Adaptive estimation of friction parameters in multilink legged robots using the dynamic regressor extension and mixing

Adaptive estimation of friction parameters in multilink legged robots using the dynamic regressor extension and mixing

Nikita V. Mikhalkov
Postgraduate Student, ITMO University, 49-A, Kronverksky pr., Saint Petersburg, 197101, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID: 0000-0003-2723-1610

Anton A. Pyrkin
Doctor of Technical Sciences, Professor, ITMO University, Dean of Faculty of Control Systems and Robotics, Professor, Leading Research Scientist, 49-A, Kronverksky pr., Saint Petersburg, 197101, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID: 0000-0001-8806-4057

Received November 05, 2024

Abstract
This paper presents a method for adaptive friction parameter estimation in multilink legged robots. The relevance of this approach lies in the need to account for changes in joint friction parameters due to factors such as temperature fluctuations and wear. The proposed method, based on the dynamic regressor extension and mixing (DREM) technique and leveraging the specifics of legged motion, enables stable friction parameter estimation while avoiding computational complexities and the need for additional sensors, as seen in traditional methods. Simulation on a seven-link robotic system demonstrated convergence of the estimates to true values, even in the presence of noise and delays.

Key words
Adaptive parameter estimation, legged robots, friction parameter estimation.

Acknowledgements
Supported by the Ministry of Science and Higher Education of the Russian Federation (project no. FSER-2025-0002).

EDN
APWUMW

Bibliographic description
Mikhalkov, М.V. and Pyrkin, А.А. (2024), "Adaptive estimation of friction parameters in multilink legged robots using the dynamic regressor extension and mixing", Robotics and Technical Cybernetics, vol. 13, no. 1, pp. 18-25, EDN: APWUMW. (in Russian).

UDC identifier
539.62:007.52

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