning information to be given to indoor mobile and wearable computers. We design an economical transmitter circuit by adding few components to a commercial electronic ballast circuit for fluorescent lamps with price of less than US $10. The propose system can be used in indoor guidance and navigation applications. Exemplary applications are included in the paper, with experimented results detailed.     

移动机器人基于激光测距和单目视觉的室内同时定位和地图构建

该文研究了部分结构化室内环境中自主移动机器人同时定位和地图构建问题.基于激光和视觉传感器模型的不同,加权最小二乘拟合方法和非局部最大抑制算法被分别用于提取二维水平环境特征和垂直物体边缘.为完成移动机器人在缺少先验地图支持的室内环境中的自主导航任务,该文提出了同时进行扩展卡尔曼滤波定位和构建具有不确定性描述的二维几何地图的具体方法.通过对于SmartROB-2移动机器人平台所获得的实验结果和数据的分析讨论,论证了所提出方法的有效性和实用性.     

Landmark detection in mobile robotics using fuzzy temporal rules

Detection of landmarks is essential in mobile robotics for navigation tasks like building topological maps or robot localization. Doors are one of the most common landmarks since they show the topological structure of indoor environments. In this paper, the novel paradigm of fuzzy temporal rules is used for detecting doors from the information of ultrasound sensors. This paradigm can be used both to model the necessary knowledge for detection and to consider the temporal variation of several sensor signals. Experimental results using a Nomad 200 mobile robot in a real environment produce 91% of doors were correctly detected, which show the reliability and robustness of the system.     

Skeleton pruning as trade-off between skeleton simplicity and reconstruction error

The position and orientation of moving platform mainly depends on global positioning system and inertial navigation system in the field of low-altitude surveying, mapping and remote sensing and land-based mobile mapping system. However, GPS signal is unavailable in the application of deep space exploration and indoor robot control. In such circumstances, image-based methods are very important for self-position and orientation of moving platform. Therefore, this paper firstly introduces state of the art development of the image-based self-position and orientation method (ISPOM) for moving platform from the following aspects: 1) A comparison among major image-based methods (i.e., visual odometry, structure from motion, simultaneous localization and mapping) for position and orientation; 2) types of moving platform; 3) integration schemes of image sensor with other sensors; 4) calculation methodology and quantity of image sensors. Then, the paper proposes a new scheme of ISPOM for mobile robot — depending merely on image sensors. It takes the advantages of both monocular vision and stereo vision, and estimates the relative position and orientation of moving platform with high precision and high frequency. In a word, ISPOM will gradually speed from research to application, as well as play a vital role in deep space exploration and indoor robot control.