Increasing the payload capacity of soft robot arms by localized stiffening.


Journal

Science robotics
ISSN: 2470-9476
Titre abrégé: Sci Robot
Pays: United States
ID NLM: 101733136

Informations de publication

Date de publication:
30 Aug 2023
Historique:
medline: 30 8 2023
pubmed: 30 8 2023
entrez: 30 8 2023
Statut: ppublish

Résumé

Soft robot arms offer safety and adaptability due to their passive compliance, but this compliance typically limits their payload capacity and prevents them from performing many tasks. This paper presents a model-based design approach to effectively increase the payload capacity of soft robot arms. The proposed approach uses localized body stiffening to decrease the compliance at the end effector without sacrificing the robot's range of motion. This approach is validated on both a simulated and a real soft robot arm, where experiments show that increasing the stiffness of localized regions of their bodies reduces the compliance at the end effector and increases the height to which the arm can lift a payload. By increasing the payload capacity of soft robot arms, this approach has the potential to improve their efficacy in a variety of tasks including object manipulation and exploration of cluttered environments.

Identifiants

pubmed: 37647385
doi: 10.1126/scirobotics.adf9001
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

eadf9001

Auteurs

Daniel Bruder (D)

John A. Paulson School of Engineering and Applied Sciences, Harvard University, 150 Western Ave., Boston, MA 02134, USA.

Moritz A Graule (MA)

John A. Paulson School of Engineering and Applied Sciences, Harvard University, 150 Western Ave., Boston, MA 02134, USA.

Clark B Teeple (CB)

John A. Paulson School of Engineering and Applied Sciences, Harvard University, 150 Western Ave., Boston, MA 02134, USA.

Robert J Wood (RJ)

John A. Paulson School of Engineering and Applied Sciences, Harvard University, 150 Western Ave., Boston, MA 02134, USA.

Classifications MeSH