A hybrid architecture for robot navigation

In the context of the approach to intelligent autonomous systems based on the subsumption architectural concept, the authors describe a hybrid model of the navigation skill, to be considered as one of the many skills or behaviours that allow an autonomous agent to survive in an unknown/hostile envir...

Full description

Saved in:
Bibliographic Details
Published inInternational Joint Conference on Neural Networks, Nagoya, 1993 Vol. 2; pp. 1875 - 1878 vol.2
Main Authors Morasso, P., Vercelli, G., Zaccaria, R.
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 1993
Subjects
Algorithm design and analysis
Computer architecture
Context modeling
Hybrid intelligent systems
Intelligent robots
Mobile robots
Motion estimation
Navigation
Neurons
Self organizing feature maps
Online AccessGet full text

Cover

More Information
Summary:In the context of the approach to intelligent autonomous systems based on the subsumption architectural concept, the authors describe a hybrid model of the navigation skill, to be considered as one of the many skills or behaviours that allow an autonomous agent to survive in an unknown/hostile environment. The hybrid navigation behaviour consists of three main functions that operate in parallel on the same set of input/output data: (i) WRA (wild rover algorithm), (ii) SON (self-organized navigator), (iii) SEA (symbolic environment analysis). The term "hybrid" here refers to the cooperation between a logics-based representation formalism and a neural model. Starting from rough sensorial data given by WRA, the knowledge about the explored environment of a mobile robot can be incrementally organized by means the self-organizing maps (SON) and the set of heuristic rules (SEA).
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISBN:0780314212
9780780314214
DOI:10.1109/IJCNN.1993.717021