CLC number: TP311.5
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Received: 2005-09-26
Revision Accepted: 2006-05-22
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LIANG Hai-hua, ZHU Miao-liang. Applying the model driven generative domain engineering method to develop self-organizing architectural solutions for mobile robot[J]. Journal of Zhejiang University Science A, 2006, 7(10): 1652-1661.
@article{title="Applying the model driven generative domain engineering method to develop self-organizing architectural solutions for mobile robot",
author="LIANG Hai-hua, ZHU Miao-liang",
journal="Journal of Zhejiang University Science A",
volume="7",
number="10",
pages="1652-1661",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A1652"
}
%0 Journal Article
%T Applying the model driven generative domain engineering method to develop self-organizing architectural solutions for mobile robot
%A LIANG Hai-hua
%A ZHU Miao-liang
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 10
%P 1652-1661
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A1652
TY - JOUR
T1 - Applying the model driven generative domain engineering method to develop self-organizing architectural solutions for mobile robot
A1 - LIANG Hai-hua
A1 - ZHU Miao-liang
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 10
SP - 1652
EP - 1661
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A1652
Abstract: Model driven generative domain engineering (MDGDE) is a domain engineering method aiming to develop optimized, reusable architectures, components and aspects for application engineering. Agents are regarded in MDGDE as special objects having more autonomy, and taking more initiative. Design of the agent involves three levels of activities: logical analysis and design, physical analysis, physical design. This classification corresponds to domain analysis and design, application analysis, and application design. Agent is an important analysis and design tool for MDGDE because it facilitates development of complex distributed system—the mobile robot. According to MDGDE, we designed a distributed communication middleware and a set of event-driven agents, which enables the robot to initiate actions adaptively to the dynamical changes in the environment. This paper describes our approach as well as its motivations and our practice.
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