DrawBot: a bio-inspired robotic portraitist

Abstract

We are developing the control architecture of a portraitist artificial agent called DrawBot that reproduces the visuomotor behaviour of a human carrying out a realistic portrait. The visuomotor strategy adopted by DrawBot is based on computational models of eye movements in human beings,and one xperimental findings on eye-hand coordination in expert draughtsmen. In this paper we present a behavioural model of the visuomotor coordination adopted by a draughtsman, designed in terms of visual routines.Eventually we outline the implementation of the basic routines.     

高海拔地区500kV线路绝缘配合设计中导线绝缘子片数的选择

文章主要根据高海拔地区线路经过的污秽等级,通过泄漏比距计算出了工频电压条件下所要求的绝缘子片数,并进行海拔修正,然后根据操作过电压及雷电过电压对该绝缘子片数进行复核,最终确定导线绝缘子片数.     

带导流墙的门槽结构在闸门全开工况下的应用

从空穴特性、流态特征方面出发,分析了带导流墙的门槽结构在闸门全开泄洪情况下改善流态、降低门槽受冲刷和空蚀危险性方面的作用,认为其在深孔泄水道闸门及其他高水头平面闸门中有很好的推广应用价值。     

水资源复合系统协调性指标体系构建与调控措施研究

根据复合系统协调性理论,通过分析水资源复合系统内水资源子系统、社会经济子系统和生态环境子系统两两之间的相互作用关系,以全新的视角构建了水资源复合系统协调性评价指标体系,并针对指标反映的系统特征和系统间关系相应地提出了子系统之间协调性调控措施。     

区域水资源生态经济系统耦合关系分析

以复杂系统科学理论和生态经济学原理为指导,论述了水资源生态经济系统的层次关联模式及动态反馈关系,分析了系统耦合关系的实质和特征.在此基础上,研究了各子系统之间关系的规律性及生态环境问题发生的机制,以求为水资源生态经济系统关系的评价与调控提供理论基础.     

嵌入式Linux和Qtopia下矩阵键盘输入的实现

详细介绍了基于嵌入式Linux和Qtopia的矩阵键盘输入实现方法。通过重载Qt的事件过滤器,结合信号和槽机制,利用两级状态处理及有效输入的界定,来简化输入过程,减少按键次数,提高输入效率。同时利用Qtopia的图形显示,使输入界面清晰,更适用于嵌入式终端设备。     

Artemis-COOR:一个基于Agent的软件动态协同支撑平台

针对开放网络环境下软件协同应用需求,本文提出了一种基于Agent的软件动态协同模型。该模型以软件实体的Agent封装为基础,通过Agent运行时刻重解释以软件体系结构表达的协同逻辑和Agent间的多模式交互技术,实现对动态协同的支持。面向此概念模型,给出了相应的软件动态协同支撑平台Artemis-COOR,该平台在"非侵入式"A-gent封装、多模式交互支撑和软件体系结构动态演化支撑等方面形成了一定的技术特色。最后,给出以水雨情会商系统为例的演示性应用,展示了上述技术的可行性和有效性。     

Behaviour based on decision matrices for a coordination between agents in a urban traffic simulation

This paper describes a multi-agent coordination mechanism applied to intersection simulation situations. In a goal of urban traffic simulation, we must consider the dynamic interactions between autonomous vehicles. The field of multi-agent systems provides us some studies for such systems, in particular on the coordination mechanisms. Conflicts between vehicles (i.e. agents) are very frequent in such applications, and they may cause deadlocks, particularly at intersections such as crossroads. Our approach is based on the solving of two player games/decision matrices which characterize three basic situations. An aggregation method generalizes to n-player games for complex crossroads. The objective of this approach consists in searching basic two-player matrices for solving n-agent problems. To explain the principle, we describe our approach for a particular case of crossroad with three agents. Finally, the obtained results have been examined via a tool of road traffic simulation, ARCHISIM. We assume also that the global traffic replicates the behavior of agents in different situations.     

An optimized modular neural network controller based on environment classification and selective sensor usage for mobile robot reactive navigation

A new approach to the design of a neural network (NN) based navigator is proposed in which the mobile robot travels to a pre-defined goal position safely and efficiently without any prior map of the environment. This navigator can be optimized for any user-defined objective function through the use of an evolutionary algorithm. The motivation of this research is to develop an efficient methodology for general goal-directed navigation in generic indoor environments as opposed to learning specialized primitive behaviors in a limited environment. To this end, a modular NN has been employed to achieve the necessary generalization capability across a variety of indoor environments. Herein, each NN module takes charge of navigating in a specialized local environment, which is the result of decomposing the whole path into a sequence of local paths through clustering of all the possible environments. We verify the efficacy of the proposed algorithm over a variety of both simulated and real unstructured indoor environments using our autonomous mobile robot platform.     

基于语义的协同模型研究

大规模并行与分布式系统的出现开拓了软件技术的应用前景,要开发大规模并行与分布式系统的全部潜能,必须要处理系统中大量并发的活动体的协同过程。以Linda为代表的基于共享数据空间的协同模型和协同语言具有时间解耦、空间解耦和引用解耦的特点,为大规模并行与分布式系统的设计与发展提供了一种新方法。该文以多Agent系统为应用背景,研究有关Agent协同模型的问题,解决了现在大多数协同模型中缺乏语义信息的问题。