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Carbon allotropes/fabrics-based triboelectric nanogenerators: Current progress and future perspectives

Materials science and engineering: R: Reports 2025年 166卷

作者： Shan He Matt Jellicoe Aniket Chakraborthy Md. Eshrat E. Alahi Anindya Nag Warwick Powell School of Food and Pharmacy Zhejiang Ocean University Zhoushan Zhejiang 316022 China Institute for NanoScale Science and Technology College of Science and Engineering Flinders University Bedford Park Australia Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden 01062 Germany Centre for Tactile Internet with Human-in-the-Loop (CeTI) Technische Universität Dresden Dresden 01069 Germany School of Engineering and Technology Walailak University 222 Thaiburi Thasala District Nakhon Si Thammarat 80160 Thailand QUT Design Lab Queensland University of Technology Brisbane Queensland Australia

The paper presents a substantial review of triboelectric nanogenerators (TENG) development using different carbon allotropes and fabric materials. TENG has been state-of-the-art since the last decade due to its low cost, simple construction, high output and multifunctional applications. Based on their working mechanism, these prototypes have been developed using a wide range of nanomaterials and polymers to induce high open-circuit voltage and short-circuit current. Certain carbon-based nanomaterials, such as carbon nanotubes, graphene and others, have been found to be very effective due to their excellent electrical properties and biocompatibility. These carbon materials have been intertwined and fused with polymers to form effective energy generators and harvesters. Conjugating these carbon materials into certain flexible fabrics, like cotton, silk, polyester and others, has been largely successful. In addition to some of the factors that affect the performance of the nanogenerators, this paper also showcases some of the fabric-based prototypes, the performance of which has been enhanced by adding carbon materials. The market survey and the future perspectives have also been shown.

关键词： Nanogenerators Carbon Fabric Energy harvesting Flexible

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Observation of intrinsic chiral bound states in the continuum

arXiv

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arXiv 2022年

作者： Chen, Yang Deng, Huachun Sha, Xinbo Chen, Weijin Wang, Ruize Chen, Yuhang Wu, Dong Chu, Jiaru Kivshar, Yuri S. Xiao, Shumin Qiu, Cheng-Wei Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Chinese Academy of Sciences Key Laboratory of Mechanical Behavior and Design of Materials Department of Precision Machinery and Precision Instrumentation University of Science and Technology of China Hefei230027 China Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Harbin Institute of Technology Shenzhen518055 China Nonlinear Physics Center Research School of Physics Australian National University CanberraACT2601 Australia Pengcheng Laboratory Shenzhen518055 China

Photons with spin angular momentum possess intrinsic chirality which underpins many phenomena including nonlinear optics1, quantum optics2, topological photonics3 and chiroptics4. Intrinsic chirality is weak in natural materials, and recent theoretical proposals5-7 aimed to enlarge circular dichroism by resonant metasurfaces supporting bound states in the continuum that enhance substantially chiral light-matter interaction. Those insightful works resort to three-dimensional sophisticated geometries, which are too challenging to be realized for optical frequencies8. Therefore, most of the experimental attempts9-11 showing strong circular dichroism rely on false/extrinsic chirality by employing either oblique incidence9, 10 or structural anisotropy11. Here, we report on the experimental realization of true/intrinsic chiral response with resonant metasurfaces where the engineered slant geometry breaks both in-plane and out-of-plane symmetries. Our result marks the first observation of intrinsic chiral bound states in the continuum with near-unity chiral dichroism of 0.93 and record-high quality factor exceeding 2663 for visible frequencies. Our chiral metasurfaces promise a plethora of applications in chiral light sources and detectors, chiral sensing, valleytronics and asymmetric photocatalysis. © 2022, CC BY.

关键词： Dichroism

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Fractal dimension and retinal pathology: A meta-analysis

arXiv

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arXiv 2021年

作者： Yu, Sam Lakshminarayanan, Vasudevan Department of Physics and Astronomy University of Waterloo ONN2L 3G1 Canada Theoretical and Experimental Epistemology Lab School of Optometry and Vision Science Department of Electrical and Computer Engineering University of Waterloo ONN2L 3G1 Canada Department of Systems Design Engineering University of Waterloo ONN2L 3G1 Canada

Due to the fractal nature of retinal blood vessels, the retinal fractal dimension is a natural parameter for researchers to explore and has garnered interest as a potential diagnostic tool. This review aims to summarize the current scientific evidence regarding the relationship between fractal dimension and retinal pathology and thus assess the clinical value of retinal fractal dimension. Following the PRISMA guidelines, a literature search for research articles was conducted in several internet databases (Embase, PubMed, Web of science, Scopus). This led to a result of 28 studies included in the final review, which were analyzed via meta-analysis to determine whether the fractal dimension changes significantly in retinal disease versus normal individuals. © 2021, CC BY.

关键词： Ophthalmology

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Bring game characters to the social space: Developing storytelling community AI agents driven by LLMs

引用

Entertainment Computing 2025年 54卷

作者： Yuqian Sun Hanyi Wang Pok Man Chan Morteza Tabibi Yan Zhang Huan Lu Yuheng Chen Chang Hee Lee Ali Asadipour Computer Science Research Centre Royal College of Art Rausing Research & Innovation Building 15 Parkgate Road London SW11 4NL United Kingdom Independent United States Independent Hong Kong Independent China rct.ai United States Affective Systems and Cognition Lab Industrial Design Department College of Engineering KAIST Daejeon South Korea

AI agents driven by Large Language Models (LLMs) are now ubiquitous in our daily life, so can they bring characters from games into reality? We address the integration of storytelling and AI agents driven by LLMs to develop engaging and believable fictional characters in community settings. Motivated by the potential of fictional characters to enhance social interactions, we introduce Storytelling Community AI Agents (SCAs) and the concept of story engineering to transform fictional game characters into ”live” social entities within player communities. Our story engineering process includes three steps: (1) Character and story creation, defining the SCA’s personality and worldview, (2) Presenting Live Stories to the Community, allowing the agent to recount challenges and seek suggestions, and (3) Communication with community members, enabling interaction between the agent and users. We employed the LLM GPT-3 to drive our SCAs, “David” and “Catherine,” and evaluated their performance in an online gaming community, “DE (Alias),” on Discord. Our mixed-method analysis, based on questionnaires (N=15) and interviews (N=8) with community members, reveals that storytelling significantly enhances the engagement and believability of AI agents in community settings.

关键词： AI agent Community agent Interactive storytelling LLM agent Non-player character

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Novel Smart N95 Filtering Facepiece Respirator with Real-time Adaptive Fit Functionality and Wireless Humidity Monitoring for Enhanced Wearable Comfort

arXiv

引用

arXiv 2023年

作者： Kwon, Kangkyu Lee, Yoon Jae Jung, Yeongju Soltis, Ira Choi, Chanyeong Na, Yewon Romero, Lissette Kim, Myung Chul Rodeheaver, Nathan Kim, Hodam Lloyd, Michael S. Zhuang, Ziqing King, William Xu, Susan Ko, Seung-Hwan Lee, Jinwoo Yeo, Woon-Hong School of Electrical and Computer Engineering College of Engineering Georgia Institute of Technology AtlantaGA30332 United States Center for Human-Centric Interfaces and Nanoengineering Institute for Electronics and Nanotechnology Georgia Institute of Technology AtlantaGA30332 United States Applied Nano and Thermal Science Lab Department of Mechanical Engineering Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology AtlantaGA30332 United States School of Industrial Design Georgia Institute of Technology AtlantaGA30332 United States Division of Cardiology Emory University School of Medicine AtlantaGA30322 United States National Institute for Occupational Safety and Health National Personal Protective Technology Laboratory PittsburghPA15236 United States Seoul National University Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Department of Mechanical Robotics and Energy Engineering Dongguk University 30 Pildongro 1-gil Jung-gu Seoul04620 Korea Republic of Wallace H. Coulter Department of Biomedical Engineering Parker H. Petit Institute for Bioengineering and Biosciences Neural Engineering Center Institute for Materials Institute for Robotics and Intelligent Machines Georgia Institute of Technology AtlantaGA30332 United States

The widespread emergence of the COVID-19 pandemic has transformed our lifestyle, and facial respirators have become an essential part of daily life. Nevertheless, the current respirators possess several limitations such as poor respirator fit because they are incapable of covering diverse human facial sizes and shapes, potentially diminishing the effect of wearing respirators. In addition, the current facial respirators do not inform the user of the air quality within the smart facepiece respirator in case of continuous long-term use. Here, we demonstrate the novel smart N-95 filtering facepiece respirator that incorporates the humidity sensor and pressure sensory feedback-enabled self-fit adjusting functionality for the effective performance of the facial respirator to prevent the transmission of airborne pathogens. The laser-induced graphene (LIG) constitutes the humidity sensor, and the pressure sensor array based on the dielectric elastomeric sponge monitors the respirator contact on the user’s face, providing the sensory information for a closed-loop feedback mechanism. As a result of the self-fit adjusting mode along with elastomeric lining, the fit factor is increased by 3.20 and 5 times at average and maximum respectively. We expect that the experimental proof-of-concept of this work will offer viable solutions to the current commercial respirators to address the *** Codes 92C55 Copyright © 2023, The Authors. All rights reserved.

关键词： Graphene

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Fast generation of high fidelity RGB-D images by deep-learning with adaptive convolution

arXiv

引用

arXiv 2020年

作者： Xian, Chuhua Zhang, Dongjiu Dai, Chengkai Wang, Charlie C.L. Guangdong Provincial Key Lab of Computational Intelligence and Cyberspace Information School of Computer Science and Engineering South China University of Technology Guangzhou Guangzhou510006 China Faculty of Industrial Design Engineering Delft University of Technology Netherlands Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

Using the raw data from consumer-level RGB-D cameras as input, we propose a deep-learning based approach to efficiently generate RGB-D images with completed information in high resolution. To process the input images in low resolution with missing regions, new operators for adaptive convolution are introduced in our deep-learning network that consists of three cascaded modules - the completion module, the refinement module and the super-resolution module. The completion module is based on an architecture of encoder-decoder, where the features of input raw RGB-D will be automatically extracted by the encoding layers of a deep neural-network. The decoding layers are applied to reconstruct the completed depth map, which is followed by a refinement module to sharpen the boundary of different regions. For the super-resolution module, we generate RGB-D images in high resolution by multiple layers for feature extraction and a layer for up-sampling. Benefited from the adaptive convolution operators proposed in this paper, our results outperform the existing deep-learning based approaches for RGB-D image complete and super-resolution. As an end-to-end approach, high fidelity RGB-D images can be generated efficiently at the rate of 22 frames per second. Copyright © 2020, The Authors. All rights reserved.

关键词： Cameras

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Generalized Scaling Law for Exciton Binding Energy in Two-Dimensional Materials

引用

Physical Review Applied 2020年第6期13卷 064062-064062页

作者： S. Ahmad M. Zubair O. Jalil M. Q. Mehmood U. Younis X. Liu K. W. Ang L. K. Ang Electrical Engineering Department Information Technology University (ITU) of the Punjab Lahore 54000 Pakistan NanoTech Lab Electrical Engineering Department Information Technology University (ITU) of the Punjab Lahore 54000 Pakistan College of Materials Science and Engineering Shenzhen Key Laboratory of Microscale Optical Information Technology Chinese Engineering and Research Institute of Microelectronics Shenzhen University 3688 Nanhai Avenue Shenzhen 518060 People’s Republic of China Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 Singapore Science and Math Cluster Singapore University of Technology and Design (SUTD) 8 Somapah Road Singapore 487372 Singapore

Binding energy calculation in two-dimensional (2D) materials is crucial in determining their electronic and optical properties pertaining to enhanced Coulomb interactions between charge carriers due to quantum confinement and reduced dielectric screening. Based on full solutions of the Schrödinger equation in a screened hydrogen model with a modified Coulomb potential (1/rβ−2), we present a generalized and analytical scaling law for the exciton binding energy, Eβ=E0(aβb+c)(μ/ϵ2), where β is a fractional-dimension parameter that accounts for the reduced dielectric screening. The model is able to provide accurate binding energies, benchmarked using the reported Bethe-Salpeter equation and experimental data, for 58 monolayer 2D and eight bulk materials, respectively, through β. For a given material, β is varied from β=3 for bulk three-dimensional materials to a value lying in the range 2.55–2.7 for 2D monolayer materials. With βmean=2.625, our model improves the average relative mean square error by a factor of 3 in comparison to existing models. The results can be used for Coulomb engineering of exciton binding energies in the optimal design of 2D materials.

关键词： Excitons Optoelectronics 2-dimensional systems Quantum wells Semiconductors Scaling methods

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SoccerNet 2023 Challenges Results

arXiv

引用

arXiv 2023年

作者： Cioppa, Anthony Giancola, Silvio Somers, Vladimir Magera, Floriane Zhou, Xin Mkhallati, Hassan Deliège, Adrien Held, Jan Hinojosa, Carlos Mansourian, Amir M. Miralles, Pierre Barnich, Olivier De Vleeschouwer, Christophe Alahi, Alexandre Ghanem, Bernard Van Droogenbroeck, Marc Kamal, Abdullah Maglo, Adrien Clapés, Albert Abdelaziz, Amr Xarles, Artur Orcesi, Astrid Scott, Atom Liu, Bin Lim, Byoungkwon Chen, Chen Deuser, Fabian Yan, Feng Yu, Fufu Shitrit, Gal Wang, Guanshuo Choi, Gyusik Kim, Hankyul Guo, Hao Fahrudin, Hasby Koguchi, Hidenari Ardö, Håkan Salah, Ibrahim Yerushalmy, Ido Muhammad, Iftikar Uchida, Ikuma Be'ery, Ishay Rabarisoa, Jaonary Lee, Jeongae Fu, Jiajun Yin, Jianqin Xu, Jinghang Nang, Jongho Denize, Julien Li, Junjie Zhang, Junpei Kim, Juntae Synowiec, Kamil Kobayashi, Kenji Zhang, Kexin Habel, Konrad Nakajima, Kota Jiao, Licheng Ma, Lin Wang, Lizhi Wang, Luping Li, Menglong Zhou, Mengying Nasr, Mohamed Abdelwahed, Mohamed Liashuha, Mykola Falaleev, Nikolay Oswald, Norbert Jia, Qiong Pham, Quoc-Cuong Song, Ran Hérault, Romain Peng, Rui Chen, Ruilong Liu, Ruixuan Baikulov, Ruslan Fukushima, Ryuto Escalera, Sergio Lee, Seungcheon Chen, Shimin Ding, Shouhong Someya, Taiga Moeslund, Thomas B. Li, Tianjiao Shen, Wei Zhang, Wei Li, Wei Dai, Wei Luo, Weixin Zhao, Wending Zhang, Wenjie Yang, Xinquan Ma, Yanbiao Joo, Yeeun Zeng, Yingsen Gan, Yiyang Zhu, Yongqiang Zhong, Yujie Ruan, Zheng Li, Zhiheng Huang, Zhijian Meng, Ziyu Belgium Saudi Arabia Sportradar Norway UCLouvain Belgium EPFL Switzerland EVS Broadcast Equipment Belgium Baidu Research United States Belgium Sharif University of Technology Iran Footovision France Zewail City of Science Technology and Innovation Egypt Université Paris-Saclay CEA France Universitat de Barcelona Spain Computer Vision Center Spain Nagoya University Japan Research Center for Applied Mathematics and Machine Intelligence Zhejiang Lab China AIBrain United States OPPO Research Institute China Germany Meituan China Tencent Youtu Lab China Amazon Prime Video Sport United States Sogang University Korea Republic of The University of Tokyo Japan Spiideo Sweden University of Tsukuba Japan School of Artificial Intelligence Beijing University of Posts and Telecommunications China Normandie Univ INSA Rouen LITIS France Shanghai Jiao Tong University China Key Laboratory of Intelligent Perception and Image Understanding The Ministry of Education Xidian University China NASK - National Research Institute Poland Robo Space China Tongji University China Sportlight Technology United Kingdom School of Control Science and Engineering Shandong University China lRomul Russia Aalborg University Denmark Turing AI Cultures GmbH Germany Information Systems Technology and Design Singapore University of Technology and Design Singapore Sun Yat-sen University China

The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vision-based tasks split into three main themes. The first theme, broadcast video understanding, is composed of three high-level tasks related to describing events occurring in the video broadcasts: (1) action spotting, focusing on retrieving all timestamps related to global actions in soccer, (2) ball action spotting, focusing on retrieving all timestamps related to the soccer ball change of state, and (3) dense video captioning, focusing on describing the broadcast with natural language and anchored timestamps. The second theme, field understanding, relates to the single task of (4) camera calibration, focusing on retrieving the intrinsic and extrinsic camera parameters from images. The third and last theme, player understanding, is composed of three low-level tasks related to extracting information about the players: (5) re-identification, focusing on retrieving the same players across multiple views, (6) multiple object tracking, focusing on tracking players and the ball through unedited video streams, and (7) jersey number recognition, focusing on recognizing the jersey number of players from tracklets. Compared to the previous editions of the SoccerNet challenges, tasks (2-3-7) are novel, including new annotations and data, task (4) was enhanced with more data and annotations, and task (6) now focuses on end-to-end approaches. More information on the tasks, challenges, and leader-boards are available on https://***. Baselines and development kits can be found on https://***/SoccerNet. © 2023, CC BY.

关键词： computer vision

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Consistent Discretization of a Class of Predefined-Time Stable Systems

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IFAC-PapersOnLine 2020年第2期53卷 628-633页

作者： Esteban Jiménez-Rodríguez Rodrigo Aldana-López Juan D. Sánchez-Torres David Gómez-Gutiérrez Alexander G. Loukianov Relativity6 Inc. Computer Science & Artificial Intelligence Lab Jalisco 45040 México Department of Computer Science and Systems Engineering University of Zaragoza Zaragoza 50009 España Research Laboratory on Optimal Design Devices and Advanced Materials -OPTIMA- Department of Mathematics and Physics ITESO Jalisco 45604 México Multi-agent autonomous systems lab Intel Labs Intel Tecnología de México Jalisco 45019 Mexico Tecnologico de Monterrey Escuela de Ingeniería y Ciencias Jalisco 45138 Mexico Department of Electrical Engineering Cinvestav-Guadalajara Jalisco 45019 México

As the main contribution, this document provides a consistent discretization of a class of fixed-time stable systems, namely predefined-time stable systems. In the unperturbed case, the proposed approach allows obtaining not only a consistent but exact discretization of the considered class of predefined-time stable systems, whereas in the perturbed case, the consistent discretization preserves the predefined-time stability property. All the results are validated through simulations and compared with the conventional explicit Euler scheme, highlighting the advantages of this proposal.

关键词： Predefined-time stability Discrete-time systems Digital implementation Stability of nonlinear systems Fixed-time stability

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Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

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Nature Ecology and Evolution 2025年第6期9卷 1031-1042页

作者： Pringle, Stephen Dallimer, Martin Goddard, Mark A. Le Goff, Léni K. Hart, Emma Langdale, Simon J. Fisher, Jessica C. Abad, Sara-Adela Ancrenaz, Marc Angeoletto, Fabio Auat Cheein, Fernando Austen, Gail E. Bailey, Joseph J. Baldock, Katherine C. R. Banin, Lindsay F. Banks-Leite, Cristina Barau, Aliyu S. Bashyal, Reshu Bates, Adam J. Bicknell, Jake E. Bielby, Jon Bosilj, Petra Bush, Emma R. Butler, Simon J. Carpenter, Dan Clements, Christopher F. Cully, Antoine Davies, Kendi F. Deere, Nicolas J. Dodd, Michael Drinkwater, Rosie Driscoll, Don A. Dutilleux, Guillaume Dyrmann, Mads Edwards, David P. Farhadinia, Mohammad S. Faruk, Aisyah Field, Richard Fletcher, Robert J. Foster, Chris W. Fox, Richard Francksen, Richard M. Franco, Aldina M. A. Gainsbury, Alison M. Gardner, Charlie J. Giorgi, Ioanna Griffiths, Richard A. Hamaza, Salua Hanheide, Marc Hayward, Matt W. Hedblom, Marcus Helgason, Thorunn Heon, Sui P. Hughes, Kevin A. Hunt, Edmund R. Ingram, Daniel J. Jackson-Mills, George Jowett, Kelly Keitt, Timothy H. Kloepper, Laura N. Kramer-Schadt, Stephanie labisko, Jim labrosse, Frédéric Lawson, Jenna Lecomte, Nicolas de Lima, Ricardo F. Littlewood, Nick A. Marshall, Harry H. Masala, Giovanni L. Maskell, Lindsay C. Matechou, Eleni Mazzolai, Barbara McConnell, Alistair Melbourne, Brett A. Miriyev, Aslan Nana, Eric Djomo Ossola, Alessandro Papworth, Sarah Parr, Catherine L. Payo-Payo, Ana Perry, Gad Pettorelli, Nathalie Pillay, Rajeev Potts, Simon G. Prendergast-Miller, Miranda T. Qie, Lan Rolley-Parnell, Persie Rossiter, Stephen J. Rowcliffe, Marcus Rumble, Heather Sadler, Jon P. Sandom, Christopher J. Sanyal, Asiem Schrodt, Franziska Sethi, Sarab S. Shabrani, Adi Siddall, Robert Smith, Simón C. Snep, Robbert P. H. Soulsbury, Carl D. Stanley, Margaret C. Stephens, Philip A. Stephenson, P.J. Struebig, Matthew J. Studley, Matthew Svátek, Martin Tang, Gilbert Taylor, Nicholas K. Umbers, Kate D. L. Ward, Robert J. White, Patrick J. C. Whittingham, Mark J. Wich, Serge Williams, Christopher D. Yakubu, Ibrahim B. Yoh, Natalie Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury United Kingdom Centre for Environmental Policy Imperial College London London United Kingdom Department of Geography and Environmental Sciences Northumbria University Newcastle upon Tyne United Kingdom School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom Synthotech Ltd Milner Court Hornbeam Square Harrogate United Kingdom Mechanical Engineering Department University College London London United Kingdom HUTAN SWD Kota Kinabalu Malaysia Programa de Pós-Graduação em Gestão e Tecnologia Ambiental da Universidade Federal de Rondonópolis Rondonópolis Brazil Department of Engineering Harper Adams University Newport United Kingdom Applied Ecology Research Group School of Life Sciences Anglia Ruskin University Cambridge United Kingdom Centre for Ecology and Hydrology Penicuik United Kingdom Department of Life Sciences Imperial College London Silwood Park Campus Ascot United Kingdom Department of Urban and Regional Planning Faculty of Earth and Environmental Sciences Bayero University Kano Nigeria Greenhood Nepal Kathmandu Nepal Animal Rural & Environmental Sciences Nottingham Trent University Nottinghamshire United Kingdom School of Biological and Environmental Sciences Liverpool John Moores University Liverpool United Kingdom Lincoln Centre for Autonomous Systems University of Lincoln Lincoln United Kingdom Royal Botanic Garden Edinburgh Edinburgh United Kingdom School of Biological Sciences University of East Anglia Norwich Research Park Norwich United Kingdom Digital Ecology Limited Bristol United Kingdom School of Biological Sciences University of Bristol Bristol United Kingdom Department of Computing Imperial College London London United Kingdom Department of Ecology and Evolutionary Biology University of Colorado Boulder CO United States Faculty of Science Technology Engineering

With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more ‘difficult’ taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively. © The Author(s) 2025.

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