Wang Xiaopeng, Wei Ruilai, Chen Zhongming, Pang Hao, Li Haotian, Yang Yang, Hua Qilin, Shen Guozhen
School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, 100081, China.
Adv Sci (Weinh). 2025 Aug;12(32):e06296. doi: 10.1002/advs.202506296. Epub 2025 Jun 29.
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.
软机器人技术以其固有的柔顺性、仿生适应性和安全的人机环境交互为特点,已成为下一代智能系统中的变革性范式。生物系统经过进化优化,在非结构化环境中展现出无与伦比的多功能性,这激发了具有节能重构和环境响应能力的软机器人的发展。本文通过多学科整合对智能软机器人技术进行了全面分析,涵盖了从仿生设计原理到先进功能实现的关键方面。系统地研究了四个相互关联领域的最新突破:1)通过创新结构配置提高驱动效率的仿生驱动机制;2)实现自适应形态和可调机械性能的可编程材料;3)用于制造复杂异质结构的多尺度制造技术;4)集成人工智能算法的闭环控制策略。在强调生物医学工程、环境探索和人机界面等新兴应用的同时,还讨论了诸如驱动效率、材料降解、制造限制、非线性控制复杂性以及实际条件下的传感不稳定性等挑战。此外,还确定了战略研究方向,以指导具有实体智能和自适应功能的下一代软机器人的发展。值得注意的是,通过整合材料科学、机械工程和计算智能方面的进展,软机器人技术有望重新定义智能机器在医疗保健、探索和人类增强等领域的边界。