Cyclic Gait Learning Based on The Ant Colony Optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F15%3A00531653" target="_blank" >RIV/60162694:G43__/15:00531653 - isvavai.cz</a>

Výsledek na webu

<a href="http://vavtest.unob.cz/registr" target="_blank" >http://vavtest.unob.cz/registr</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/MILTECHS.2015.7153688" target="_blank" >10.1109/MILTECHS.2015.7153688</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cyclic Gait Learning Based on The Ant Colony Optimization

Popis výsledku v původním jazyce

This paper focuses on a development of a feasible gait pattern that can be used to control hexapod robot locomotion. The main objective of the presented paper is to develop suboptimal gait pattern to control walking robot. We are considering the construction of a six-legged walking robot (Hexapod). Hexapod robot locomotion should be controlled via controller. Controller should be capable of producing in open loops coordinated walking patterns. Gait generation is an optimization problem with constrains which can change during the time. Usage of Swarm Intelligence methods to obtain feasible solution of this complex optimization task is presented in this paper. Ant Colony Optimization methods were found as an appropriate learning algorithms to accomplishthis task. The control of a hexapod locomotion would be based on the model of artificial central pattern generators. This paper proposes to invent proper leg co-ordination control using a controller learned through the Ant Colony Optimiza

Název v anglickém jazyce

Cyclic Gait Learning Based on The Ant Colony Optimization

Popis výsledku anglicky

This paper focuses on a development of a feasible gait pattern that can be used to control hexapod robot locomotion. The main objective of the presented paper is to develop suboptimal gait pattern to control walking robot. We are considering the construction of a six-legged walking robot (Hexapod). Hexapod robot locomotion should be controlled via controller. Controller should be capable of producing in open loops coordinated walking patterns. Gait generation is an optimization problem with constrains which can change during the time. Usage of Swarm Intelligence methods to obtain feasible solution of this complex optimization task is presented in this paper. Ant Colony Optimization methods were found as an appropriate learning algorithms to accomplishthis task. The control of a hexapod locomotion would be based on the model of artificial central pattern generators. This paper proposes to invent proper leg co-ordination control using a controller learned through the Ant Colony Optimiza

Druh

D - Stať ve sborníku

CEP obor

KA - Vojenství

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

International Conference on Military Technology Proceeding, ICMT?15

ISBN

978-80-7231-976-3

ISSN

—

e-ISSN

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Počet stran výsledku

6

Strana od-do

653-658

Název nakladatele

University of Defence

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

1. 1. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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