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  3. Autonomous Soft Robotics: Revolutionizing Motion With Intelligence And Flexibility.
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  3. Autonomous Soft Robotics: Revolutionizing Motion With Intelligence And Flexibility.

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Autonomous soft robotics: Revolutionizing motion with intelligence and flexibility.

Boyu Liu1, Lizhi Zhang1, Ben Wang2

  • 1School of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, PR China.

Advances in Colloid and Interface Science
|May 1, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

This review explores self-sustained motion in soft robots, inspired by nature. It categorizes mechanisms and behaviors, offering a framework for adaptive, autonomous robotic systems in diverse environments.

Keywords:
Intelligent structureSelf-sustaining movementSmart materialsSoft robotics

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Area of Science:

  • Robotics and Biomimetics
  • Materials Science
  • Nonlinear Dynamics

Background:

  • Nature exhibits highly efficient autonomous locomotion through cyclic motions (e.g., muscle actuation, insect flight).
  • Soft robotics aims to replicate this efficiency using compliant materials and self-regulation, reducing reliance on external control.
  • Understanding self-sustained motion is crucial for developing adaptive and autonomous soft robotic systems.

Purpose of the Study:

  • To review and categorize mechanisms enabling self-sustained motion in soft robots.
  • To classify observed motion behaviors and their underlying strategies.
  • To establish a framework correlating motion strategies with environmental features for designing adaptive soft robots.

Main Methods:

  • Categorization of soft robot self-sustained motion strategies into six types based on stimuli (thermal, light, photochemical, humidity, topological structure, negative feedback).
  • Classification of motion behaviors into five modes (oscillation, rolling/crawling, obstacle avoidance, spinning, nonlinear trajectory).
  • Comparative analysis of mechanisms regarding environmental adaptability, energy conversion, and locomotion performance.

    • Main Results:

    • A comprehensive framework mapping soft robot motion strategies to environmental features is established.
    • Six distinct stimulus-driven mechanisms and five emergent motion behaviors are identified and analyzed.
    • The framework aids in developing soft robotic systems tailored for specific environmental demands.

    Conclusions:

    • Significant challenges remain in achieving robust, long-term autonomous soft robot operation in unstructured environments.
    • Future research should focus on overcoming these challenges to enhance the practical applicability of autonomous soft robots.
    • The established framework provides a valuable resource for guiding future development in adaptive and autonomous soft robotics.