Design optimization of soft pneumatic actuators using genetic algorithms

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autorschaft

Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des Sammelwerks2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten393-400
Seitenumfang8
ISBN (elektronisch)9781538637418
ISBN (Print)978-1-5386-3743-2
PublikationsstatusVeröffentlicht - 23 März 2018
Veranstaltung2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017 - Macau, China
Dauer: 5 Dez. 20178 Dez. 2017

Publikationsreihe

Name2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)

Abstract

Recent trends in bioinspired robotic systems are paving the way for robots to become part of our daily lives. Soft robots, which are widely recognized as the next generation of human-friendly robots, are such a trend. Soft robots are generally more adaptable, more flexible, and safer than their rigid-link counterparts. Research in soft robotics has produced a broad variety of interesting solutions for all sorts of applications ranging from medical engineering and rehabilitation over exploration to industrial handling. This diversity together with a general lack of experience in designing with soft materials has contributed to a design flow that is highly empirical in nature. For soft robots to become mass-producible in the near future, more general design and modeling methods are needed. In this article, we present a method for the design optimization of soft robot modules that effectively combines finite element modeling and gradient-free optimization. To demonstrate the feasibility of the approach, a soft pneumatic actuator is designed and optimized. Performance analysis of the optimization scheme shows the robustness of the solution in the given case.

ASJC Scopus Sachgebiete

Zitieren

Design optimization of soft pneumatic actuators using genetic algorithms. / Runge-Borchert, Gundula; Peters, Jan; Raatz, Annika.
2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017. Institute of Electrical and Electronics Engineers Inc., 2018. S. 393-400 (2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Runge-Borchert, G, Peters, J & Raatz, A 2018, Design optimization of soft pneumatic actuators using genetic algorithms. in 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017. 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), Institute of Electrical and Electronics Engineers Inc., S. 393-400, 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017, Macau, China, 5 Dez. 2017. https://doi.org/10.15488/14443, https://doi.org/10.1109/robio.2017.8324449
Runge-Borchert, G., Peters, J., & Raatz, A. (2018). Design optimization of soft pneumatic actuators using genetic algorithms. In 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017 (S. 393-400). (2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.15488/14443, https://doi.org/10.1109/robio.2017.8324449
Runge-Borchert G, Peters J, Raatz A. Design optimization of soft pneumatic actuators using genetic algorithms. in 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017. Institute of Electrical and Electronics Engineers Inc. 2018. S. 393-400. (2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)). doi: 10.15488/14443, 10.1109/robio.2017.8324449
Runge-Borchert, Gundula ; Peters, Jan ; Raatz, Annika. / Design optimization of soft pneumatic actuators using genetic algorithms. 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017. Institute of Electrical and Electronics Engineers Inc., 2018. S. 393-400 (2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)).
Download
@inproceedings{776f1cf868e54dc1a356ac089c446ac9,
title = "Design optimization of soft pneumatic actuators using genetic algorithms",
abstract = "Recent trends in bioinspired robotic systems are paving the way for robots to become part of our daily lives. Soft robots, which are widely recognized as the next generation of human-friendly robots, are such a trend. Soft robots are generally more adaptable, more flexible, and safer than their rigid-link counterparts. Research in soft robotics has produced a broad variety of interesting solutions for all sorts of applications ranging from medical engineering and rehabilitation over exploration to industrial handling. This diversity together with a general lack of experience in designing with soft materials has contributed to a design flow that is highly empirical in nature. For soft robots to become mass-producible in the near future, more general design and modeling methods are needed. In this article, we present a method for the design optimization of soft robot modules that effectively combines finite element modeling and gradient-free optimization. To demonstrate the feasibility of the approach, a soft pneumatic actuator is designed and optimized. Performance analysis of the optimization scheme shows the robustness of the solution in the given case.",
author = "Gundula Runge-Borchert and Jan Peters and Annika Raatz",
year = "2018",
month = mar,
day = "23",
doi = "10.15488/14443",
language = "English",
isbn = "978-1-5386-3743-2",
series = "2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "393--400",
booktitle = "2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017",
address = "United States",
note = "2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017 ; Conference date: 05-12-2017 Through 08-12-2017",

}

Download

TY - GEN

T1 - Design optimization of soft pneumatic actuators using genetic algorithms

AU - Runge-Borchert, Gundula

AU - Peters, Jan

AU - Raatz, Annika

PY - 2018/3/23

Y1 - 2018/3/23

N2 - Recent trends in bioinspired robotic systems are paving the way for robots to become part of our daily lives. Soft robots, which are widely recognized as the next generation of human-friendly robots, are such a trend. Soft robots are generally more adaptable, more flexible, and safer than their rigid-link counterparts. Research in soft robotics has produced a broad variety of interesting solutions for all sorts of applications ranging from medical engineering and rehabilitation over exploration to industrial handling. This diversity together with a general lack of experience in designing with soft materials has contributed to a design flow that is highly empirical in nature. For soft robots to become mass-producible in the near future, more general design and modeling methods are needed. In this article, we present a method for the design optimization of soft robot modules that effectively combines finite element modeling and gradient-free optimization. To demonstrate the feasibility of the approach, a soft pneumatic actuator is designed and optimized. Performance analysis of the optimization scheme shows the robustness of the solution in the given case.

AB - Recent trends in bioinspired robotic systems are paving the way for robots to become part of our daily lives. Soft robots, which are widely recognized as the next generation of human-friendly robots, are such a trend. Soft robots are generally more adaptable, more flexible, and safer than their rigid-link counterparts. Research in soft robotics has produced a broad variety of interesting solutions for all sorts of applications ranging from medical engineering and rehabilitation over exploration to industrial handling. This diversity together with a general lack of experience in designing with soft materials has contributed to a design flow that is highly empirical in nature. For soft robots to become mass-producible in the near future, more general design and modeling methods are needed. In this article, we present a method for the design optimization of soft robot modules that effectively combines finite element modeling and gradient-free optimization. To demonstrate the feasibility of the approach, a soft pneumatic actuator is designed and optimized. Performance analysis of the optimization scheme shows the robustness of the solution in the given case.

UR - http://www.scopus.com/inward/record.url?scp=85049910736&partnerID=8YFLogxK

U2 - 10.15488/14443

DO - 10.15488/14443

M3 - Conference contribution

AN - SCOPUS:85049910736

SN - 978-1-5386-3743-2

T3 - 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)

SP - 393

EP - 400

BT - 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017

Y2 - 5 December 2017 through 8 December 2017

ER -

Von denselben Autoren