工业机器人控制系统的开放体系结构

本文分析研究了开放式机器人体系结构的研究进展，探讨了利用PC技术、现场总线（CAN）技术以及 多传感技术，研究开发开放的工业机器人控制系统的问题.最后介绍了我们具有自主版权的开放式AIASUN-06B工业机器人控制系统.􀁱     

基于人工情感的拟人机器人控制体系结构

简要概括了当前人工情感的应用,提出一种基于人工情感的拟人机器人控制体系结构,并给出了仿真示例．基于情感的控制结构具有混合分层的特点,情感状态影响到机器人的整个信息处理过程．这种结构不仅体现了机器人的个性化,同时增强了机器人在动态环境中的学习和自适应能力．     

A Flexible Control Architecture for Mobile Robots: An Application for a Walking Robot

To get the best features of both deliberative and reactive controllers, present mobile robot control architectures are designed to accommodate both types of controller. However, these architectures are still very rigidly structured thus deliberative modules are always assigned to the same role as a high-level planner or sequencer while low-level reactive modules are still the ones directly interacting with the robot environment. Furthermore, within these architectures communication and interface between modules are if not strongly established, they are very complex thus making them unsuitable for simple robotic systems. Our idea in this paper is to present a control architecture that is flexible in the sense that it can easily integrate both reactive and deliberative modules but not necessarily restricting the role of each type of controller. Communication between modules is through simple arbitration schemes while interface is by connecting a common communication line between modules and simple read and/or write access of data objects. On top of these features, the proposed control architecture is scalable and exhibits graceful degradation when some of the modules fail, similar to the present mobile robot architectures. Our idea has enabled our four-legged robot to walk autonomously in a structured uneven terrain.     

基于多Agent的移动机器人导航进化控制的体系结构

将进化控制与多Agent技术相结合,兼顾几种经典体系结构的优点,提出了一种基于多Agent的移动机器人导航进化控制的体系结构.该体系结构特别适合于网络环境下的机器人系统,能充分发挥进化控制隐含并行性的优点.最后,结合其所在研究所实验室的条件,设计出以该体系结构为基础机器人系统实现方案.     

基于混合结构的机器人Agent控制结构的研究

该文面向分布Agent多移动机器人系统,提出了一种适合于多移动机器人的机器人Agent分层式体系结构,包括状态监测层、决策规划层、协调控制层和行为控制层,其中状态监测层主要实现整个系统对外部环境的状态监测。决策规划层设定系统的全局目标和单个机器人的局部目标,合理快速地完成任务的分解和分配,实现机器人之间任务级之间的协作。协调控制层完成机器人之间的运动协调。行为控制器主要采用基于行为的方法实现具体的运动控制。该结构应用于RoboCup环境下的分布多机器人系统中,满足复杂的、动态的应用环境和系统要求。     

深海采矿机器人控制体系结构研究

针对深海采矿机器人控制这一难题,提出了基于嵌入式ARM控制器的硬件设计方法和基于多任务调用的集成体系结构软件设计思路.从硬件和软件两方面进行了讨论,硬件包括海上监控系统与海底信息采集/作业系统,引入了ARM等嵌入式控制器及CAN总线结构,海底采用声纳、视觉图像及各类定位传感器协同工作,采集海底作业信息,通过6 000 m光缆进行海底与海上通讯;软件则在采矿机器人任务合理分配的基础上,将控制系统软件结构设计分为执行层、控制层和规划层.该方法能使整个系统成为一个有机整体,有效地完成对采矿机器人的实时控制.     

Internet Control Architecture for Internet-Based Personal Robot

This paper proposes a novel direct internet control architecture for internet-based personal robot, which is insensitive to the inherent internet time delay. The personal robot can be controlled using a simulator provided at a local site. Since the internet time delay is affected by the number of nodes and the internet loads, it is variable and unpredictable so that a large internet delay makes some control inputs distorted. The proposed control architecture guarantees that the personal robot can avoid obstacles and reduce the path error and the time difference between a virtual robot at the local site and a real robot at the remote site. This architecture is extended for an uncertain environment. Simulations and experimental results in the real internet environment demonstrate the effectiveness and applicability of the proposed internet control architecture.     

Markov Chain Approach to Probabilistic Guidance for Swarms of Autonomous Agents

Motivated by biological swarms occurring in nature, there is recent interest in developing swarms comprised completely of engineered agents. The main challenge for developing swarm guidance laws compared to earlier formation flying and multi‐vehicle coordination approaches is the sheer number of agents involved. While formation flying applications might involve up to 10 to 20 agents, swarms are desired to contain hundreds to many thousands of agents. In order to deal with the sheer size, the present paper makes a break with past deterministic methods, and considers the swarm as a statistical ensemble for which guidance can be performed from a probabilistic point of view. The probability‐based approach takes advantage of the law of large numbers, and leads to computationally tractable and implementable swarm guidance laws. Agents following a probabilistic guidance algorithm make statistically independent probabilistic decisions based solely on their own state, which ultimately guides the swarm to the desired density distribution in the configuration space. Two different synthesis methods are introduced for designing probabilistic guidance laws. The first is based on the Metropolis‐Hastings (M‐H) algorithm, and the second is based on using linear matrix inequalities (LMIs). The M‐H approach ensures convergent swarm behavior subject to enforced desired motion constraints, while the LMI approach additionally ensures exponential convergence with a prescribed decay rate, and allows minimization of a cost function that reflects fuel expenditure. In addition, both algorithms endow the swarm with the property of self‐repair, and the capability to strictly enforce zero‐probability keep‐out regions. This last property requires a slight generalization of the Perron‐Frobenius theory, and can be very useful in swarm applications that contain regions where no agents are allowed to go. Simulation examples are given to illustrate the methods and demonstrate desired properties of the guided swarm.     

Sensor-Based Control Architecture for a Car-Like Vehicle

This paper presents a control architecture endowing a car-like vehicle moving in a dynamic and partially known environment with autonomous motion capabilities. Like most recent control architectures for autonomous robot systems, it combines three functional components: a set of basic real-time skills, a reactive execution mechanism and a decision module. The main novelty of the architecture proposed lies in the introduction of a fourth component akin to a meta-level of skills: the sensor-based manoeuvers, i.e., general templates that encode high-level expert human knowledge and heuristics about how a specific motion task is to be performed. The concept of sensor-based manoeuvers permit to reduce the planning effort required to address a given motion task, thus improving the overall response-time of the system, while retaining the good properties of a skill-based architecture, i.e., robustness, flexibility and reactivity. The paper focuses on the trajectory planning function (which is an important part of the decision module) and two types of sensor-based manoeuvers, trajectory following and parallel parking, that have been implemented and successfully tested on a real automatic car-like vehicle placed in different situations.     

一种基于核设计的SOC测试控制体系结构

随着集成电路复杂性的提高和SOC系统的出现,电路测试的难度也在不断增大,测试问题已经成为SOC设汁的瓶颈。在研究了现存的测试控制结构后提出了基于核设计的SOC测试控制结构,它以边界扫描控制体系为基础,融合多种测试控制方法,支持不同类型的IP核进行测试。从而解决了SOC测试中控制部分的一些问题。     

一种混合结构的移动机器人导航控制策略

研究了未知环境下移动机器人实时的导航控制问题.采用分布式系统将反射式行为、反应式行为与慎思规划相结合,设计了移动机器人导航控制策略.根据激光雷达传感器信息设计了基于栅格的实时避障算法和解锁策略.通过慎思规划解决了复杂环境下的局部势能陷阱问题.通过自行研制的移动机器人IMR01的实验验证了导航策略的有效性.     

An Improved Production Activity Control Architecture for Shop Floor Control

This paper presents a further improved Production Activity Control Architecture to deal with the complexity of information by creating Sub-Producers and Sub-Movers which will not only give a better control at workstation level but also reduce load on the Dispatcher. It also makes an analysis of the basic and improved PAC (Production Activity Control) Architecture in the Control System for Integrated Manufacturing. The PAC Architecture and the improvement will further enhance the flexibility and adaptability of the architecture in the ever changing environment of the Shop Floor Control (SFC) Systems.     

HALVM:一个大型分层视频组播层次化自适应体系

针对端点自适应方法和基于静态配置代理的应用自适应方法无法满足大型视频组播扩展性、动态性和复杂性要求这一难点问题,提出了一个基于自组织代理的视频组播层次化自适应体系HALVM.该体系综合了代理的动态自组织协议和可伸缩性视频转换编码技术,将复杂的大型视频组播应用系统的动态自适应问题分解为层次化的小型视频组播应用子系统,由发送端、接收端和层次化代理分布完成自适应功能,是一个扩展性能好、管理与控制效率高的自适应解决方案.     

微装配机器人的控制软件设计

针对亚毫米级微型零件的装配精度和效率偏低的问题,构建了21自由度微装配机器人控制系统。首先简要介绍了其控制系统的硬件组成。接着将系统控制软件分解成相应的功能模块,并由这些软件模块组成二个控制阶段,以完成整个微装配过程。提出了一种通用的基于.NET框架的＂四层架构＂设计模式,简化了各软件模块的编写工作,重点讨论了各层的功能及实现细节。最后,成功地应用了所提出的设计方案构建了微装配系统,结果表明该控制系统极大的改善了装配精度和装配效率,能够满足微装配作业的要求。     

基于Server Push技术的机器人远程控制方法研究

提出了一种基于Server Push技术(服务器推技术)实现的机器人远程控制方法,并利用该方法建立了一种新型的开放的基于Internet的机器人远程控制系统模型.该模型实现了实时的远程数据采集及高速的控制信号响应,更适合进行在线实时机器人远程控制.基于该系统,完成了以六自由度关节机器人为对象的远程控制试验,试验表明该模型系统在信号采集的实时性、控制指令响应时间等系统参数均优于传统系统.     

移动机器人的可重构控制系统

针对未知环境下如何提高移动机器人导航控制系统的柔性和鲁棒性,分析了复杂控制系统（Complex Control System）的体系结构,以异构多Agent系统理论为基础,提出了一种可在多个层次上动态重构的控制系统设计方案,有效地增强了移动机器人的适应能力,为实现控制系统跟随任务和环境变化而动态配置提供了一条可行的途径。设计方案在移动机器人MORCS-I上得到了初步的技术验证,部分实验数据展示了重构控制的实际效果,所具有的通用性表明其亦适合应用于其他类型的复杂控制系统。     

自主移动机器人混合式体系结构的设计与实现

针对以往自主移动机器人体系结构在实时处理方面的不足,提出了一种基于多智能体的混合式体系结构,统一规划了机器人系统的软硬件结构,在该体系结构中设计并实现了协调Agent和推理Agent两种智能体,针对紧急事件进行了更实时的Agent实现,有效的提高的自主移动机器人在突发事件时的实时性,提出了使用多样化的信息组织形式,增强了系统的自适应能力和易扩展性。本文的实验结果表明在紧急状态下,系统的反应时间有效缩短,增加了系统的智能性和实时性。     

MRCS中机器人控制体系框架结构

针对机器人协作系统中任务协作和运动协调的两个过程,考虑机器人自主性和协作性的要求,设计一种分层的机器人控制体系结构,其中包括协作规划层、协调规划层和行为控制层,该控制体系采用分层、模块式结构,有利于功能的扩充。     

某无人直升机的软件架构设计

针对机载软件研发难度日益增加的问题,结合机载软件的特点,分析了软件架构的理论知识,给出了软件架构应用于机载软件的视图表示法,设计了某无人机飞控系统软件的功能逻辑架构和数据运行架构,提出了机载软件架构验证的一种方法.试验表明,软件架构技术运用于机载软件的开发,能有效地改善软件质量,实现机载软件的鲁棒性要求.     

航天飞控软件的二维容错体系结构设计

介绍航天飞控软件系统的主要功能及其常规体系结构。设计开发航天飞控软件系统的一个二维容错体系结构。版本维A包括所有应用软件功能的完整功能进程,版本维B仅包括部分关键软件功能进程的二版本设计与实现,其中有原功能进程的全功能冗余设计,以及原功能进程的降级冗余设计。版本维主要实现进程级程序的容错功能。关键等级维实现的是不同关键等级进程之间的数据容错。如果数据从较高关键等级进程流向较低或相同关键等级进程,则数据交换可以直接进行,如果数据从较低关键等级进程流向较高关键等级进程,则必须由容错处理进程经过容错处理,才能流向目的进程。