Neural based obstacle avoidance with CPG controlled hexapod walking robot
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00315454" target="_blank" >RIV/68407700:21230/17:00315454 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/document/7965914/" target="_blank" >http://ieeexplore.ieee.org/document/7965914/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IJCNN.2017.7965914" target="_blank" >10.1109/IJCNN.2017.7965914</a>
Alternative languages
Result language
angličtina
Original language name
Neural based obstacle avoidance with CPG controlled hexapod walking robot
Original language description
In this work, we are proposing a collision avoidance system for a hexapod crawling robot based on the detection of intercepting objects using the Lobula giant movement detector (LGMD) connected directly to the locomotion control unit based on the Central pattern generator (CPG). We have designed and experimentally verified the proposed approach that maps the output of the LGMD directly on the locomotion control parameters of the CPG. The results of the experimental verification of the system with real mobile hexapod crawling robot support the feasibility of the proposed approach in collision avoidance scenarios.
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
<a href="/en/project/GJ15-09600Y" target="_blank" >GJ15-09600Y: Adaptive Informative Path Planning in Autonomous Data Collection in Dynamic Unstructured Environments</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
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 the International Joint Conference on Neural Networks
ISBN
978-1-5090-6181-5
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
650-656
Publisher name
IEEE Xplore
Place of publication
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Event location
Anchorage
Event date
May 14, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000426968700087