Acta Mechanica Sinica, Год журнала: 2024, Номер 41(10)
Опубликована: Окт. 24, 2024
Язык: Английский
Acta Mechanica Sinica, Год журнала: 2024, Номер 41(10)
Опубликована: Окт. 24, 2024
Язык: Английский
Soft Science, Год журнала: 2024, Номер 4(2)
Опубликована: Май 14, 2024
The skin, a vital medium for human-environment communication, stands as an indispensable and pivotal element in the realms of both production daily life. As landscape science technology undergoes gradual evolution demand seamless human-machine interfaces continues to surge, escalating need emerges counterpart our biological skin - electronic skins (e-skins). Achieving high-performance sensing capabilities comparable has consistently posed formidable challenge. In this article, we systematically outline fundamental strategies enabling e-skins with including strain sensing, pressure shear temperature humidity self-healing. Subsequently, complex e-skin systems current major applications were briefly introduced. We conclude by envisioning future trajectory, anticipating continued advancements transformative innovations shaping dynamic technology. This article provides profound insight into state e-skins, potentially inspiring scholars explore new possibilities.
Язык: Английский
Процитировано
9ACS Nano, Год журнала: 2025, Номер unknown
Опубликована: Апрель 7, 2025
Tactile electronic skins (e-skins) are flexible devices that aim to replicate tactile sensing capabilities of the human skin, while possessing skin-like geometric features and materials properties. Since skin is composed complex 3D constructions, where various types mechanoreceptors distributed in a spatial layout, an important trend e-skin development involves introduction device architectures can certain structural skins. The resulting architected e-skins have demonstrated advantages detection shear forces decoupled perception multiple mechanical stimuli, which pivotal importance many application scenarios. In this perspective, we summarize main biological prototypes existing e-skins, focus on key related capabilities. Then highlight enhanced terms super-resolution predictions diverse physical properties surface object, allow for broad spectrum practical applications, such as object recognition, human-machine interactions, dexterous manipulation, health monitoring. Finally, discuss scientific challenges opportunities future developments e-skins.
Язык: Английский
Процитировано
0ACS Applied Polymer Materials, Год журнала: 2024, Номер unknown
Опубликована: Сен. 24, 2024
Язык: Английский
Процитировано
1Journal of Semiconductors, Год журнала: 2024, Номер 45(12), С. 121601 - 121601
Опубликована: Дек. 1, 2024
Abstract Human skin, through its complex mechanoreceptor system, possesses the exceptional ability to finely perceive and differentiate multimodal mechanical stimuli, forming biological foundation for dexterous manipulation, environmental exploration, tactile perception. Tactile sensors that emulate this sensory capability, particularly in detection, decoupling, application of normal shear forces, have made significant strides recent years. This review comprehensively examines latest research advancements force sensing, delving into design decoupling methods multi-unit structures, multilayer encapsulation bionic structures. It analyzes advantages disadvantages various sensing principles, including piezoresistive, capacitive, self-powered mechanisms, evaluates their potential health monitoring, robotics, wearable devices, smart prosthetics, human-machine interaction. By systematically summarizing current progress technical challenges, aims provide forward-looking insights future directions, driving development electronic skin technology ultimately achieve perception capabilities comparable human skin.
Язык: Английский
Процитировано
1Research Square (Research Square), Год журнала: 2024, Номер unknown
Опубликована: Апрель 9, 2024
Abstract The integration of artificial intelligence with sensor technologies has revolutionized precision agriculture, offering unprecedented opportunities for enhancing crop management and productivity. This review focuses on the latest advancements in vision-based tactile sensors, a technology at forefront this transformation. By combining data techniques, these sensors provide more comprehensive understanding agricultural environment. We investigate thoroughly role deep learning approaches refining functionality highlighting their potential to significantly improve accuracy efficiency operations. paper also explores importance specialized datasets training neural networks applications, assessing current landscape identifying gaps available data. Through thorough examination state art, aims shed light AI-driven sensing agriculture outline future research directions further advance field.
Язык: Английский
Процитировано
0Acta Mechanica Sinica, Год журнала: 2024, Номер 41(10)
Опубликована: Окт. 24, 2024
Язык: Английский
Процитировано
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