Recent advances in multifunctional soft robots: A materials–structures–systems co‐design perspective for synergistic integration

Abstract Soft robots, engineered from highly compliant materials, offer superior adaptability and safety in unstructured environments compared to their rigid counterparts. Recent advancements, fueled by bio‐inspiration and material programmability, have led to the rapid co‐evolution of their core modules: actuation, sensing, protection, energy, and communication. A fundamental challenge lies in integrating these diverse functionalities into a cohesive system without compromising soft robotic performance. Here we show that a rational “materials‐structures‐systems” co‐design strategy is pivotal for achieving this multifunctional integration. While existing reviews often compartmentalize advances by functional modules, this review synthesizes a unified framework demonstrating how such synergistic design enables tight coupling of functionalities, thereby overcoming the traditional trade‐offs between compliance and capability. This approach significantly expands the operational autonomy and environmental resilience of soft robots. The resulting framework not only advances soft robotics but also provides a cross‐disciplinary methodology for innovation in biomedical devices, environmental exploration, and human‐robot interaction, marking a transition from laboratory prototypes to deployable systems for real‐world challenges.

Authors

Institutions

Publication Details

Journal
FlexMat.
Published
2026-03-14
DOI
https://doi.org/10.1002/flm2.70053
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Recent advances in multifunctional soft robots: A materials–structures–systems co‐design perspective for synergistic integration

Zicao Peng, Qiulei Liu, Chong Sun, Haitao Yang
FlexMat.
Micro and Nano Robotics
article

Recent advances in multifunctional soft robots: A materials–structures–systems co‐design perspective for synergistic integration

Zicao Peng, Qiulei Liu, Chong Sun, Haitao Yang
article en

Abstract

Abstract Soft robots, engineered from highly compliant materials, offer superior adaptability and safety in unstructured environments compared to their rigid counterparts. Recent advancements, fueled by bio‐inspiration and material programmability, have led to the rapid co‐evolution of their core modules: actuation, sensing, protection, energy, and communication. A fundamental challenge lies in integrating these diverse functionalities into a cohesive system without compromising soft robotic performance. Here we show that a rational “materials‐structures‐systems” co‐design strategy is pivotal for achieving this multifunctional integration. While existing reviews often compartmentalize advances by functional modules, this review synthesizes a unified framework demonstrating how such synergistic design enables tight coupling of functionalities, thereby overcoming the traditional trade‐offs between compliance and capability. This approach significantly expands the operational autonomy and environmental resilience of soft robots. The resulting framework not only advances soft robotics but also provides a cross‐disciplinary methodology for innovation in biomedical devices, environmental exploration, and human‐robot interaction, marking a transition from laboratory prototypes to deployable systems for real‐world challenges.

FlexMat.
Northwestern Polytechnical University (CN), Henan Institute of Education (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 20%
Micro and Nano Robotics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.