基于聚类匹配的移动机器人地图实时创建算法

提出了一种基于模式识别聚类思想的数据点集匹配算法.该匹配算法具有传统迭代匹配算法和非迭代匹配算法的优点,匹配速度快,精度高.结合上述匹配算法,给出了一种基于激光测距仪的移动机器人环境地图实时创建方法.该方法使用从环境数据中提取出的特征点来完成两组激光数据点集的匹配,进而完成环境地图的创建.利用本实验室自主研发的救援机器人平台对该算法进行了验证,实验结果表明,该算法能够完成室内环境下移动机器人实时准确有效的环境地图创建.     

基于环境贴图的实时光照及其在VR中的应用

为了解决全局光照下漫反射和高光反射的实时计算,提出了一种利用环境贴图实现漫反射和高光反射实时渲染的综合算法。通过对原始光照环境贴图进行分级,改进了原有计算漫反射贴图的滤波算法,提高了运算速度。同时在保证一定逼真度的条件下,利用硬件完成了高光反射贴图的生成。最终通过可编程图形管道,完成了光照的实时计算和渲染。实验结果表明,这种综合算法可以在VR程序中达到比较满意的效果。     

Gossip-based cooperative caching for mobile applications in mobile wireless networks

Cooperative caching is an efficient way to improve the performance of data access in mobile wireless networks, by cache nodes selecting different data items in their limited storage in order to reduce total access delay. With more demands on sharing a video or other data, especially for mobile applications in an Internet-based Mobile Ad Hoc Network, considering the relations among data items in cooperative caching becomes more important than before. However, most of the existing works do not consider these inherent relations among data items, such as the logical, temporal, or spatial relations. In this paper, we present a novel solution, Gossip-based Cooperative Caching (GosCC) to address the cache placement problem, and consider the sequential relation among data items. Each mobile node stores the IDs of data items cached locally and the ID of the data item in use into its progress report. Each mobile node also makes use of these progress reports to determine whether a data item should be cached locally. These progress reports are propagated within the network in a gossip-based way. To improve the user experience, GosCC aims to provide users with an uninterrupted data access service. Simulation results show that GosCC achieves better performance than Benefit-based Data Caching and HybridCache, in terms of average interruption intervals and average interruption times, while sacrificing message cost to a certain degree.     

基于声纳传感器的移动机器人地图创建方法研究*

提出了一种改进的基于声纳传感器信息进行栅格地图创建的方法。将Bayes法则用于移动机器人地图创建,对多个声纳传感器信息进行融合,解决信息间的冲突问题,并根据声纳模型将测量数据集成到局部地图中,改变栅格被障碍物占有的概率。经过坐标变换后,利用Bayes法则更新全局地图中的栅格信息,实现从局部地图到全局地图的更新。实验验证了该算法的可行性与有效性。     

Real-time building of a thinning-based topological map

An accurate and compact map is essential to an autonomous mobile robot system. A topological map, one of the most popular map types, can be used to represent the environment in terms of discrete nodes with edges connecting them. It is usually constructed by Voronoi-like graphs, but in this paper the topological map is incrementally built based on the local grid map by using a thinning algorithm. This algorithm, when combined with the application of the C-obstacle, can easily extract only the meaningful topological information in real-time and is robust to environment change, because this map is extracted from a local grid map generated based on the Bayesian update formula. In this paper, position probability is defined to evaluate the quantitative reliability of the end node extracted by the thinning process. Since the thinning process builds only local topological maps, a global topological map should be constructed by merging local topological maps according to nodes with high position probability. For real and complex environments, experiments showed that the proposed map building method based on the thinning process can accurately build a local topological map in real-time, with which an accurate global topological map can be incrementally constructed.     

Real-time data dissemination in mobile peer-to-peer networks

Mobile peer-to-peer networks have found many uses such as streaming of audio and video data. There are circumstances, such as emergency situations and disaster recovery, when real-time delivery is a fundamental requirement. The problem is challenging due to the limited network capacity, the variable transmission rates and the unpredictability with respect to the network conditions in the mobile peer-to-peer network.In this paper we address the problem of real-time data dissemination of multimedia streams in mobile peer-to-peer networks. Four routing algorithms are proposed based on a packet's deadline, priority or a combination of these metrics. They are simulated under different setups in a mobile peer-to-peer network with Bluetooth connectivity and nodes broadcasting audio and video streams using different priorities. We compare the performance of the algorithms using a number of metrics. Detailed experimental results are presented. Based on these results, propositions on the usage of the algorithms and the design of network requirements are presented.     

地图符号服务与地图服务的耦合

为了实现地图符号在地图服务(WMS)中的应用,达到灵活定制WMS可视化效果的目的,从支持WMS的图层样式描述规范(SLD)入手,通过对SLD和WMS的分析,研究网络地图符号的发布方法,设计地图符号服务框架,提出了基于SLD,地图符号服务与WMS的耦合方法,以解决基于WMS的WebGIS应用中无法通过符号改变地图可视化效果的问题,实验结果表明该方法可以有效地关联地图符号服务与WMS,实现了WMS可视化效果的灵活定制.     

Sentient map – a new paradigm for visual computing

 A sentient map enables the user to view a collection of information items as a map so that gestures, or more specifically c-gestures, can be used for the interaction between the user and the information system. Different c-gestures are dynamically transformed into spatial/temporal queries, or σ-queries, for accessing the information items in multimedia databases and data sources. An application in e-learning called the Growing Book is described. The visual computing paradigm offered by the sentient map can be summarized as follows: “I come, I see, I gesture”.     

实时通告服务设计与实现

OMG通告服务为对策之间提供强有力的解耦通信支持,是CORBA提供的重要服务之一,目前很多应用需要之间的通信具有实时性,而现有的通告服务规范已不能满足这种需求,为此,设计并实现了具有实时功能的通告服务,提出了一种实时通告服务的体系结构,讨论了实时通告服务系统的实现技术。     

Monitoring and evaluating the quality of Web Map Service resources for optimizing map composition over the internet to support decision making

Over the past 10 years, there have been great advances in the interoperability technologies in geographic information science. More than 10,000 map layers are available online today through Open Geospatial Consortium (OGC) specified interfaces, such as Web Map Service (WMS), Web Feature Service (WFS), and Web Coverage Service (WCS). These map layers are persistently serving the geospatial communities; however, our empirical study found that their potential value has not been fully exploited. Frequently, a targeted map cannot be composed because some published map servers are unavailable. This problem becomes more serious when a map is composed of several layers from different servers. These services are geographically distributed and maintained by various hosts; therefore, simply waiting for service improvement on the host side cannot solve this problem. In this paper, we proposed a new approach and developed a mechanism that allows clients to select the best map layers at run-time. The selection is based on the results of continuous monitoring and evaluation of the quality of WMSs. Based on Service Oriented Architecture (SOA), this approach includes quality monitoring and evaluation modules. Quality factors are taken into account during the process of registration, search, and bind. The OGC capability document is extended to include WMS quality information. Three prototype systems were developed in this study to demonstrate: (a) how WMS layers are monitored and evaluated, (b) how the subjective evaluation of WMS quality by a user is collected, and (c) how this can be a feasible method to fuse WMS resources suitable for decision making.     

实时事件服务设计与实现

提出一个扩展标准ＣＯＲＢＡ事件服务的方案,通过在标准事件服务事件通道中增加事件描述过滤模块、优先级和时间设定模块、调度模块和相关事件处理模块,并对原有消费者代理和供给代理模块的功能扩充,使之有进行实时事件处理、实时事件广播等满足实时应用要求的实时事件服务。     

Object-spatial layout-route based hybrid map and global localization for mobile robots

This paper presents new object-spatial layout-route based hybrid map representation and global localization approaches using a stereo camera. By representing objects as high-level features in a map, a robot can deal more effectively with different contexts such as dynamic environments, human-robot interaction, and semantic information. However, the use of objects alone for map representation has inherent problems. For example, it is difficult to represent empty spaces for robot navigation, and objects are limited to readily recognizable things. One way to overcome these problems is to develop a hybrid map that includes objects and the spatial layout of a local space. The map developed in this research has a hybrid structure that combines a global topological map and a local hybrid map. The topological map represents the spatial relationships between local spaces. The local hybrid map combines the spatial layout of the local space with the objects found in that space. Based on the proposed map, we suggest a novel coarse-to-fine global localization method that uses object recognition, point cloud fitting and probabilistic scan matching. This approach can accurately estimate robot pose with respect to the correct local space. Recommended by Editor Jae-Bok Song. This research was performed for the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Knowledge Economy of Korea. Soonyong Park received the B.S. and M.S. degrees from the Department of Mechanical Engineering, Kyunghee University, Seoul, Korea, in 2001 and 2003, respectively. He is currently working toward the Ph.D. degree in the Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea. Since 2001, he has been a student researcher in the Center for Cognitive Robotics Research, Korea Institute of Science and Technology (KIST), Seoul, Korea. His research interests include mobile robot navigation and computer vision. Mignon Park received the B.S. and M.S. degrees in Electronics from Yonsei University, Seoul, Korea, in 1973 and 1977, respectively. He received the Ph.D. degree in University of Tokyo, Japan, 1982. He was a researcher with the Institute of Biomedical Engineering, University of Tokyo, Japan, from 1972 to 1982, as well as at the Massachusetts Institute of Technology, Cambridge, and the University of California Berkeley, in 1982. He was a visiting researcher in Robotics Division, Mechanical Engineering Laboratory, Ministry of International Trade and Industry, Tsukuba, Japan, from 1986 to 1987. He has been a Professor in the Department of Electrical and Electronic Engineering in Yonsei University, since 1982. His research interests include fuzzy control and application, robotics, and fuzzy biomedical system. Sung-Kee Park is a principal research scientist for Korea Institute of Science and Technology (KIST). He received the B.S. and M.S. degrees in Mechanical Design and Production Engineering from Seoul National University, Seoul, Korea, in 1987 and 1989, respectively. He received the Ph.D. degree (2000) from Korea Advanced Institue of Science and Technology (KAIST), Korea, in the area of computer vision. Since then, he has been working for the center for cognitive robotics research at KIST. During his period at KIST, he held a visiting position at the Robotics Institute of Carnegie Mellon University in 2005, where he did research on object recognition. His recent work has been on cognitive visual processing, object recognition, visual navigation, and human-robot interaction.     

一种保证传感器网络实时服务的中间件机制

传感器网络技术的发展导致了在应用与网络之间建立中间件,根据系统资源及网络能源保证在网络上并发运行的应用的QoS。首先,本文结合传感器网络的特性及实时应用的特点,定义了一个事件驱动的保证实时QoS的传感器网络中间件框架。然后,定义了传感器网络中实时应用的执行模型,提出了一种基于时间戳相关的实现技术,在应用调度中结合应用语义保证实时QoS、数据流的时间一致性及并发应用执行的逻辑一致性。最后,给出了基于时间戳模型的调度算法。通过性能测试结果分析表明,它能够显著提高系统的运行效率及对高速外部采集数据处理的实时性,特别适应于处理间歇、高速的传感器网络外部采集数据。     

iFrame: Dynamic indoor map construction through automatic mobile sensing

Many pervasive computing applications depend upon maps for support of location based services. Individuals can determine their location outdoors on these maps via GPS. Indoor pervasive applications may also need to know the layout of buildings, however indoor maps are less prevalent. This paper presents iFrame, a dynamic approach that leverages existing mobile sensing capabilities for constructing indoor floor plans. We explore how iFrame users may collaborate and contribute to constructing 2-dimensional indoor maps by merely carrying smartphones. A deployment study shows iFrame is an unattended approach that provides a skeleton map of a real building effectively and automatically.     

Linear time algorithms for an image labelling machine

Region labelling is one of the essential preprocessing operations in an image understanding system. In this paper we present two region labelling algorithms for a multiprocessor architecture with a time complexity of O(n).     

温室移动机器人复合栅格地图构建方法研究

针对温室环境中机器人依靠自身携带的传感器无法获取全面的环境信息,从而常导致路径规划错误的问题,提出了一种结合外部传感器系统获取温室环境信息,构建复合栅格地图的方法。首先,利用无线传感器网络定时采集对机器人通过性有影响的温度、湿度环境信息,并发送给机器人;其次,当温度或湿度数据的变化率达到设定阈值时,机器人利用阈值分割和插值法分别建立温度和湿度栅格地图;最后,将温度栅格地图、湿度栅格地图和室内障碍物物栅格地图相结合,构建动态更新的复合栅格地图。经测试,采用常规A*算法规划路径时,基于环境数据变化率阈值设定为±10%的复合栅格地图的成功率和完成时间,分别是基于普通栅格地图成功率的2.5倍,和1.05倍。结果表明,复合栅格地图能提高路径规划的成功率,并且不会由于动态更新复合栅格地图,导致机器人响应时间明显增加,实时性能满足系统的实际需求。     

Bisection approach for pixel labelling problem

This paper formulates pixel labelling as a series of two-category classification. Unlike existing techniques, which assign a determinate label to each pixel, we assign a label set to each pixel and shrink the label set step by step. Determinate labelling is achieved within log₂n (n is size of label set) steps. In each step, we bisect the label set into two subsets and discard the one with higher cost of assigning it to the pixel. Simultaneous labelling of an image is carried out by minimizing an energy function that can be minimized via graph cut algorithm. Based on the bisection approach, we propose a bitwise algorithm for pixel labelling, which set one bit of each pixel's label in each step. We apply the proposed algorithm to stereo matching and image restoration. Experimental results demonstrate that both good performance and high efficiency are achieved.     

TAPON-MT: A versatile framework for semantic labelling

Semantic labelling refers to the problem of assigning known labels to the elements of structured information from a source such as an HTML table or an RDF dump with unknown semantics. In the recent years it has become progressively more relevant due to the growth of available structured information in the Web of data that need to be labelled in order to integrate it in data systems. The existing approaches for semantic labelling have several drawbacks that make them unappealing if not impossible to use in certain scenarios: not accepting nested structures as input, being unable to label structural elements, not being customisable, requiring groups of instances when labelling, requiring matching instances to named entities in a knowledge base, not detecting numeric data, or not supporting complex features. In this article, we propose TAPON-MT, a framework for machine learning semantic labelling. Our framework does not have the former limitations, which makes it domain-independent and customisable. We have implemented it with a graphical interface that eases the creation and analysis of models, and we offer a web service API for their application. We have also validated it with a subset of the National Science Foundation awards dataset, and our conclusion is that TAPON-MT creates models to label information that are effective and efficient in practice.