Design Optimization of a Pneumatic Soft Robotic Actuator Using Model-Based Optimization and Deep Reinforcement Learning

We present two frameworks for design optimization of a multi-chamber pneumatic-driven soft actuator to optimize its mechanical performance. The design goal is to achieve maximal horizontal motion of the top surface of the actuator with a minimum effect on its vertical motion. The parametric shape an...

Descripción completa

Detalles Bibliográficos
Autores principales: Raeisinezhad, Mahsa, Pagliocca, Nicholas, Koohbor, Behrad, Trkov, Mitja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Robotics and AI
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138170/
https://www.ncbi.nlm.nih.gov/pubmed/34026857
http://dx.doi.org/10.3389/frobt.2021.639102

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138170/
https://www.ncbi.nlm.nih.gov/pubmed/34026857
http://dx.doi.org/10.3389/frobt.2021.639102

Ejemplares similares