Self‐Healing Hydrogel‐Based Triboelectric Nanogenerator in Smart Glove System for Integrated Drone Safety Protection and Motion Control

Abstract Flexible sensing technology offers significant advantages in gesture recognition and human–machine interactions. However, existent smart gloves based on flexible sensors still have limitations in their security mechanisms; thus, they are unsuitable for high‐risk environments where identity verification and system protection are critical. This study proposes an innovative smart glove system in which person recognition and gesture control functionalities are integrated. The glove utilizes a triboelectric nanogenerator based on a polyvinyl‐alcohol–sodium‐alginate–conductive‐polyaniline (PSP) hydrogel electrode as the sensor and exhibits high sensitivity, fast response/recovery, and fatigue resistance. These properties are primarily attributed to the excellent stretchability, conductivity, and self‐healing ability of the PSP hydrogel. Because of the coordinated design of the hardware–software architecture, the smart glove enables precise control of drone flight postures via contact sensing. The glove also leverages non‐contact sensing to recognize personalized fingertip trajectories, enabling user recognition and unlocking the aforementioned drone control interface. This design improves not only the flexibility and portability of drone operation but also safety of weapon systems in future battlefield environments.

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Publication Details

Journal
Advanced Functional Materials
Published
2024-12-23
DOI
https://doi.org/10.1002/adfm.202419809
Citations
30
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
5.53

Funders

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article

Self‐Healing Hydrogel‐Based Triboelectric Nanogenerator in Smart Glove System for Integrated Drone Safety Protection and Motion Control

Yang Li, Guozhen Shen, Hongsen Niu, Chengwen Wang
30 citations
Advanced Functional Materials
Advanced Sensor and Energy Harvesting Materials
5.53
article

Self‐Healing Hydrogel‐Based Triboelectric Nanogenerator in Smart Glove System for Integrated Drone Safety Protection and Motion Control

Yang Li, Guozhen Shen, Hongsen Niu, Chengwen Wang
article en
30 citations

Abstract

Abstract Flexible sensing technology offers significant advantages in gesture recognition and human–machine interactions. However, existent smart gloves based on flexible sensors still have limitations in their security mechanisms; thus, they are unsuitable for high‐risk environments where identity verification and system protection are critical. This study proposes an innovative smart glove system in which person recognition and gesture control functionalities are integrated. The glove utilizes a triboelectric nanogenerator based on a polyvinyl‐alcohol–sodium‐alginate–conductive‐polyaniline (PSP) hydrogel electrode as the sensor and exhibits high sensitivity, fast response/recovery, and fatigue resistance. These properties are primarily attributed to the excellent stretchability, conductivity, and self‐healing ability of the PSP hydrogel. Because of the coordinated design of the hardware–software architecture, the smart glove enables precise control of drone flight postures via contact sensing. The glove also leverages non‐contact sensing to recognize personalized fingertip trajectories, enabling user recognition and unlocking the aforementioned drone control interface. This design improves not only the flexibility and portability of drone operation but also safety of weapon systems in future battlefield environments.

Advanced Functional MaterialsVol. 35(17)
Beijing Institute of Technology (CN), Shandong University (CN), Fudan University (CN), University of Jinan (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, National Key Research and Development Program of China
Openalex Percentile: Top 3%
Advanced Sensor and Energy Harvesting Materials
5.53
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Self‐Healing Hydrogel‐Based Triboelectric Nanogenerator in Smart Glove System for Integrated Drone Safety Protection and Motion Control — Yang Li, Guozhen Shen, et al. · Advanced Functional Materials (2024) | TGRS Research Map | TGRS