DocumentCode
1887502
Title
Flat-distributed network architecture (FDNet) for rescue robots - FDNet and its implementation
Author
Koji, Yosihisa ; Tadokoro, Satoshi ; Tokuda, Kenichi ; Pujol, Alain ; Toda, Takahumi ; Nobuhiro, Hideyuki ; Konyo, Masashi ; Takamori, Toshi
Author_Institution
Graduate Sch. of Sci. & Technol., Kobe Univ., Japan
Volume
1
fYear
2003
fDate
16-20 July 2003
Firstpage
235
Abstract
This paper deals with flat-distributed architecture for a rescue robot. This architecture provides the rescue robot with intelligence and flexibility. When this architecture is used, the robot system is described using networks. These networks are composed by data and processing agents. The data, referred to as "data", is a distributed component. The processing agents, referred to as "relation", are a distributed and parallel-processing component, which can refer to any existing data. We consider nodes that can formally connect to any other node, and relations that can be organized according to human\´s or any other network\´s pattern. This architecture was called "FDNet(Flat-Distributed Networks for Rescue System)". First, we describe the proposition of the architecture and its implementation for a robot. Then we report some experimental results. We provide this architecture for any intelligent rescue system.
Keywords
intelligent robots; mobile robots; parallel processing; FDNet; distributed component; flat-distributed network architecture; intelligent rescue system; parallel processing component; processing agents; rescue robots; robot flexibility; robot intelligence; Artificial intelligence; Computer architecture; Computer networks; Earthquakes; Educational institutions; Intelligent networks; Intelligent robots; Intelligent systems; Protocols; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence in Robotics and Automation, 2003. Proceedings. 2003 IEEE International Symposium on
Print_ISBN
0-7803-7866-0
Type
conf
DOI
10.1109/CIRA.2003.1222095
Filename
1222095
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