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Increasing the Payload Capacity of Soft Robot Arms by Localized StiffeningSoft 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.
Document ID
20250001131
Acquisition Source
2230 Support
Document Type
Accepted Manuscript (Version with final changes)
Authors
Daniel Bruder ORCID
(Harvard University Cambridge, United States)
Moritz A Graule ORCID
(Harvard University Cambridge, United States)
Clark B Teeple ORCID
(Harvard University Cambridge, United States)
Robert J Wood ORCID
(Harvard University Cambridge, United States)
Date Acquired
January 30, 2025
Publication Date
August 30, 2023
Publication Information
Publication: Science Robotics
Publisher: American Association For The Advancement of Science
Volume: 8
Issue: 81
Issue Publication Date: August 1, 2023
e-ISSN: 2470-9476
Subject Category
Cybernetics, Artificial Intelligence and Robotics
Funding Number(s)
CONTRACT_GRANT: 80NSSC19K1076
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
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