Bridging Reinforcement Learning and Iterative Learning Control: Autonomous Motion Learning for Unknown, Nonlinear Dynamics

This work addresses the problem of reference tracking in autonomously learning robots with unknown, nonlinear dynamics. Existing solutions require model information or extensive parameter tuning, and have rarely been validated in real-world experiments. We propose a learning control scheme that lear...

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Detalles Bibliográficos
Autores principales: Meindl, Michael, Lehmann, Dustin, Seel, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Robotics and AI
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9315427/
https://www.ncbi.nlm.nih.gov/pubmed/35903721
http://dx.doi.org/10.3389/frobt.2022.793512

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9315427/
https://www.ncbi.nlm.nih.gov/pubmed/35903721
http://dx.doi.org/10.3389/frobt.2022.793512

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