Control of Hexapod with Static-stable Walking Using Artificial Intelligence

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RIV/68407700:21460/16:00312085

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Control of Hexapod with Static-stable Walking Using Artificial Intelligence

Popis výsledku v původním jazyce

The objective of article is to describe a method for signal processing and decision making process of six-legged robots. The model of the decision making process allows the hexapod to static stable walk on terrain with obstacles. The decision making process is based on the evaluation of leg positions and the states of six-legged body to maintain static stability. Control system of six legged robot model is composed of three main parts: walking pattern classification algorithm, fuzzy expert system, neural network for decision-making. This approach combines stand-alone method to solve problems of acyclic walking and methods of AI to speed up the decisionmaking process. The composite structure enables to apply the control law of the locomotion with help of the parallel cooperating control and learning. The control system of the hexapod allows to adopt the hexapod on the specific conditions of terrain. The new technique was verified by models of hexapod and terrain with obstacles. The described hierarchical technique based on coordination of mentioned methods has not been tested before. The process of determining the gait phases selects the safe action for each state to overcome the obstacles in the terrain.

Název v anglickém jazyce

Control of Hexapod with Static-stable Walking Using Artificial Intelligence

Popis výsledku anglicky

The objective of article is to describe a method for signal processing and decision making process of six-legged robots. The model of the decision making process allows the hexapod to static stable walk on terrain with obstacles. The decision making process is based on the evaluation of leg positions and the states of six-legged body to maintain static stability. Control system of six legged robot model is composed of three main parts: walking pattern classification algorithm, fuzzy expert system, neural network for decision-making. This approach combines stand-alone method to solve problems of acyclic walking and methods of AI to speed up the decisionmaking process. The composite structure enables to apply the control law of the locomotion with help of the parallel cooperating control and learning. The control system of the hexapod allows to adopt the hexapod on the specific conditions of terrain. The new technique was verified by models of hexapod and terrain with obstacles. The described hierarchical technique based on coordination of mentioned methods has not been tested before. The process of determining the gait phases selects the safe action for each state to overcome the obstacles in the terrain.

Druh

D - Stať ve sborníku

CEP obor

KA - Vojenství

OECD FORD obor

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Projekt

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Návaznosti

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

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 2016 17th International Conference on Mechatronics - 17th Mechatronika (ME) 2016

ISBN

978-800105883-1

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

422-427

Název nakladatele

Czech technical university in Prague

Místo vydání

Praha

Místo konání akce

Praha

Datum konání akce

7. 12. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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