The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Control Strategies for Soft Robot Systems
Open accessAbstract
Soft robots have recently attracted increased attention because their characteristics of low‐cost fabrication, durability, and deformability make them uniquely suited for applications in bio‐integrated systems. Being fundamentally different from traditional rigid robots, soft robots exhibit properties of infinite degrees of freedom (DOF) and nonlinear materials properties that require innovations in control systems. With the rapid development of materials science, robotics, and artificial intelligence, the diversification of actuator mechanisms and algorithms has enabled a wide range of unique control strategies. This review summarizes the basics of actuator mechanisms and control strategies, including open‐loop control, closed‐loop control, and autonomous control, and discusses their implementation from diversified perspectives. Control strategies are evaluated based on their compatibility with materials sets, application goals, and implementation route. The emerging directions are forecasted from the perspectives of interfacing between controller and actuator, underactuated control strategies, and implementation of artificial intelligence (AI).
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Cites
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Cited by
Hegde, C., Su, J., Tan, J. M. R., He, K., Chen, X., & Magdassi, S. (2023) · ACS Nano · doi:10.1021/acsnano.3c04089 · Cited by 384
Passively addressed robotic morphing surface (PARMS) based on machine learning
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Metadata
- Authors
- Wang, J., & Chortos, A.
- Venue
- Advanced Intelligent Systems
- Publisher
- Wiley
- Published
- 2022-02-22
- Volume
- 4
- Issue
- 5
- ISSN
- 2640-4567 (ISSN-L)
- OpenAlex
- W4214644029
- Cited by
- 254
- References
- 22
- FWCI
- 13.63
- Type
- journal article
- Language
- en
- Open access
- gold
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