Bioinspired Intelligent Soft Robotics: From Multidisciplinary Integration to Next-Generation Intelligence.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Published Date: Jun 29, 2025

Abstract

Soft robotics, distinguished by intrinsic compliance, biomimetic adaptability, and safe human-environment interaction, has emerged as a transformative paradigm in next-generation intelligent systems. Biological systems, refined through evolutionary optimization, exhibit unparalleled multifunctionality in unstructured environments, inspiring the development of soft robots with energy-efficient reconfiguration and environmental responsiveness. This review presents a comprehensive analysis of intelligent soft robotics via multidisciplinary integration, covering key aspects from bioinspired design principles to advanced functional implementation. Recent breakthroughs across four interconnected domains are systematically examined: 1) biomimetic actuation mechanisms that enhance actuation efficiency through innovative structural configurations; 2) programmable materials enabling adaptive morphology and tunable mechanical properties; 3) multiscale manufacturing techniques for fabricating complex heterogeneous structures; and 4) closed-loop control strategies integrating artificial intelligence algorithms. While highlighting emerging applications in biomedical engineering, environmental exploration, and human-machine interfaces, challenges such as actuation efficiency, material degradation, manufacturing limitations, nonlinear-control complexity, and sensing instability under real-world conditions are discussed. Furthermore, strategic research directions are identified to guide the development of next-generation soft robots endowed with embodied intelligence and adaptive functionalities. Notably, by synergizing advances in materials science, mechanical engineering, and computational intelligence, soft robotics is poised to redefine the boundaries of intelligent machines across healthcare, exploration, and human augmentation.

Authors

  • Xiaopeng Wang
    Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou 215009, China.
  • Ruilai Wei
    Center on Nanoenergy Research, School of Physical Science and Technology, Guangxi University, Nanning, Guangxi 530004, P. R. China.
  • Zhongming Chen
    LifeBridge Health, Sinai Hospital of Baltimore, Rubin Institute for Advanced Orthopedics, Baltimore, Maryland.
  • Hao Pang
    School of Software, Beijing University of Posts and Telecommunications, Beijing, China.
  • Haotian Li
    Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, China.
  • Yang Yang
    Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
  • Qilin Hua
    CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China. huaqilin@binn.cas.cn.
  • Guozhen Shen
    School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, 100081, China.

Keywords

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