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research article

A Survey on Soft Robot Adaptability: Implementations, Applications, and Prospects [Survey]

Chen, Zixi
•
Wu, Di
•
Guan, Qinghua  
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2025
IEEE Robotics and Automation Magazine

Soft robots, compared to rigid robots, possess inherent advantages, including higher degrees of freedom, compliance, and enhanced safety, which have contributed to their increasing application across various fields. Among these benefits, adaptability is particularly noteworthy. In this article, adaptability in soft robots is categorized into external and internal adaptability. External adaptability refers to the robot’s ability to adjust, either passively or actively, to variations in environments, object properties, geometries, and task dynamics. Internal adaptability refers to the robot’s ability to cope with internal variations, such as manufacturing tolerances or material aging, and to generalize control strategies across different robots. As the field of soft robotics continues to evolve, the significance of adaptability has become increasingly pronounced. In this review article, we summarize various approaches to enhancing the adaptability of soft robots, including design, sensing, and control strategies. Additionally, we assess the impact of adaptability on applications such as surgery, wearable devices, locomotion, and manipulation. We also discuss the limitations of soft robotics adaptability and prospective directions for future research. By analyzing adaptability through the lenses of implementation, application, and challenges, this article aims to provide a comprehensive understanding of this essential characteristic in soft robotics and its implications for diverse applications.

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Type
research article
DOI
10.1109/MRA.2025.3584346
Scopus ID

2-s2.0-105010709527

Author(s)
Chen, Zixi

Sant'Anna Scuola Universitaria Superiore Pisa

Wu, Di

Syddansk Universitet

Guan, Qinghua  

École Polytechnique Fédérale de Lausanne

Hardman, David

University of Cambridge

Renda, Federico

Khalifa University of Science and Technology

Hughes, Josie  

École Polytechnique Fédérale de Lausanne

Thuruthel, Thomas George

UCL Engineering

Santina, Cosimo Della

Department of Cognitive Robotics, TU Delft

Mazzolai, Barbara

Istituto Italiano di Tecnologia

Zhao, Huichan

Tsinghua University

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Date Issued

2025

Published in
IEEE Robotics and Automation Magazine
Start page

2

End page

14

Subjects

Soft robotics

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Robots

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Robot sensing systems

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Sensors

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Regulation

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Hardware

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Shape

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Heuristic algorithms

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Software algorithms

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Manufacturing

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CREATE-LAB  
Available on Infoscience
July 25, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/252478
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