Bioinspired Intelligence for Soft Actuators: Learning, Control, and Embodied Design

Dear Colleagues,

Soft robotic systems increasingly depend on intelligent actuation, the tight coupling of compliant actuators, embedded sensing, and control and learning algorithms to achieve robust performance under nonlinearities such as hysteresis, drift, viscoelasticity, and environmental disturbances. Inspired by biological intelligence, including reflex loops, central pattern generators, adaptive muscle recruitment, and morphological computation, recent advances in machine learning and bioinspired algorithms provide powerful tools to model, optimize, and control soft actuators and actuator-driven robots with improved autonomy and reliability.

This Special Issue focuses on bioinspired and AI-enabled methods that directly advance soft actuation technologies, including data-driven modeling, self-sensing actuation, adaptive and learning-based control, design optimization, and sim-to-real transfer. We particularly welcome contributions that provide reproducible experimental validation, benchmarking protocols, or open datasets and models, enabling the community to compare and build upon prior results.

Submissions may report component-level innovations in actuators, self-sensing structures, drive electronics, and control architectures, as well as system demonstrations where the primary novelty is an actuator-centric intelligence pipeline linking sensing, modeling, and closed-loop control. We encourage studies that report clear performance metrics, rigorous comparisons to baseline methods, and sufficient implementation details to support reproducibility.

Dr. Yanhong Peng
Dr. Fangchao Hu
Dr. Yi Li
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Actuators is an international peer-reviewed open access monthly journal published by MDPI.

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