Incremental Traversability Assessment Learning Using Growing Neural Gas Algorithm
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00332831" target="_blank" >RIV/68407700:21230/19:00332831 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-19642-4_17" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-19642-4_17</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-19642-4_17" target="_blank" >10.1007/978-3-030-19642-4_17</a>
Alternative languages
Result language
angličtina
Original language name
Incremental Traversability Assessment Learning Using Growing Neural Gas Algorithm
Original language description
In this paper, we report early results on the deployment of the growing neural gas algorithm in online incremental learning of traversability assessment with a multi-legged walking robot. The addressed problem is to incrementally build a model of the robot experience with traversing the terrain that can be immediately utilized in the traversability cost assessment of seen but not yet visited areas. The main motivation of the studied deployment is to improve the performance of the autonomous mission by avoiding hard to traverse areas and support planning cost-efficient paths based on the continuously collected measurements characterizing the operational environment. We propose to employ the growing neural gas algorithm to incrementally build a model of the terrain characterization from exteroceptive features that are associated with the proprioceptive based estimation of the traversal cost. Based on the reported results, the proposed deployment provides competitive results to the existing approach based on the Incremental Gaussian Mixture Network.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization
ISBN
978-3-030-19641-7
ISSN
2194-5357
e-ISSN
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Number of pages
11
Pages from-to
166-176
Publisher name
Springer-VDI-Verlag
Place of publication
Düsseldorf
Event location
Barcelona
Event date
Jun 26, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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