Structured Multimaterial Fibers Enabling Intelligent Robots

S Shengshun Duan X Xingbei Wang (School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore) W Wenge Que (State Key Laboratory of Advanced Fiber Materials College of Materials Science and Engineering Donghua University Shanghai P. R. China) C Cheng Liu Z Zhiyuan Liu H Hailiang Wang (Department of Chemistry) W Wei Yan M Meifang Zhu

Abstract

ABSTRACT Traditional robots, defined by rigid and bulky architectures, perform poorly in soft, dynamic, or spatially constrained environments such as the human body, and are incompatible with flexible, large‐area systems like textiles. These limitations have accelerated the search for robotic paradigms that are smaller, softer, and more adaptive. Inspired by muscle fibers that convert biochemical energy into motion, fiber robots have emerged as a compelling solution that bridges microscale integration with macroscale intelligence. These fibers integrating heterogeneous material components respond to thermal, electrical, chemical, or optical stimuli with programmable actuation, and when integrated with distributed sensing and artificial intelligence (AI), they evolve into ultrathin, compliant, and intelligent systems. Such properties enable navigation in confined biological spaces and incorporation into comfortable fabrics for wearables, biomedical devices, and soft robotic skins. This work summarizes recent advances in actuation mechanisms, multimodal sensing, and system‐level integration of fiber robots enabled by structured multimaterial fibers, as well as applications ranging from artificial muscles to adaptive textile systems and implantable medicine. We further highlight the transformative role of AI in material discovery, actuator‐sensor co‐design, autonomous fabrication, and embodied intelligence, and outline key challenges and frontier application opportunities for fully autonomous intelligent fiber robots across scales, from inside the human body to the deep sea and deep space.

Article Details

Volume / Issue Vol. 38, Issue 26
Published May 01, 2026
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (8)

S

Shengshun Duan

X

Xingbei Wang

School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

W

Wenge Que

State Key Laboratory of Advanced Fiber Materials College of Materials Science and Engineering Donghua University Shanghai P. R. China

C

Cheng Liu

Z

Zhiyuan Liu

H

Hailiang Wang

Department of Chemistry

W

Wei Yan

M

Meifang Zhu