超材料
适应性
转化式学习
机器人学
机器人
人工智能
工程类
计算机科学
桥(图论)
系统工程
人机交互
计算
作者
Xiaoyang Zheng,Yuhao Jiang,Mustafa Mete,Jingjing Li,Ikumu Watanabe,Takayuki Yamada,Jamie Paik
出处
期刊:Science robotics
[American Association for the Advancement of Science]
日期:2025-11-19
卷期号:10 (108)
标识
DOI:10.1126/scirobotics.adx1519
摘要
Mechanical metamaterials with customized microstructures are increasingly shaping robotic design and functionality, enabling the integration of sensing, actuation, control, and computation within the robot body. This Review outlines how metamaterial design principles—mechanics-inspired architectures, shape-reconfigurable structures, and material-driven functionality—enhance adaptability and distributed intelligence in robotics. We also discuss how artificial intelligence supports metamaterial robotics in design, modeling, and control, advancing systems with complex sensory feedback, learning capability, and adaptive physical interactions. This Review aims to inspire the community to explore the transformative potential of metamaterial robotics, fostering innovations that bridge the gap between materials engineering and intelligent robotics.
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