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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...
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| Veröffentlicht in: | Front Robot AI |
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| Hauptverfasser: | , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Frontiers Media S.A.
2021
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8138170/ https://ncbi.nlm.nih.gov/pubmed/34026857 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/frobt.2021.639102 |
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