The impact of external conditions on quadruped robot behavior: modeling using fuzzy logic and machine learning

• Autorzy: Krzykowska-Piotrowska Karolina , Piotrowski Marek , Rosiński Adam , Paś Jacek , Nistor Sorin , Sibilska-Mroziewicz Anna , Janusz Marcin , Kasprzyk Zbigniew

Identyfikatory

DOI

10.5604/01.3001.0055.0629

Warianty tytułu

PL

Wpływ warunków zewnętrznych na zachowanie robota czworonożnego: modelowanie z wykorzystaniem logiki rozmytej i uczenia maszynowego

• Języki publikacji: EN

Abstrakty

EN

This article presents research on modeling the behavior of quadruped robots, specifically Spot from Boston Dynamics, under various external conditions using fuzzy logic and machine learning. A two-stage fuzzy inference model was developed to analyze the impact of environmental factors (temperature, precipitation, visibility) and operational factors (route duration, population density) on navigation disruptions and the probability of failure. Advanced machine learning algorithms, such as Gaussian Process Regression (GPR) and neural networks, were used for precise prediction of navigation failures. The proposed model, developed using MATLAB tools, represents a significant advancement in improving navigation precision and operational efficiency of assistive robots in complex environments. These findings hold promise for applications aiding individuals with special needs.

PL

W tym artykule przedstawiono badania nad modelowaniem i przewidywaniem zachowania robotów czworonożnych przy użyciu logiki rozmytej i uczenia maszynowego, w szczególności robota Spot firmy Boston Dynamics, w różnych warunkach zewnętrznych. Opracowano dwuetapowy model wnioskowania rozmytego w celu analizy wpływu czynników środowiskowych (temperatura, opady, widoczność) i czynników operacyjnych (czas trwania trasy, gęstość zaludnienia) na zakłócenia nawigacji i prawdopodobieństwo awarii. Do precyzyjnego przewidywania awarii nawigacji wykorzystano zaawansowane algorytmy uczenia maszynowego, takie jak regresja procesów gaussowskich (GPR) i sieci neuronowe. Proponowany model, opracowany przy użyciu narzędzi MATLAB, stanowi znaczący postęp w zakresie poprawy precyzji nawigacji i wydajności operacyjnej robotów wspomagających w złożonych środowiskach.

Słowa kluczowe

EN

fuzzy logic; machine learning; quadruped robot; navigation failure; external conditions

PL

logika rozmyta; uczenie maszynowe; robot czworonożny; awaria nawigacji; warunki zewnętrzne

• Wydawca: Wydawnictwo Instytutu Technicznego Wojsk Lotniczych
• Czasopismo: Journal of KONBiN
• Rocznik: 2025
• Tom: Vol. 55, iss.1
• Strony: 155--167
• Opis fizyczny: Bibliogr. 25 poz., rys., tab.

Twórcy

autor

Krzykowska-Piotrowska Karolina

• Warsaw University of Technology (Politechnika Warszawska), Poland

• https://orcid.org/0000-0002-1253-3125

autor

Piotrowski Marek

• University of Warmia and Mazury in Olsztyn (Uniwersytet Warmińsko-Mazurski w Olsztynie), Poland

• https://orcid.org/0000-0002-1977-5995

autor

Rosiński Adam

• Warsaw University of Technology (Politechnika Warszawska), Poland

• https://orcid.org/0000-0002-1776-9540

autor

Paś Jacek

• Military University of Technology (Wojskowa Akademia Techniczna), Poland

• https://orcid.org/0000-0001-8900-1445

autor

Nistor Sorin

• University of Oradea, Romania

• https://orcid.org/0000-0001-8630-0087

autor

Sibilska-Mroziewicz Anna

• Warsaw University of Technology (Politechnika Warszawska), Poland

• https://orcid.org/0000-0002-5989-9562

autor

Janusz Marcin

• University of Warmia and Mazury in Olsztyn (Uniwersytet Warmińsko-Mazurski w Olsztynie), Poland

• https://orcid.org/0000-0002-4652-6898

autor

Kasprzyk Zbigniew

• Warsaw University of Technology (Politechnika Warszawska), Poland

• https://orcid.org/0000-0002-1745-1946

Bibliografia

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