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Learning adaptive reaching and pushing skills using contact information

In this paper, we propose a deep reinforcement learning-based framework that enables adaptive and continuous control of a robot to push unseen objects from random positions to the target position. Our approach takes into account contact information in the design of the reward function, resulting in...

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Detalles Bibliográficos
Autores principales: Wang, Shuaijun, Sun, Lining, Zha, Fusheng, Guo, Wei, Wang, Pengfei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536165/
https://www.ncbi.nlm.nih.gov/pubmed/37781411
http://dx.doi.org/10.3389/fnbot.2023.1271607