目标围捕任务中搜索与预包围阶段的群机器人行为学习

为了进行群机器人协同作业,提出目标搜索中导航类集体行为学习策略.在使用具有闭环调节功能的动态任务分工方法进行任务分配、自组织地生成多个子群后,在子群中引入基于社会学习微粒群算法的机器人行为学习策略.在子群框架内,机器人各自独立地以感知的共同意向目标信号强度为标准对所有成员排序,将感知优于自己的机器人作为行为示范者.然后在搜索空间各维度上分别随机选择一个行为示范者,学习其在相应维度上的位置坐标,经构造得到搜索空间中自己的学习行为向量,由此决策自身的运动行为.仿真结果表明,在不需要学习全局社会经验的前提下,机器人能针对所属子群的共同意向目标进行协同作业,提高搜索效率.     

群机器人多目标搜索中带闭环调节的动态任务分工

群机器人在并行化地同时搜索多个目标时,须通过任务分工形成若干个子群联盟,每个子群分别针对一个确定性目标协同搜索.非结构化环境中搜索对象和搜索主体的变化,要求任务分工动态进行.故在基于响应阈值分工模型基础上,提出一种带闭环调节的动态分工方法.根据机器人或者通过检测目标信号、或者通过邻域通信获得目标认知的特点,将元任务分类并构造个性化任务集,基于概率原则评估针对目标激励的响应并自主选取意向目标.具有共同意向的机器人自组织地缔结子群联盟.然后用平均距离法度量子群联盟内的机器人资源配置水平,作为负反馈引入任务分工模型,调节机器人在不同子群联盟间动态迁移.仿真结果表明,使用本文方法对群机器人动态分工后进行协同搜索,搜索效率较现有方法有显著提高.     

群机器人任务分工与协同搜索方法

群机器人执行搜索任务时,为平衡任务分工和提高协同搜索效率,提出预分工与反馈调节的双层分工方法和模拟鸟群觅食的协同搜索方法。在任务分工方面,以探测的目标强度为依据建立目标选择概率函数,使用轮盘赌确定机器人意向目标,将意向目标相同的机器人预分配为同一子群,使用反馈调节法实现分工平衡。在协调搜索方面,模拟鸟群觅食过程,提出粒子群-人工势场的搜索和避障协同控制方法。仿真结果表明,协同搜索方法能够锁定区域内所有目标,与文献[10]方法相比,任务完成平均耗时减少了17.14%,最优耗时减少了18.61%,验证了该方法在任务分工和目标搜索上的优越性。     

动态双子群协同进化果蝇优化算法

针对基本果蝇优化算法(FOA)寻优精度不高和易陷入局部最优的缺点,提出动态双子群协同进化果蝇优化算法(DDSCFOA).该算法在运行过程中根据群体的进化水平,动态地将整个种群划分为先进子群和后进子群;先进子群采用混沌算法在局部最优解邻域内进行精细的局部搜索,后进子群采用基本FOA算法进行全局搜索,较好地平衡局部搜索能力和全局搜索能力;两个子群间的信息通过全局最优个体的更新和种群个体的重组进行交换.DDSCFOA算法能跳出局部极值,避免陷入局部最优.仿真结果表明,动态双子群协同进化的策略有效可行,DDSCFOA算法比基本FOA算法具有更好的优化性能.     

基于多粒子群协同的动态多目标优化算法及应用

在现实生活中大多数多目标优化问题都随时间变化,这就要求优化算法在时间约束内快速找到动态变化Pareto最优解或Pareto边界.基于此,提出一种基于多种群协同的动态多目标粒子群改进算法,旨在利用多种群竞争和协作两种模式互相配合,从而达到快速高效求解动态多目标优化问题的目的,多种群竞争模式主要任务是对解空间进行“勘探”搜索,当竞争失效后,自适应切换到协作模式对解空间进行“开采”搜索.通过对多种群协同搜索概率分析,证明多种群相比单种群具有更高的搜索效率,通过对3类动态多目标测试函数仿真,验证了改进算法的有效性;最后将该方法应用于动态系统PID控制器的参数整定上,得到了较优的控制参数,取得满意的控制效果.     

基于随机扩散搜索的协同差分进化算法

针对差分进化算法存在的收敛速度慢、稳健性差等问题,借鉴多种群并行机制和随机搜索策略,提出一种基于随机扩散搜索的协同差分进化算法。引入反向混沌搜索的初始化机制,利用随机扩散搜索策略将种群分为成功和失败2个子群并进行改进,对改进的成功和失败子群分别采用不同的差分策略,克服单一差分策略的缺陷,同时定期使子群的部分最好与最差个体实现一对一的信息交流,从而达到协同进化的目的。仿真结果证明,与粒子群优化算法及差分进化算法相比,该算法具有较好的收敛速度和寻优能力。     

绝对定位机制下目标位置估计辅助的群机器人搜索

基于扩展微粒群算法模型控制群机器人协同搜索目标时,成员机器人在社会经验和自身认知,主要是社会经验引导下逐步向目标趋近.由于社会经验仅从成员机器人的认知中“选举”产生,未形式化地融合多个机器人的经验,因此文中从群机器人通信子系统在本质上属于无线传感器网络的事实出发,引入集体决策机制,改进社会经验的生成模式.用无线传感器网络中的测距定位方法来估计目标位置,并将估计值作为社会经验引入现有模型.仿真结果表明,当群体规模够大时,采用文中社会经验生成模式可使协同搜索速度得到提高.     

多子群协同进化的多目标微粒群优化算法

微粒群优化(PSO)算法是一种非常有竞争力的求解多目标优化问题的群智能算法,因其容易陷入局部极值,导致非劣解集的收敛性和正确性不理想。为此提出一种基于多目标分解进化策略的多子群协同进化的多目标微粒群优化算法(MOPSO_MC),算法中每个子群对应于一个多目标分解之后的子问题,并构造了一种新的速率更新策略,每个粒子跟踪自身历史最优值、子群最优值和子群邻域最优值,从而在增强算法的局部寻优能力的同时,也能从邻域子群获得进化信息,实现协同进化。最后通过仿真实验,与现在主流的多目标微粒群算法在ZDT基准测试函数上比较,验证了算法的收敛性,解分布的均匀性和正确性。     

基于多样性检测的双子群多目标粒子群算法

为了平衡多目标粒子群算法的多样性和收敛性,提出一种基于多样性检测的多子群多目标粒子群算法.首先,将多样性检测方法引入到多目标粒子群算法中,并结合多目标粒子群算法的特点进行改进.然后,将种群分为两个不同分工的子群,一个子群保持较好的多样性,在搜索空间进行全局搜索;另一个子群保持较好的收敛性,在Pareto前沿附近进行局部搜索.最后,根据多样性度量指标调整两个子群的搜索行为,以达到兼顾多样性和收敛性的目的.在标准测试问题上的仿真结果表明了所提算法的有效性.     

基于集散式模型预测控制的多无人机协同分区搜索

针对多无人机在对大范围目标区域执行协同搜索任务时搜索资源分配不均、容易因频繁转场造成资源浪费等问题,借鉴集中式控制和分布式控制结构的优点,建立了集散式多无人机(unmanned aerial vehicle,UAV)协同搜索结构体系,通过聚类分析和V图划分等方法对目标区域进行分区,结合各子区域任务特点对无人机群进行搜索任务分配,并采用一种经改进后可有效增大UAV预测范围的预测控制模型,研究了动态环境下多UAV集散式协同分区搜索问题,最后,将所提方法与常见几种协同搜索方法进行对比仿真,获取仿真结果验证了所提方法在目标发现概率和搜索效率方面的有效性和优越性.     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and     

Editorial:Brain-machine interface(BMI) and cyborg intelligence

正Brain-machine interfaces(BMIs)aim at building a direct communication pathway between the brain and an external device,and represent an area of research where significant progress has been made during the past decade.Based on BMIs,mind information can be read out by neural signals to control     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate     

SCIENCE CHINA Information Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate