Flexible sensors for soft robotics: a problem-oriented review of sensing mechanisms, integration and applications

Purpose This paper systematically reviews flexible sensors in soft robotics, aiming to summarize current progress, challenges, and provide a reference for future research. Design/methodology/approach This paper provides a review of flexible sensors in soft robotics, employing a problem-oriented approach to systematically summarize current research progress and challenges. The text commences with an introduction to the various categories of flexible sensors. The performance characteristics, recent developments, practical application issues and corresponding solutions for each sensor type are analyzed. Subsequently, the paper explores the placement and embedding of flexible sensors within soft robots, covering optimal sensor layout, embedding techniques, and challenges in sensor integration along with corresponding solutions. The paper further synthesizes the latest research findings on flexible sensors across diverse application scenarios. Findings Flexible sensors face integration challenges, with key developments spanning diverse applications (soft mobile robots, grippers, motion monitoring). Future trends include codesign of materials/structures/mechanisms, improved sensor integration, and convergence of intelligent sensing with AI. Originality/value This problem-oriented, comprehensive overview uniquely synthesizes sensor types, integration techniques, applications and prospective trends, offering a structured reference for advancing flexible sensors in soft robotics.

Authors

Institutions

Publication Details

Journal
Sensor Review
Published
2026-09-01
DOI
https://doi.org/10.1108/sr-05-2026-0474
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Flexible sensors for soft robotics: a problem-oriented review of sensing mechanisms, integration and applications

Yuxiang Shi, Leilei Miao, Dedong Tang, Tongxuan Tang
Sensor Review
Soft Robotics and Applications
article

Flexible sensors for soft robotics: a problem-oriented review of sensing mechanisms, integration and applications

Yuxiang Shi, Leilei Miao, Dedong Tang, Tongxuan Tang
article en

Abstract

Purpose This paper systematically reviews flexible sensors in soft robotics, aiming to summarize current progress, challenges, and provide a reference for future research. Design/methodology/approach This paper provides a review of flexible sensors in soft robotics, employing a problem-oriented approach to systematically summarize current research progress and challenges. The text commences with an introduction to the various categories of flexible sensors. The performance characteristics, recent developments, practical application issues and corresponding solutions for each sensor type are analyzed. Subsequently, the paper explores the placement and embedding of flexible sensors within soft robots, covering optimal sensor layout, embedding techniques, and challenges in sensor integration along with corresponding solutions. The paper further synthesizes the latest research findings on flexible sensors across diverse application scenarios. Findings Flexible sensors face integration challenges, with key developments spanning diverse applications (soft mobile robots, grippers, motion monitoring). Future trends include codesign of materials/structures/mechanisms, improved sensor integration, and convergence of intelligent sensing with AI. Originality/value This problem-oriented, comprehensive overview uniquely synthesizes sensor types, integration techniques, applications and prospective trends, offering a structured reference for advancing flexible sensors in soft robotics.

Sensor Review
Harbin University of Science and Technology (CN)
Openalex Percentile: Top 20%
Soft Robotics and Applications
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.