SIA OpenIR  > 空间自动化技术研究室
面向任务的空间机器人控制结构研究
Alternative TitleA Research on Task-Oriented Space Robot Control Architecture
余岑1,2
Department空间自动化技术研究室
Thesis Advisor周维佳
ClassificationTP242
Keyword面向任务 空间机器人 多机器人控制结构 多agent系统 本体论模型
Call NumberTP242/Y74/2014
Pages155页
Degree Discipline模式识别与智能系统
Degree Name博士
2014-06-03
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Abstract文对比分析了目前的空间机器人控制结构和其它一些面向任务的多机器人控制结构的研究贡献和不足,提出一种采用多agent系统理论形式化描述的控制结构,目的是使得控制结构可以根据用户的任务描述自动改变agent之间的关系完成任务,用户也可以通过与不同的agent进行人机交互获得不同分辨率的状态反馈并参与决策。规划问题分布在各个agent中,可以进行快速的求解满足容错性的要求。具体阐述如下: (1)将机器人、分布式传感器-执行器闭环、软件单元抽象为具有有限感知、决策和行为能力的agent,使用多agent系统理论中的社会机制设计一个面向任务的空间机器人控制结构。控制结构的社会机制分为两个部分:分层组织模型描述了控制结构在面向特定任务时agent之间的关系,agent之间的交互被限制在一个小范围内,适用于空间机器人通信带宽有限且有较大延时的应用背景;社会规范包括知识交互规范和任务交互规范,分别定义了agent交互的数据格式和内容。 (2)通过知识服务器和交互接口标准实现了知识交互规范。知识服务器采用共享的本体论模型定义agent通信使用到的词汇表和词汇的使用约束,并提供一致性推理服务来判断某个agent的内部知识表示是否与共享本体论模型一致。交互接口标准使用KIF(Knowledge Interchange Format)语言作为中间语言实现不同语言agent之间的格式转换,使用OKBC(Open Knowledge Base Connectivity)作为agent访问知识服务器的通信协议。 (3)基于SOAR(State, Operator and Result)的认知模型作为agent设计的理论基础,使得agent满足任务交互规范的要求。认知模型将agent的内部结构分为感知部分、工作内存、长期知识存储、认知处理、行为输出五个部分。提出了一个逻辑系统描述决策问题,通过这个逻辑系统对目标公式的证明过程可以获得针对该目标进行决策的产生式规则,便于agent设计过程中的检查和分析。开发了控制结构仿真验证的软件平台,可以对agent进行在线调试。 (4)设计了在线规划单元供agent调用实现对某些不能使用目标公式描述的复杂任务的规划问题求解,根据求解结果设定当前的目标。在线规划单元使用形式化语言NDDL(New Domain Description Language)描述任务、领域模型、资源和能力数据,以EUROPA(Extensible Universal Remote Operations Planning Architecture)平台提供的PSEngine作为搜索引擎。求解完成后的规划数据库中如果存在无缺陷的规划,将规划和保存历史信息的时态数据库对比确定agent当前的目标;如果不存在无缺陷规划,则向父节点反馈任务降额分析。 (5)通过一个应用案例来来说明本文的理论应用,着重分析了控制结构中将规划问题限制在单个agent范围内的优势,加入一定的启发式搜索策略后可以进一步缩短求解时间。最后与其它多机器人控制结构的研究对比分析,指出了本文提出的面向任务的空间机器人控制结构的特点和贡献。
Other AbstractThis research compares and analyses the Contributions and limitations of recent space robot control architecture and task-oriented multi-robot control architecture, presents a control architecture formally described by multi-agent system theory. The control architecture automatically change the relationships between agents according to the task description from user. User can interact with different agent to get feedbacks and make decisions of different resolution. Planning problem is distributed in several agents, so the problem solving will be quickly to meet the requirement of fault-tolerance. Detailed descriptions are as follows: (1) Firstly, it abstracts robots, the distributed closed-loop of sensor-actuator, software unit as agents; based on the abstraction, it then uses social institution of multi-agent system theory to design a task-oriented space robot control architecture; it divides social institution into two parts: a hierarchical organization model describes the task-oriented relationships between agents in the architecture, within the organization model interactions between agents are limited in a small scope to adapt to the application background of limited communication bandwidth and large-time delay; social norms compose of knowledge interaction norm which defines the data format and task interaction norm which defines the data content. (2) Secondly, it achieves knowledge interaction norm with a knowledge servicer and a interface criterion: the knowledge servicer manages a shared ontology which defines the vocabulary and constraints in communication, and provides consistency reasoning service to decide the knowledge representation of an agent is consistent with the shared ontology; the interface criterion uses KIF(Knowledge Interchange Format) as intermediate language to translate formats between different languages, and uses OKBC(Open Knowledge Base Connectivity) as protocol to enable agents access the knowledge servicer. (3) Thirdly, it achieves task interaction norm with a cognitive model based on SOAR(State, Operator and Result) as the theoretical basis for agent design, the cognitive model divides the internal structure of agent into five components: perception, working memory, long-term knowledge memory, cognitive processing and behavior output; it presents a logic system for decision-making, through the proofs for a target formula, a set of production rules will be generated for checking and analyzing the design of an agent; it then develops a platform by which developer can online debug agents for simulation and verification of control architecture. (4) It presents a online planning unit which is called by agent to describe and plan complex task that cannot be represented by target formula. The online planning unit describes task, domain model, resource and capability by NDDL(New Domain Description Language) and uses PSEngine which is provided by EUROPA(Extensible Universal Remote Operations Planning Architecture) as problem solving engine. If there is a plan in the plan database with no flaw, then agent compares the plan with temporal database which maintains a execution history to set current target, else then agent feed task compromise analysis to parent node. (5)Finally, it applies the control architecture to a space robot system and emphatically analyzes the advantage that planning problems are restrict within single agent; it indicates that problem solving will be more quickly introducing some heuristics strategy; it shows unique features and contributions by comparing itself with others task-oriented multi-robot control architectures.
Language中文
Contribution Rank1
Document Type学位论文
Identifierhttp://ir.sia.cn/handle/173321/14816
Collection空间自动化技术研究室
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院大学
Recommended Citation
GB/T 7714
余岑. 面向任务的空间机器人控制结构研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2014.
Files in This Item:
File Name/Size DocType Version Access License
面向任务的空间机器人控制结构研究.pdf(3084KB) 开放获取CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[余岑]'s Articles
Baidu academic
Similar articles in Baidu academic
[余岑]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[余岑]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.