Nature Reviews Electrical Engineering最新文献_第5页

Innovating robot-assisted surgery through large vision models 通过大视觉模型创新机器人辅助手术

Nature Reviews Electrical Engineering Pub Date : 2025-05-12 DOI: 10.1038/s44287-025-00166-6

Zhe Min (, ), Jiewen Lai (, ), Hongliang Ren (, )

{"title":"Innovating robot-assisted surgery through large vision models","authors":"Zhe Min \u0000 (, ), Jiewen Lai \u0000 (, ), Hongliang Ren \u0000 (, )","doi":"10.1038/s44287-025-00166-6","DOIUrl":"10.1038/s44287-025-00166-6","url":null,"abstract":"The rapid development of generative artificial intelligence and large models, including large vision models (LVMs), has accelerated their wide applications in medicine. Robot-assisted surgery (RAS) or surgical robotics, in which vision has a vital role, typically combines medical images for diagnostic or navigation abilities with robots with precise operative capabilities. In this context, LVMs could serve as a revolutionary paradigm towards surgical autonomy, accomplishing surgical representations with high fidelity and physical intelligence and enabling high-quality data use and long-term learning. In this Perspective, vision-related tasks in RAS are divided into fundamental upstream tasks and advanced downstream counterparts, elucidating their shared technical foundations with state-of-the-art research that could catalyse a paradigm shift in surgical robotics research for the next decade. LVMs have already been extensively explored to tackle upstream tasks in RAS, exhibiting promising performances. Developing vision foundation models for downstream RAS tasks, which is based on upstream counterparts but necessitates further investigations, will directly enhance surgical autonomy. Here, we outline research trends that could accelerate this paradigm shift and highlight major challenges that could impede progress in the way to the ultimate transformation from ‘surgical robots’ to ‘robotic surgeons’. Robot-assisted surgery relies heavily on vision and generally integrates medical imaging for diagnostic and/or navigation purposes with robots that offer accurate surgical functions. This Perspective discusses how large vision models can enhance vision-related tasks in robot-assisted surgery transforming ‘surgical robots’ into ‘robotic surgeons’.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 5","pages":"350-363"},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging Wi-Fi networks for better motion detection 利用Wi-Fi网络进行更好的运动检测

Nature Reviews Electrical Engineering Pub Date : 2025-05-09 DOI: 10.1038/s44287-025-00180-8

Miranda L. Vinay

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Unlocking wavefront control potential with stacked technologies that jointly sense and shape light at pixel level 通过堆叠技术，在像素级共同感知和塑造光，解锁波前控制潜力

Nature Reviews Electrical Engineering Pub Date : 2025-05-09 DOI: 10.1038/s44287-025-00173-7

Arnaud Verdant, Pierre L. Joly

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Meet the winners of the 2024 Sony Women in Technology Award 来看看2024年索尼女性科技奖的获奖者吧

Nature Reviews Electrical Engineering Pub Date : 2025-05-08 DOI: 10.1038/s44287-025-00171-9

Kiana Aran, Jiawen Li, Amanda Randles, Yating Wan

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Electrodermal activity sensors for monitoring mental and physical activity 用于监测精神和身体活动的皮肤电活动传感器

Nature Reviews Electrical Engineering Pub Date : 2025-04-29 DOI: 10.1038/s44287-025-00172-8

Silvia Conti

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Ungendering engineering to solve the engineering crisis 解决工程危机的非性别工程

Nature Reviews Electrical Engineering Pub Date : 2025-04-28 DOI: 10.1038/s44287-025-00167-5

Anna Grzelec, Christina Mauléon

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Designing the future electricity spot market with high renewables via reliable simulations 通过可靠模拟设计未来高可再生能源电力现货市场

Nature Reviews Electrical Engineering Pub Date : 2025-04-23 DOI: 10.1038/s44287-025-00163-9

Ziqing Zhu, Siqi Bu, Ka Wing Chan, Fangxing Li, Yujian Ye, Chi Yung Chung, Goran Strbac

{"title":"Designing the future electricity spot market with high renewables via reliable simulations","authors":"Ziqing Zhu, Siqi Bu, Ka Wing Chan, Fangxing Li, Yujian Ye, Chi Yung Chung, Goran Strbac","doi":"10.1038/s44287-025-00163-9","DOIUrl":"10.1038/s44287-025-00163-9","url":null,"abstract":"The global transition to renewable energy is crucial for mitigating climate change, but the increasing penetration of renewable sources introduces challenges such as uncertainty and intermittency. The electricity market plays a vital role in encouraging renewable generation while ensuring operational security and grid stability. This Review examines the optimization of market design for power systems with high renewable penetration. We explore recent innovations in renewable-dominated electricity market designs, summarizing key research questions and strategies. Special focus is given to multi-agent reinforcement learning (MARL) for market simulations, its performance and real-world applicability. We also review performance evaluation metrics and present a case study from the Horizon 2020 TradeRES project, exploring European electricity market design under 100% renewable penetration. Finally, we discuss unresolved issues and future research directions. This Review examines the optimization of electricity market design to support high renewable penetration, focusing on multi-agent reinforcement learning (MARL) for market simulations, performance evaluation and future research directions, with a case study on European market design under 100% renewable penetration.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 5","pages":"320-337"},"PeriodicalIF":0.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Symbiotic energy paradigm for self-sustaining aerial robots 自给式空中机器人的共生能量模式

Nature Reviews Electrical Engineering Pub Date : 2025-04-17 DOI: 10.1038/s44287-025-00168-4

Hao Wang, Lingji Kong, Zheng Fang, Rui Zou, Zutao Zhang, Xinyi Zhao, Qianqian Zong, Zhongqu Xie

{"title":"Symbiotic energy paradigm for self-sustaining aerial robots","authors":"Hao Wang, Lingji Kong, Zheng Fang, Rui Zou, Zutao Zhang, Xinyi Zhao, Qianqian Zong, Zhongqu Xie","doi":"10.1038/s44287-025-00168-4","DOIUrl":"10.1038/s44287-025-00168-4","url":null,"abstract":"Aerial robots, capable of autonomous flight and task execution, are increasingly applied in photography, geo-mapping, surveillance, agriculture and logistics fields. As these technologies evolve, the need for robust, reliable and self-sustaining aerial robots (SSARs) with extended endurance and range becomes more urgent. Integrating energy-harvesting technologies in aerial robots is essential to enable self-sufficiency by using environmental energy sources. The analysis of the design principles of aerial robots and the exploration of energy utilization models from nature that offer symbiotic energy design concepts are essential for creating compact, versatile and efficient SSARs. Here, we discuss the emerging paradigm of environmental energy-harvesting and storage technologies and construct system-level energy matching and analyse flight energy-saving technologies guided by symbiotic energy principles, such as self-sensing, advanced drives, dynamic soaring and swarm intelligence. We also address technical challenges in the evaluation, design and development processes and discuss future directions considering interdisciplinary research in artificial intelligence and advanced materials. Central to this Review is an emphasis on a symbiotic energy design paradigm that integrates bionics, multifunctionality and integration in developing SSARs. Symbiotic energy paradigm for self-sustaining aerial robots includes multifunctional integration strategies and energy-saving mechanisms inspired by natural flyers. This Review outlines design principles, technological solutions, technical challenges and future directions of the application of the symbiotic energy paradigm to aerial robots.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 5","pages":"302-319"},"PeriodicalIF":0.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing generative AI reliability via agentic AI in 6G-enabled edge computing 通过支持6g的边缘计算中的代理AI增强生成式AI的可靠性

Nature Reviews Electrical Engineering Pub Date : 2025-04-14 DOI: 10.1038/s44287-025-00169-3

Laha Ale, Scott A. King, Ning Zhang, Huanlai Xing

引用次数: 0

A bright future for self-sustainable bioelectronics 自我可持续生物电子学的光明未来

Nature Reviews Electrical Engineering Pub Date : 2025-04-09 DOI: 10.1038/s44287-025-00164-8

Fei Jin, Tong Li, Zhidong Wei, Lili Qian, Negar Javanmardi, Ting Wang, Steven Wang, Zhang-Qi Feng

{"title":"A bright future for self-sustainable bioelectronics","authors":"Fei Jin, Tong Li, Zhidong Wei, Lili Qian, Negar Javanmardi, Ting Wang, Steven Wang, Zhang-Qi Feng","doi":"10.1038/s44287-025-00164-8","DOIUrl":"10.1038/s44287-025-00164-8","url":null,"abstract":"Self-sustainable bioelectronic devices that incorporate physiological synchronization functions are attracting increasing research interest because they could provide the variable functions required by living cells and tissues. However, from the popular viewpoint, self-sustainable bioelectronic devices are presently regarded to provide unidirectional stimulation, similarly to traditional bioelectronic devices that prompt cells and tissues to passively respond to the electrical cues delivered to them. The active effect of self-sustainable bioelectronic devices, which allows cells and/or tissues to autonomously alter the delivered electrical stimulation on demand, has not been fully recognized. This Perspective article presents the insight that self-sustainable bioelectronics could act as a bidirectional ‘bridge’ linking the electrical modulation of a cell or tissue with its growth and development requirements, thereby establishing a fully autonomous, closed-loop regulatory system. The interaction processes arising in microscopic (cell–piezoelectric material) and macroscopic (organ–electromechanically coupled device) systems are discussed, and typical examples of self-sustainable bioelectronics are presented, highlighting the key challenges of signal fidelity and long-term device stability. Predictions of the future trajectory of self-sustainable bioelectronics, and design considerations for the next generation of intelligent bioelectronic devices, are also included. This Perspective highlights the biofeedback capability of self-sustainable bioelectronics, which provides a new treatment paradigm. This feature enables cells and tissues to autonomously alter the supplied electrical stimulation to meet their varying needs, thereby forming a bidirectional interaction mechanism at organism–machine interfaces.","PeriodicalId":501701,"journal":{"name":"Nature Reviews Electrical Engineering","volume":"2 5","pages":"338-349"},"PeriodicalIF":0.0,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0