小卫星编队飞行的自主控制与规划调度

本文针对小卫星编队飞行研究的重点问题,从功能分配的角度对小卫星编队飞行的自主控制系统进行设计,并针对小卫星编队飞行的规划和调度采用基于模型的智能推理方式进行工作这一特点,研究了小卫星编队飞行的规划和调度系统的体系结构。     

三峡工程船舶智能调度系统的动态规划建模与算法

本文讨论了多个并联船闸的智能调度问题,并使用动态规划理论建立了该问题的数学模型,提出了一种基于滑动窗口方法的算法。实践证明,该算法能快速得出较优解,很好地满足了自动编制船闸调度计划的需求。     

多模式智能教学系统教学规划与模式调度研究

具有多种教学模式的智能教学系统为适应不同学生的学习风格和学习要求，具有其它智能教学系统不可替代的优势，其关键问题之一是要解决教学规划和教学模式调度问题。提出了多模式智能教学系统的教学规划及教学模式调度的解决方案，以知识点关系图为基础提出了全局教学规划算法，根据对学生学习的评价和教学资源的相关特征为学生选择合适的教学模式并激活之。实验证明这种解决方案能取得令人满意的效果。     

空间飞行器有效载荷规划与调度软件平台

单一的算法已经无法解决大型复杂空间飞行器的有效载荷规划与调度问题,建立具有通用性和灵活性且适用于该问题的软件平台.分析国内外现有研究方法,算法比较和智能规划思想.总结有效载荷规划与调度问题共性,抽象为活动和约束,进一步使用CSOP模型对其进行数学描述.利用智能规划思想建立了有效载荷规划与调度软件平台总体架构,详述各组成结构、功能以及实现方法,描述了高级目标如何转换为具体的约束和活动的流程,并分析了其核心智能规划的一般方法.初步的仿真结果表明,该平台设计方案基本满足设计要求.     

在轨运行卫星的智能规划调度算法

在轨卫星的智能规划可以归结为资源受限的实时规划和调度问题,由于此类问题的规模大,实时性要求强,通常的解法很难满足应用要求.本文针对该问题的特点,建立了问题的数学模型,包括知识表示、目标函数等.提出了三种启发式的规划算法,并对算法特点进行了比较分析,具体应用时,可以根据问题的不同特点选用相应的算法,从快速性和准确性两方面适应系统要求.最后本文通过一个算例,从统计特性角度分析了三种算法,验证了算法的正确性.     

多维动态规划在对地观测卫星调度中的应用

对地观测卫星调度问题是指如何利用有限卫星资源,在时间、空间等多约束条件下提高对地观测任务执行效率,是一个多约束条件下的目标满足问题.多维动态规划是针对多维约束任务将有限资源进行合理分配、高效调度的有效方法.它以缩短任务完成时间为目标,通过先求解一系列子问题,再处理子问题间关系求得问题最终解,避免了计算的复杂性,又满足了时效性要求.针对卫星对地观测任务约束变量多的特点,将多维动态规划应用到对地观测卫星调度问题中,是解决该问题在时效性要求条件下的有效方法,其可行性通过想定任务在文章中得到证明.     

基于Multi-agent的卫星计划调度系统智能机制

卫星自主运控技术是各个航天发达国家的研究热点,Agent技术是提高卫星天基自主运行能力和地基智能化运控的关键技术。在分析传统的卫星计划调度系统的基础上,研究了基于Multi-agent的卫星计划调度系统智能实现机制所涉及到的一些关键问题,并据此设计了一个原型系统。     

基于AGVs路径规划的物流智能调度系统设计与实现

为了解决现有物流调度系统低效缓慢、容错率低的问题,设计了基于自动导引运输车(AGV,automated guided vechicle)和路径规划优化算法的物流智能调度系统;系统搭配了AGV的物流调度硬件,又结合了路径规划理论,开发了基于Petri网络的智能路径规划算法;通过算法性能对比得知,路径规划算法设计了最优调度路径,确保了较高的准确率和工作效率;系统测试结果显示,基于AGVs路径规划的物流智能调度系统能够在各种物流环境或者库房基地完成调度任务,很好地解决了物流企业在忙碌期的繁杂调度问题;基于AGVs路径规划的物流智能调度系统提高了物流调度的自动化程度,保证了物流调度和道路运输的效率,有效推动了商业模式和市场规范的发展。     

基于层级任务网络的卫星自主规划模型与算法

针对面向任务的卫星操作计划自动生成(即卫星的自主规划)问题,采用层级任务网络规划的任务分解思想,在分析卫星系统结构的基础上,建立了光学成像侦察卫星的规划模型,定义了2种常规任务的任务分解方法。根据模型的特点,开发了一个基于任务分解方法的导引式求解算法。通过一个实例进行了验证,结果表明模型和算法能有效解决卫星的自主规划问题。     

卫星成像规划调度系统中的可视化决策支持研究与实现

本文提出了一种成像卫星规划与调度的可视化决策支持方法。该方法基于多目标进化算法和地理信息系统技术,能够在考虑多目标准则、多约束的条件下对成像卫星的成像方案进行优化,并通过可视化技术进行成像方案的决策辅助,很好地解决了卫星规划调度优化方案制定的问题。     

Autonomy in production logistics: Identification, characterisation and application

Competitive enterprises have to react fast and flexible to an increasing dynamic environment. To achieve the ability to adapt on these new requirements autonomous cooperating logistic processes seem to be an appropriate method. In order to prove in which case autonomously controlled processes are more advantageous than conventionally managed processes, it is essential to specify what is exactly meant with autonomous control, how autonomous control does differ from conventional control and how the achievement of logistic objectives in autonomously controlled systems can be estimated and compared to the achievement of objectives in conventionally controlled systems. This paper introduces a general definition of autonomous control as well as a definition in the context of engineering science and its meaning in a logistics context. Based on this, a catalogue of criteria is developed to ensure the identification of autonomous cooperating processes in logistic systems and its distinction to conventionally controlled processes. To demonstrate this catalogue, its criteria and the concerning properties are explained by means of an exemplary shop-floor scenario.     

Autonomous navigation of an automated guided vehicle in industrial environments

The research presented in this paper approaches the issue of navigation using an automated guided vehicle (AGV) in industrial environments. The work describes the navigation system of a flexible AGV intended for operation in partially structured warehouses and with frequent changes in the floor plant layout. This is achieved by incorporating a high degree of on-board autonomy and by decreasing the amount of manual work required by the operator when establishing the a priori knowledge of the environment. The AGV's autonomy consists of the set of automatic tasks, such as planner, perception, path planning and path tracking, that the industrial vehicle must perform to accomplish the task required by the operator. The integration of these techniques has been tested in a real AGV working on an industrial warehouse environment.     

A feedback stabilization and collision avoidance scheme for multiple independent non-point agents

A navigation functions’ based methodology, established in our previous work for centralized multiple robot navigation, is extended to address the problem of decentralized navigation. In contrast to the centralized case, each agent plans its actions without knowing the destinations of the other agents. Asymptotic stability is guaranteed by the existence of a global Lyapunov function for the whole system, which is actually the sum of the separate navigation functions. The collision avoidance and global convergence properties are verified through simulations.     

基于运动微分约束的无人车辆纵横向协同规划算法的研究

为了满足在动态环境中快速行驶的要求,现有无人车辆普遍采用在传统规划系统的两层结构（路径规划-路径跟踪）之间增加局部规划的方法,通过在路径跟踪的同时进行避障来减少耗时的全局路径重规划. 本文针对这种三层结构规划系统存在的问题,提出基于运动微分约束的纵横向协同规划算法,在真实环境中实现速度不超过40km/h的无人驾驶. 根据车辆的实时运动状态,用高阶多项式模型在预瞄距离内对可行驶曲线进行建模,不仅使行驶过程中的转向平稳,而且在较高速时仍具有良好的路径跟踪能力. 由横向规划提供横向安全性的同时,在动力学约束的速度容许空间中进行纵向规划,实现平顺的加速与制动,并保证了纵向安全性和侧向稳定性. 该算法根据实时的局部环境自动决定纵横向期望运动参数,不需要人为设定行驶模式或调整参数. 采用该算法的无人驾驶平台在2011年和2012年智能车未来挑战赛的真实交通环境中,用统一的程序框架顺利完成全程的无人驾驶.     

基于Agent的自主探测器软件结构

深空探测的环境特点要求探测器具有一定的自主性,因而对探测器的软件结构也提出了新的要求,文章针对这一情况提出一种基于Agent的自主探测器软件结构,该结构包括两部分:短期反作用控制Agent和长期规划Agent,前者主要是处理一些紧急情况下的操作(如探测器故障时),后者是从全局考虑,对探测器的长期任务作出决策。文中软件结构以长期规划Agent为主,反作用控制Agent为辅,共同完成深空探测器的飞行任务。     

A new method for autonomous control of complex job shops – Integrating order release,sequencing and capacity control to meet due dates

Due to the development of Cyber-Physical Production Systems, autonomous control of manufacturing processes is of increasing significance. Particularly, these manufacturing control approaches have considerable potential in job shop manufacturing. However, research in this field tends to focus on subtasks of manufacturing control without considering the interdependencies. This article presents the autonomous production control method (APC), which integrates all control tasks – order release, sequencing and capacity control – to meet due dates. The APC is benchmarked with established method combinations using event-discrete simulation. The results demonstrate the potential of our method to meet due dates and emphasise the method’s relevance for practical applications.     

Behavioral task processing for cognitive robots using artificial emotions

This paper presents an artificial emotional-cognitive system-based autonomous robot control architecture for a four-wheel driven and four-wheel steered mobile robot. Discrete stochastic state-space mathematical model is considered for behavioral and emotional transition processes of the autonomous mobile robot in the dynamic realistic environment. The term of cognitive mechanism system which is composed from rule base and reinforcement self-learning algorithm explain all of the deliberative events such as learning, reasoning and memory (rule spaces) of the autonomous mobile robot. The artificial cognitive model of autonomous robot control architecture has a dynamic associative memory including behavioral transition rules which are able to be learned for achieving multi-objective robot tasks. Motivation module of architecture has been considered as behavioral gain effect generator for achieving multi-objective robot tasks. According to emotional and behavioral state transition probabilities, artificial emotions determine sequences of behaviors for long-term action planning. Also reinforcement self-learning and reasoning ability of artificial cognitive model and motivational gain effects of proposed architecture can be observed on the executing behavioral sequences during simulation. The posture and speed of the robot and the configurations, speeds and torques of the wheels and all deliberative and cognitive events can be observed from the simulation plant and virtual reality viewer. This study constitutes basis for the multi-goal robot tasks and artificial emotions and cognitive mechanism-based behavior generation experiments on a real mobile robot.     

航天器任务调度模型、算法与通用求解技术综述

针对航天器任务调度大规模、复杂化的新常态和灵活组网、快速响应的新要求, 综述了航天器任务调度模型、算法与通用求解技术的发展现状. 首先, 基于遥感卫星、中继通信卫星、导航卫星和航天测控等航天器任务, 从任务排序模型和时间窗口分配模型两个角度出发, 揭示了不同航天器任务调度模型的决策形式和共性特征, 阐明提升模型兼容性、适用性的必要性. 其次, 基于启发式算法、精确求解算法和元启发式算法, 探讨了航天器任务调度算法的适用模型与编码特色, 指明“算法−模型”解耦、算法深度融合的重要性. 在此基础上, 介绍了CPLEX、STK/Scheduler、Europa2和“高景一号”任务调度分系统等航天器任务调度通用求解技术的模型、算法与主要功能, 说明我国自主研发通用求解技术的必要性和新的应用思路. 最后, 指出了开发航天器任务调度统一化建模语言、打造算法库与测试集等未来航天器任务调度研究的新方向.