Self-Organizing Map for the Multi-Goal Path Planning with Polygonal Goals
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00181909" target="_blank" >RIV/68407700:21230/11:00181909 - isvavai.cz</a>
Result on the web
<a href="http://www.springerlink.com/content/05570w0vnq831416/" target="_blank" >http://www.springerlink.com/content/05570w0vnq831416/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-21735-7_11" target="_blank" >10.1007/978-3-642-21735-7_11</a>
Alternative languages
Result language
angličtina
Original language name
Self-Organizing Map for the Multi-Goal Path Planning with Polygonal Goals
Original language description
This paper presents a self-organizing map approach for the multi-goal path planning problem with polygonal goals. The problem is to find a shortest closed collision free path for a mobile robot operating in a planar environment represented by a polygonalmap W. The requested path has to visit a given set of areas where the robot takes measurements in order to find an object of interest. Neurons' weights are considered as points in W and the solution is found as approximate shortest paths connecting thepoints (weights). The proposed self-organizing map has less number of parameters than a previous approach based on the self-organizing map for the traveling salesman problem. Moreover, the proposed algorithm provides better solutions within less computational time for problems with high number of polygonal goals.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/2C06005" target="_blank" >2C06005: A System for robotic e-learning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of Artificial Neural Networks and Machine Learning
ISBN
978-3-642-21734-0
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
85-92
Publisher name
Springer
Place of publication
Heidelberg
Event location
Espoo
Event date
Jun 14, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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