Learning of a Rapid Prototyping Gait Library for a Quadruped Robot Using PD-ILC and Gaussian Processes

verfasst von

Manuel Weiss, Alexander Pawluchin, Thomas Seel, Ivo Boblan

Abstract

This work presents a body velocity control strategy for quadruped robots. Such control typically requires accurate kinematic and dynamic model knowledge, which is very challenging because of the multidimensional input-output system and the ground contact. Based on the inverse kinematics, we propose a Proportional-Derivative controlled robot that uses Iterative Learning Control to learn discrete body velocities, which are then generalized using the Gaussian Process Regression model for each joint separately. This controller design enables onboard control and learning in real-time without any simulation. This study illustrates the effectiveness of the proposed methodology over a range of velocities while emphasizing the minimal computational effort associated with its application in a practical context.

Organisationseinheit(en)

Institut für Mechatronische Systeme

Externe Organisation(en)

Berliner Hochschule für Technik (BHT)

Typ

Aufsatz in Konferenzband

Seiten

1213-1218

Anzahl der Seiten

6

Publikationsdatum

12.12.2024

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Artificial intelligence, Angewandte Informatik, Maschinelles Sehen und Mustererkennung, Steuerung und Optimierung

Elektronische Version(en)

https://doi.org/10.1109/ICARCV63323.2024.10821620 (Zugang: Geschlossen)