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Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

Nature ecology & evolution 2025年 2025 May 22页

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

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.

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Dejun Guo Hesheng Wang Weidong Chen Ming Liu Zeyang Xia Kam K. Leang DARC (Design Automation Robotics & Control) Lab University of Utah Robotics Center Salt Lake City Utah USA State Key Laboratory of Robotics and System (HIT) Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong China Institute of Biomedical and Health Engineering Chinese Academy of Sciences Shenzhen China

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Cameras Robot vision systems Kinematics Mobile robots Calibration Automation

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Near-field source localization with partly sensor gain and phase uncertainties

Near-field source localization with partly sensor gain and p...

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IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Weiliang Zuo Jingmin Xin Guangmin Wang Jiasong Wang Nanning Zheng Akira Sano Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China State Key Laboratory of Astronautic Dynamics Xi'an China Department of System Design Engineering Keio Univerity Yokohama Japan

In this paper, we consider the source localization for the multiple near-field narrowband signals impinging on a uniform linear array (ULA) with partly gain and phase uncertainties. By dividing the ULA into two overlapped symmetric subarrays and assuming that they have partly unknown gain and phase responses but correspondingly identical, a new modified generalized ESPRIT based method is presented, in which the direction of arrival (DOA) and range are estimated separately. Moreover, we prove that the proposed method is equivalent to the spectral Fresnel-region rank reduction (FR-RARE) [15] method, but more computationally efficient than it. The simulations demonstrate the effectiveness of the proposed method.

关键词： Direction-of-arrival estimation Arrays Estimation Conferences Signal to noise ratio Vectors

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Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016

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Implement Sci 2017年第SUPPL 1期12卷 48-48页

作者： David Chambers Lisa Simpson Gila Neta Ulrica von Thiele Schwarz Antoinette Percy-Laurry Gregory A. Aarons Ross Brownson Amanda Vogel Shannon Wiltsey Stirman Kenneth Sherr Rachel Sturke Wynne E. Norton Allyson Varley Cynthia Vinson Lisa Klesges Suzanne Heurtin-Roberts M. Rashad Massoud Leighann Kimble Arne Beck Claire Neely Jennifer Boggs Carmel Nichols Wen Wan Erin Staab Neda Laiteerapong Nathalie Moise Ravi Shah Susan Essock Margaret Handley Amy Jones Jay Carruthers Karina Davidson Lauren Peccoralo Lloyd Sederer Todd Molfenter Ashley Scudder Sarah Taber-Thomas Kristen Schaffner Amy Herschell Eva Woodward Jeffery Pitcock Mona Ritchie JoAnn Kirchner Julia E. Moore Sobia Khan Shusmita Rashid Jamie Park Melissa Courvoisier Sharon Straus Daniel Blonigen Allison Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal David Smelson Christine Timko Nicole Stadnick Jennifer Regan Miya Barnett Anna Lau Lauren Brookman-Frazee Erick Guerrero Karissa Fenwick Yinfei Kong Gregory Aarons Rebecca Lengnick-Hall Benjamin Henwood Nina Sayer Craig Rosen Robert Orazem Brandy Smith Lindsey Zimmerman David Lounsbury Rachel Kimerling Jodie A. Trafton Steven Lindley Rahul Bhargava Hal Roberts Laura Gibson Gabriel J. Escobar Vincent Liu Benjamin Turk Arona Ragins Patricia Kipnis Ashley Ketterer Gruszkowski Michael W. Kennedy Emily Rentschler Drobek Lior Turgeman Aleksandra Sasha Milicevic Terrence L. Hubert Larissa Myaskovsky Youxu C. Tjader Robert J. Monte Kathryn G. Sapnas Edmond Ramly Diane R Lauver Christie M Bartels Shereef Elnahal Andrea Ippolito Hillary Peabody Carolyn Clancy Randall Cebul Thomas Love Douglas Einstadter Shari Bolen Brook Watts Vera Yakovchenko Angela Park William Lukesh Donald R. Miller David Thornton Mari-Lynn Drainoni Allen L. Gifford Shawna Smith Julia Kyle Mark S Bauer Daniel Eisenberg Celeste Liebrecht Michelle Barbaresso Amy Kilbourne Elyse Park Giselle Perez Jamie Ostroff Sarah Greene Michael Parchman Brian Austin Eric Larson Stefanie Ferreri Chris Shea Megan Smith Kea Turner Jennifer Bacci Kyle Bigham Geoffr Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD 20850 USA AcademyHealth Washington DC 20009 USA Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm 17177 Sweden Department of Psychiatry University of California San Diego San Diego CA 92093 USA George Warren Brown School of Social Work Washington University in St. Louis St. Louis MO 63130 USA Center for Global Health National Cancer Institute Rockville MD 20850 USA Dissemination and Training Division VA National Center for PTSD Palo Alto CA 94305 USA Department of Global Health University of Washington Seattle WA 98105 USA Center for Global Health Studies Fogarty International Center National Institutes of Health Bethesda MD 20912 USA School of Public Health University of Alabama at Birmingham Birmingham AL 35243 USA School of Public Health University of Memphis Memphis TN 38152 USA USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project Bethesda Maryland 20814 USA Institute for Health Research Kaiser Permanente Denver CO 80231 USA ICSI Institute for Clinical Systems Improvement Bloomington MN 55425 USA Medicine University of Chicago Chicago IL 60637 USA Medicine Columbia University Medical Center New York NY 10032 USA Psychiatry Columbia University New York NY 10032 USA General Internal Medicine Epidemiology and Biostatistics University of California San Francisco San Francisco CA 94110 USA New York State Office of Mental Health New York NY 10001 USA Medicine Icahn School of Medicine at Mount Sinai New York NY 10029 USA Center for Health Enhancement System Studies University of Wisconsin Madison WI 53706 USA Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA Psychology University at Buffalo Buffalo NY 14260 USA Department of Psychology West Virginia University Morgantown WV 26506 USA MIRECC VA North Little Rock AR 72114 USA QUERI for Team-Based Behavioral Health Centr

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A COMPUTATIONALLY EFFICIENT SOURCE LOCALIZATION METHOD FOR A MIXTURE OF NEAR-FIELD AND FAR-FIELD NARROWBAND SIGNALS

A COMPUTATIONALLY EFFICIENT SOURCE LOCALIZATION METHOD FOR A...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Weiliang Zuo Jingmin Xin Jiasong Wang Nanning Zheng Akira Sano Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an 710049 China State Key Laboratory of Astronautic Dynamics Xi'an 710043 China Department of System Design Engineering Keio University Yokohama 223-8522 Japan

ISBN: (纸本)9781479928941

In this paper, we consider the source localization for a mixed near-field (NF) and far-field (FF) narrowband signals impinging on a uniform linear array (ULA) with the symmetrical geometric configuration. A computationally efficient direction-of-arrivals (DOAs) and range estimation method for the mixed NF and FF signals is proposed, where the DOAs of the NF and FF signals are estimated separately, and the computationally burdensome eigendecomposition is avoided. Comparing to some existent methods, the proposed method can separate the NF signals from the FF signals more efficiently, and consequently the estimation performance is improved. The effectiveness of the proposed method is verified though numerical examples.

关键词： signals Narrowband near-field Position measurement network file system uniform linear arrays United States Department of Agriculture Logic arrays

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Multi-Objective control of Balancing systems for Li-Ion Battery Packs: A Paradigm Shift?

Multi-Objective Control of Balancing Systems for Li-Ion Batt...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Jorge V. Barreras Claudio Pinto Ricardo de Castro Erik Schaltz Soren J. Andreasen Rui Esteves Araujo Department of Energy Technology Aalborg University Aalborg Denmark INESC TEC (formerly INESC Porto) and Faculty of Engineering University of Porto Porto Portugal Institute of System Dynamics and Control Robotics and Mechatronics Center German Aerospace Center (DLR) Wessling Germany

While a great number of battery balancing circuit topologies have been proposed, the unique control objective typically pursued is equalization of single cell charge. However, a balancing circuit could offer potentially more control features, especially with topologies able to provide bidirectional power flow control. This has not been explored yet in literature or at least not with enough thoroughness. Thus, in addition to charge balancing, up to three more objectives could be pursued simultaneously. Firstly, virtual resistance control, in order to provide dynamic compensation for variations in terminal cell voltage. Secondly, thermal management, to achieve a more uniform temperature distribution within a battery pack. Third, on-board diagnosis or fault detection tools, e.g. to perform characterization tests or to identify and even isolate problematic cells. In this paper, this issue is discussed and evaluated for a battery pack made up of 48 large format Li-Ion cells in series in a e-mobility application. Simulation results demonstrate the technical feasibility of this newly defined concept.

关键词： Batteries system-on-chip Integrated circuit modeling Mathematical model control systems Voltage control Fault detection

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Haptic interfaces for the rescue walking robots motion in the disaster areas

Haptic interfaces for the rescue walking robots motion in th...

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UKACC International Conference on control (control)

作者： Luige Vladareanu Octavian Melinte Adrian Bruja Hongbo Wang Xiaojie Wang Shuang Cang Hongnian Yu Zeng-Guang Hou Xiao-Liang Xie Robotics and Mechatronics Department Institute of Solid Mechanics C-tin Mille 15 Bucharest 1 ROMANIA School of Design Engineering and Computing Boumemouth University Poole Dorset UK Parallel Robot and Mechatronic System Laboratory of Hebei Province University Qinhuangdao CHINA State Key Laboratory of Management and Control for Complex Systems Beijing P.R.CHINA

In the recent years haptic interfaces became a reliable solution in order to solve problems which arise when humans interact with the environment. If in the research area of the haptic interaction between human and environment there are important researches, a innovative approach for the interaction between the robot and the environment using haptic interfaces and virtual projection method is presented in this paper. In order to control this interaction we used the Virtual Projection Method where haptic control interfaces of impedance and admittance will be embedded. The obtained results, validated by simulations assure stability, stiffness, high maneuverability and adaptability for rescue walking robots in order to move in disaster, dangerous and hazardous areas.

关键词： Haptic interfaces Legged locomotion Robot sensing systems Impedance Force

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A Comparative Study between Causal and Non-causal Algorithms for the Energy Management of Hybrid Storage systems

A Comparative Study between Causal and Non-causal Algorithms...

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European Conference on Power Electronics and Applications

作者： Claudio Pinto Ricardo de Castro Rui Esteves Araujo INESC TEC Faculty of Engineering University of Porto Institute of System Dynamics and Control Robotics and Mechatronics Center German Aerospace Center (DLR)

ISBN: (纸本)9781479901159

This paper presents a comparative study between two non-causal algorithms for the energy management problem of electric vehicles, endowed with batteries and supercapacitors (SCs). Toward that goal, an optimization-based energy problem is formulated, which targets the minimization of the source's energy losses throughout a given driving cycle. This problem is solved, firstly, with the help of a fast (but locally optimal) non-linear programming solver;and, secondly, with a slow, but globally optimal, dynamic programming (DP) approach. Simulation results will demonstrate that, despite the different theoretical properties associated with these two solver approaches, both generate similar solutions. In the second part of the work, we will develop a filter-based energy management algorithm, i.e., employ batteries to provide the low-frequency content of the power demand, while SCs cover the high-frequency demand. Our approach builds on the idea of adapting the filter's time constant throughout the vehicle's journey, using, for that purpose, a fuzzy logic algorithm and the information of the state of the vehicle. In comparison with the traditional fixed time-constant approach, the simulation results show that under some conditions the adaptive time-constant algorithm has the potential to reduce the energy losses of the sources by up to 62%.

关键词： Optimisation Energy system management Electric vehicle Hybrid power integration Supercapacitor

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Estimation of the number of narrowband signals in the presence of multipath propagation

Estimation of the number of narrowband signals in the presen...

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2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, SAM 2012

作者： Tao, Hao Xin, Jingmin Jiasong Wang Zheng, Nanning Sano, Akira Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an 710049 China State Key Laboratory of Astronautic Dynamics Xi'an 710043 China Department of System Design Engineering Keio University Yokohama 223-8522 Japan

ISBN: (纸本)9781467310710

In this paper, we address with the problem of detection the number of narrowband signals impinging on a uniform linear array (ULA) in the presence of multipath propagation. Firstly, by forming a differencing matrix from the array covariance matrix to eliminate the effects of uncorrelated incident signals and additive noises, a combined matrix is constructed from this differencing matrix to decorrelate the coherence of signals. Since the number of coherent signals is revealed as the rank of this resultant matrix, a singular value based ratio criterion is proposed to estimate the number of coherent signals. Then, another singular value based ratio criterion is also presented to determine the number of uncorrelated signals from the array covariance matrix. The notable advantage of the proposed method is that it can detect more signals compared to some existing methods, and the number of signals resolved by our method can exceed the number of array sensors. © 2012 IEEE.

关键词： Additive noise

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