网络课件导航树动态管理的设计与实现

通过研究网络课件导航树的结构与特点,提出了基于全局索引码整数运算的页面导航定位方法,并在此基础上采用.NET和MS SQL Server技术设计与实现了导航树动态管理模块,该模块可以方便地移植到需要进行多级分类数据管理的应用程序中.     

Interface split routing for finer-grained traffic engineering

Legacy IP routing restricts the efficacy of traffic engineering solutions. This restriction stems from the constraint that traffic at a node must be uniformly split across all next-hop nodes corresponding to equal cost shortest path to a destination. Proposals that alleviate this constraint either completely overhaul legacy IP routing, or introduce complex control and/or forwarding plane components. This additional complexity departs from the elegant simplicity of legacy routing protocols where statically optimized link weights embed all traffic engineering semantics.

We present Interface Split Routing (ISR), which retains the basic forwarding and control mechanism of legacy IP routing. Furthermore, a set of link weights embed all traffic engineering semantics in ISR. However, ISR makes possible finer-grained traffic engineering by configuring independent sets of next-hops to a destination at each incoming interface. This lends itself well to modern router architectures where each incoming interface has its own forwarding table. Consequently, at the aggregated node level, traffic to a particular destination may be non-uniformly distributed across next-hop nodes. Hence, ISR allows additional flexibility in routing traffic as compared to default IP routing while retaining its simplicity. We conduct simulation studies on representative ISP topologies to compare ISR with traditional link-weight-optimized routing. ISR reduces the difference between optimal routing and weight-optimized routing by 50%.     

A study of an autonomous mobile robot for a sewer inspection system

This article describes a prototype autonomous mobile robot, KANTARO, designed for inspecting sewer pipes. It is able to move autonomously in 200–300-mm-diameter sewer pipes, to turn smoothly through 90° at a junction, and to go down a 5-cm step. KANTARO carries all the resources required, such as a control unit, a camera, a 2D laser, and an IR sensor. Damage or abnormalities in sewer pipes are detected based on recorded sensory data. KANTARO has demonstrated its effectiveness in inspection and in autonomous navigation in a dry sewer test field at the FAIS–Robotics Development Support Office (FAIS–RDSO). This work was presented in part at the 11th International Symposium on Artificial Life and Robotics, Oita, Japan, January 23–25, 2006     

Theory and experiments in SmartNav rover navigation

This paper describes theoretical and experimental results using the SmartNav rule-free fuzzy rover navigation system. SmartNav divides the terrain perceived by the rover into a number of circular sectors, and evaluates each sector using goal and safety preference factors to differentiate between preferred and unpreferred terrain sectors. The goal-preference factor is used to make sector evaluation based on the sector orientation relative to the designated goal position. The safety-preference factors are used to make sector evaluations on the basis of the sector local and regional terrain hazards. Three methods are developed to blend the three sector evaluations in order to find the effective preference factor for each sector. Two sector selection methods are then described in which the sector preference factors are used to find the heading command for the rover. The rover speed command is also computed based on the goal distance and safety-preference factor of the chosen sector. The above navigation steps are continuously repeated throughout the rover motion. Experimental results are presented to demonstrate the navigational capabilities of SmartNav using a commercial Pioneer 2AT rover traversing a simulated Martian terrain at the JPL Mini Mars Yard.

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M2S maps: supporting real-world navigation with mobile VR

Mobile devices are becoming increasingly integrated into our society. In addition to entertaining people with applications like pervasive games, mobile devices can also help to address cognitive challenges people face in the real world. This paper, by drawing on research findings from cognitive psychology and geography, explores a design to use mobile VR to help people overcome one cognitive barrier in navigation, which is to establish the correspondence between 2D spatial information found in maps and 3D entities they perceive from the real world. The design offers users multi-format, multi-scale, and semantic (M²S) maps, ranging from 2D maps to 3D immersive environments, and helps users to connect 2D maps to the real world through 3D environments which are equipped with semantic representation and animation techniques. Consequently, users can apply various kinds of spatial knowledge, 2D or 3D, in understanding the real world as well as assisting in navigation. This research enhances the design repertoire of mobile VR, and suggests a way to integrate virtual environments into people’s real-world life by examining the cognitive implications of 3D models on users’ activities.     

Three and higher dimensional autonomous formations: Rigidity, persistence and structural persistence

In this paper, we generalize the notion of persistence, which has been originally introduced for two-dimensional formations, to R^d for d?3, seeking to provide a theoretical framework for real world applications, which often are in three-dimensional space as opposed to the plane. Persistence captures the desirable property that a formation moves as a cohesive whole when certain agents maintain their distances from certain other agents. We verify that many of the properties of rigid and/or persistent formations established in R² are also valid for higher dimensions. Analysing the closed subgraphs and directed paths in persistent graphs, we derive some further properties of persistent formations. We also provide an easily checkable necessary condition for persistence. We then turn our attention to consider some practical issues raised in multi-agent formation control in three-dimensional space. We display a new phenomenon, not present in R², whereby subsets of agents can behave in a problematic way. When this behaviour is precluded, we say that the graph depicting the multi-agent formation has structural persistence. In real deployment of controlled multi-agent systems, formations with underlying structurally persistent graphs are of interest. We analyse the characteristics of structurally persistent graphs and provide a streamlined test for structural persistence. We study the connections between the allocation of degrees of freedom (DOFs) across agents and the characteristics of persistence and/or structural persistence of a directed graph. We also show how to transfer DOFs among agents, when the formation changes with new agent(s) added, to preserve persistence and/or structural persistence.     

Self-organising navigational support in lifelong learning: How predecessors can lead the way

Increased flexibility and modularisation in higher education complicates the process of learners finding their way through the offerings of higher education institutions. In lifelong learning, where learning opportunities are diverse and reach beyond institutional boundaries, it becomes even more complex to decide on a learning path. However, efficient and effective lifelong learning requires that learners can make well informed decisions. Drawing on principles of self-organisation and indirect social interaction, this article suggests solving the problem by analysing the paths followed by learners and feeding this information back as advice to learners facing navigational decisions. This article starts by introducing the principles of self-organisation and indirect social interaction. It describes how we expect the use of indirect social interaction using collaborative filtering to enhance effectiveness (completion rates and amount of progress) and efficiency (time taken to complete) in lifelong learning. The effects were tested in a controlled experiment, with the results showing effects on effectiveness though not on efficiency. The study shows that indirect feedback is a promising line of enquiry for navigational support in lifelong learning.     

编队约束下的AUV路径跟踪

研究了自主水下航行器(AUV)编队约束下的路径跟踪问题。将整个系统的误差分为2部分:①各AUV自身的跟踪误差;②AUV的编队误差;在此基础上,针对AUV的参数不确定性以及海流干扰等特点,提出了一种自适应变结构控制律,在滑动面的选取中,同时考虑了AUV的路径跟踪误差以及AUV之间的编队误差。文章从理论上证明了控制律的稳定性,并讨论了控制律实现中路径参数更新律的选取问题。仿真结果表明,所设计的控制律可以使AUV克服海流干扰,达到编队航行的目的,并且考虑编队约束时AUV相互之间的的距离误差比不考虑编队约束时的误差小。     

数字气田智能管网协调调峰模型研究

结合气田管网应急调度实际需求，从气田生产中采、集、输、配各环节的整体效益着眼，提出一种基于大系统分解协调的气田管网调峰模型及其实现技术，该模型渗透了大系统分级递阶、分而治之的思想；对复杂管网进行了形式化描述，解决了类似气田复杂管网的计算存储问题，有利于加速管网优化算法的运行。针对气田生产调度实时性问题的解决，构建了基于智能信息推拉技术（IIPP）的快速数据智能推送机制。最后通过示范工程中相关应用系统运行界面的展示证实了模型的有效性。     

Cobot in LambdaMOO: An Adaptive Social Statistics Agent

We describe our development of Cobot, a novel software agent who lives in LambdaMOO, a popular virtual world frequented by hundreds of users. Cobot’s goal was to become an actual part of that community. Here, we present a detailed discussion of the functionality that made him one of the objects most frequently interacted with in LambdaMOO, human or artificial. Cobot’s fundamental power is that he has the ability to collect social statistics summarizing the quantity and quality of interpersonal interactions. Initially, Cobot acted as little more than a reporter of this information; however, as he collected more and more data, he was able to use these statistics as models that allowed him to modify his own behavior. In particular, cobot is able to use this data to “self-program,” learning the proper way to respond to the actions of individual users, by observing how others interact with one another. Further, Cobot uses reinforcement learning to proactively take action in this complex social environment, and adapts his behavior based on multiple sources of human reward. Cobot represents a unique experiment in building adaptive agents who must live in and navigate social spaces.