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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

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NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

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Multi-robot coordination through dynamic Voronoi partitioning for informative adaptive sampling in communication-constrained environments

Multi-robot coordination through dynamic Voronoi partitionin...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Stephanie Kemna John G. Rogers Carlos Nieto-Granda Stuart Young Gaurav S. Sukhatme Department of Computer Science University of Southern California Los Angeles CA USA United States Army Research Laboratory Adel-ph MD USA Robotics and Intelligent Machines Georgia Institute of Technology Atlanta GA USA

Autonomous underwater vehicles (AUVs) are cost- and time-efficient systems for environmental sampling. Informative adaptive sampling has been shown to be an effective method of sampling a lake or ocean for environmental modeling. In this paper, we focus on multi-robot coordination for informative adaptive sampling. We use a dynamic Voronoi partitioning approach whereby the vehicles, in a decentralized fashion, repeatedly calculate weighted Voronoi partitions for the space. Each vehicle then runs informative adaptive sampling within their partition. The vehicles can request surfacing events to share data between vehicles. Simulation results show that the addition of the coordination with dynamic Voronoi partitioning results in obtaining higher quality models faster. Thus we created a decentralized, multi-robot coordination approach for informative, adaptive sampling of unknown environments.

关键词： Robot kinematics Adaptation models Vehicle dynamics Entropy Density functional theory Robot sensing systems

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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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Self-folded soft robotic structures with controllable joints

Self-folded soft robotic structures with controllable joints

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IEEE International Conference on robotics and Automation (ICRA)

作者： Cynthia Sung Rhea Lin Shuhei Miyashita Sehyuk Yim Sangbae Kim Daniela Rus Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA Department of Electronics University of York York UK Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA USA Robotics and Media Institute Korea Institute of Science and Technology Seoul South Korea

This paper describes additive self-folding, an origami-inspired rapid fabrication approach for creating actuatable compliant structures. Recent work in 3-D printing and other rapid fabrication processes have mostly focused on rigid objects or objects that can achieve small deformations. In contrast, soft robots often require elastic materials and large amounts of movement. Additive self-folding is a process that involves cutting slices of a 3-D object in a long strip and then pleat folding them into a likeness of the original model. The zigzag pattern for folding enables large bending movements that can be actuated and controlled. Gaps between slices in the folded model can be designed to provide larger deformations or higher shape accuracy. We advance existing planar fabrication and self-folding techniques to automate the fabrication process, enabling highly compliant structures with complex 3-D geometries to be designed and fabricated within a few hours. We describe this process in this paper and provide algorithms for converting 3-D meshes into additive self-folding designs. The designs can be rapidly instrumented for global control using magnetic fields or tendon-driven for local bending. We also describe how the resulting structures can be modeled and their responses to tendon-driven control predicted. We test our design and fabrication methods on three models (a bunny, a tuna fish, and a starfish) and demonstrate the method's potential for actuation by actuating the tuna fish and starfish models using tendons and magnetic control.

关键词： Fabrication Additives Geometry Algorithm design and analysis Robots Strips Tendons

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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

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Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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Study of the flexibility of a learning analytics tool to evaluate teamwork competence acquisition in different contexts

Study of the flexibility of a learning analytics tool to eva...

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2017 Learning Analytics Summer Institute Spain: Advances in Learning Analytics, LASI-SPAIN 2017

作者： Conde, Miguel Ángel García-Peñalvo, Francisco J. Fidalgo-Blanco, Ángel Sein-Echaluce, María Luisa Department of Mechanics Computer Science and Aerospace Engineering Robotics Group University of León - Campus de Vegazana S/N León24071 Spain Research Institute for Educational Sciences GRIAL research group Faculty of Science - Plaza de Los Caídos S/N. 37008 Salamanca University of Salamanca Spain Laboratory of Innovation in Information Technologies Politechnical University of Madrid Calle de Ríos Rosas 21 Madrid28003 Spain Department of Applied Mathematics Campus Rio Ebro University of Zaragoza Calle de María de Luna 3 Zaragoza50018 Spain

Learning analytics tools and methodologies aim to facilitate teachers and/or decision makers with information and knowledge about what is happening in virtual learning environments in a straightforward and effortless way. However, it is necessary to apply these tools and methodologies in different contexts with a similar success, that is, that they should be flexible and portable enough. There exist several learning analytics tools that only works properly with very specific versions of learning platforms. In this paper, the authors aim to evaluate the flexibility and portability of a methodology and a learning analytics tool that supports individual assessment of teamwork competence. In order to do so the methodology and the tool are applied in a similar course from two different academic contexts. After the experiment, it is possible to see that the learning analytics tool seems to work properly and the suggested new functionalities are similar in both contexts. The methodology can be also applied but results could be improved if some meetings are carried out to check how team works are progressing with their tasks.

关键词： computer aided instruction

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Author Correction: Observation of an ultra-high-energy cosmic neutrino with KM3NeT

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Nature 2025年第8057期640卷 E3页

作者： S. Aiello R. Bruno G. Ferrara E. Leonora F. Longhitano N. Randazzo A. Sinopoulou I. Tosta e Melo A. Albert D. Drouhin T. Pradier A. R. Alhebsi S. Thoudam A. van Vliet M. Alshamsi V. Bertin M. Breuhaus J. Brunner J. Busto L. Cerisy P. Coyle B. De Martino D. Dornic J.-G. Ducoin A. Enzenhöfer S. Henry D. Joly S. Lancelin S. Le Stum N. Lumb F. Magnani C. Paries M. Perrin-Terrin G. Vannoye S. Alves Garre A. Bariego-Quintana D. Calvo V. Cecchini A. Garcia Soto S. R. Gozzini J. J. Hernández-Rey A. Lazo N. Lessing J. Palacios González E. J. Pastor Gomez J. Prado D. Real A. Šaina F. Salesa Greus A. Sánchez Losa J. D. Zornoza J. Zúñiga A. Ambrosone M. Bendahman M. Benhassi C. Bozza R. M. Bozza R. Buompane A. Condorelli A. De Benedittis L. A. Fusco L. Gialanella W. Idrissi Ibnsalih A. Manfreda A. Marinelli F. Marzaioli S. Mastroianni G. Miele P. Migliozzi M. L. Mitsou C. M. Mollo L. Morales-Gallegos M. R. Musone V. Oliviero C. Poirè I. C. Rea A. Simonelli B. Spisso D. Vivolo F. Ameli A. Capone S. Celli I. Di Palma S. Gagliardini M. Mastrodicasa C. A. Nicolau A. Tudorache A. Veutro A. Zegarelli M. Andre M. Anghinolfi F. Badaracco B. Caiffi V. Ellajosyula C. Guidi V. Kulikovskiy L. Malerba M. Marconi B. Ó Fearraigh V. Parisi A. Romanov M. Sanguineti M. Taiuti S. Zavatarelli L. Aphecetche F. Bretaudeau R. Dallier V. Decoene L. Martin M. Ardid S. Ardid J. García Méndez C. A. Quiroz-Rangel C. Argüelles N. Kamp A. Y. Wen H. Atmani J. Boumaaza A. Eddymaoui Y. Tayalati J. Aublin B. Baret Y. Becherini T. Cartraud J. A. B. Coelho A. Coleiro S. Colonges A. Creusot C. Donzaud M. Eff S. El Hedri I. Goos P. Goswami A. Ilioni A. Kouchner M. Lindsey Clark E. Oukacha S. Peña Martínez R. Pestes A. Sharma B. Trocmé V. Van Elewyck C. Verilhac I. Lhenry-Yvon L. Bailly-Salins M. Bennani B. Guillon M. Labalme C. Lastoria G. Lehaut I. Mozun Mateo V. Pestel A. Vacheret Z. Bardačová E. Eckerová F. Mamedov Y. Shitov I. Štekl R. Dvornický F. Šimkovic F. Benfenati Gualandi F. Carenini P. Castaldi T. Chiarusi I. Del Rosso G. Levi A. Margiotta R. Muller INFN Sezione di Catania (INFN-CT) Catania Italy INFN Laboratori Nazionali del Sud (LNS) Catania Italy Dipartimento di Fisica e Astronomia “Ettore Majorana” Università di Catania (INFN-CT) Catania Italy Université de Strasbourg CNRS IPHC UMR 7178 Strasbourg France Université de Haute Alsace Mulhouse France Department of Physics Khalifa University Abu Dhabi United Arab Emirates Aix Marseille Université CNRS/IN2P3 CPPM Marseille France IFIC - Instituto de Física Corpuscular (CSIC - Universitat de València) Paterna Spain INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Napoli Italy Università di Napoli “Federico II” Dip. Scienze Fisiche “E. Pancini” Complesso Universitario di Monte S. Angelo Napoli Italy Dipartimento di Matematica e Fisica Università degli Studi della Campania “Luigi Vanvitelli” Caserta Italy Dipartimento di Fisica Università di Salerno e INFN Gruppo Collegato di Salerno Fisciano Italy INFN Sezione di Roma Roma Italy Dipartimento di Fisica Università La Sapienza Roma Italy Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Universitat Politècnica de Catalunya Vilanova i la Geltrú Spain INFN Sezione di Genova Genova Italy Università di Genova Genova Italy LPC CAEN Normandie Université ENSICAEN UNICAEN CNRS/IN2P3 Caen France Subatech IMT Atlantique IN2P3-CNRS Nantes Université Nantes France Instituto de Investigación para la Gestión Integrada de las Zonas Costeras Universitat Politècnica de València Gandia Spain Department of Physics Harvard University Cambridge MA USA Laboratory for Particle Physics and Cosmology Lyman Laboratory Harvard University Cambridge MA USA Faculty of Sciences University Mohammed V in Rabat Rabat Morocco Institute of Applied Physics Mohammed VI Polytechnic University Ben Guerir Morocco Astroparticule et Cosmologie Université Paris Cité CNRS Paris France Institut Universitaire de France Paris France Institute of Experimental and Applied Physics

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A novel extended potential field controller for use on aerial robots

A novel extended potential field controller for use on aeria...

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2016 IEEE International Conference on Automation science and Engineering, CASE 2016

作者： Woods, Alexander C. Lay, Hung M. Ha, Quang P. Advanced Robotics and Automation Laboratory Department of Computer Science and Engineering University of Nevada RenoNV89557 United States School of Electrical Mechanical and Mechatronic Systems University of Technology Sydney Australia

ISBN: (纸本)9781509024094

Unmanned Aerial Vehicles (UAV), commonly known as drones, have many potential uses in real world applications. Drones require advanced planning and navigation algorithms to enable them to safely move through and interact with the world around them. This paper presents an extended potential field controller (ePFC) which enables an aerial robot, or drone, to safely track a dynamic target location while simultaneously avoiding any obstacles in its path. The ePFC outperforms a traditional potential field controller (PFC) with smoother tracking paths and shorter settling times. The proposed ePFC's stability is evaluated by Lyapunov approach, and its performance is simulated in a Matlab environment. Finally, the controller is implemented on an experimental platform in a laboratory environment which demonstrates the effectiveness of the controller. © 2016 IEEE.

关键词： Controllers

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A hybrid model and kinematic-free control framework for a low-cost deformable manipulator using in home service

A hybrid model and kinematic-free control framework for a lo...

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2016 IEEE International Conference on Automation science and Engineering, CASE 2016

作者： Li, Gaofeng Sun, Lei Xu, Shan Song, Dezhen Liu, Jingtai Institute of Robotics and Automatic Information System NanKai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics NanKai University Tianjin300350 China Department of Computer Science and Engineering Texas A and M University College StationTX77843 United States

ISBN: (纸本)9781509024094

Home service robot works in unstructured environments with various tasks, where a low-cost, dexterous, and intrinsically safe manipulator is important. Traditionally, a redundant manipulator with high degrees of freedom (DOFs) is employed. However, high DOFs bring problems like high cost, complex physical designing, and heavy weight. Here a novel low-cost deformable manipulator for home service robot, which is composed of rigid joints and deformable links, is introduced. The deformable manipulator can obtain relatively dexterous and extended workspace with fewer joints by bending its deformable links. Considering the typical hybrid behaviors caused by bending operation, a hybrid model and a practical kinematic-free control framework with no prior kinematic information are proposed to describe and control the deformable manipulator. The model and controller have been implemented on a 4-DOF deformable manipulator with two deformable links in simulation. The simulation results validate the proposed deformable manipulator and kinematic-free control. © 2016 IEEE.

关键词： Manipulators

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Co-robotic synthetic tracked aperture ultrasound imaging with cross-correlation based dynamic error compensation and virtual fixture control

Co-robotic synthetic tracked aperture ultrasound imaging wit...

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IEEE Symposium (IUS) Ultrasonics

作者： Haichong K. Zhang Rodolfo Finocchi Kalyna Apkarian Emad M. Boctor Department of Computer Science Laboratory of Computer Sensor and Robotics Department of Radiology The Johns Hopkins University Baltimore USA

ISBN: (纸本)9781467398985

Acquiring high resolution images in deep regions is challenging in ultrasound imaging due to limited probe aperture size and low transmit frequency usage. The concept of synthetic tracked aperture ultrasound (STRATUS) imaging is introduced to extend the effective aperture size by moving the probe while accurately tracking its orientation and translation. Based on the synthetic aperture technique, sub-apertures from each pose can be synthesized to construct a high-resolution image. In particular, we propose a mechanical tracking configuration using a 6 degree-of-freedom (DOF) robotic arm with force sensors that not only provides a robust tracking accuracy, but also enables co-operative control. The ultrasound probe is moved by an operator, while a virtual fixture uses force feedback of the robotic arm to constrain the motion to be on a desired plane or trajectory. Furthermore, we developed an algorithm to mitigate the potential errors between consecutive poses, such as tracking inaccuracy, tissue deformation, and phase aberration. Those errors were extracted by computing subtle image shift through cross-correlation for all neighboring poses, and the procedure is dynamically applied to the entire image. Comparing the STRATUS image to a conventional single pose image, the full width at the half maximum (FWHM) of a point target located at a depth of around 85 mm improved from 3.13 mm to 2.78 mm, and SNR improved from 28.96 dB to 30.27 dB. In addition, the dynamic error compensation further improved the FWHM and SNR to be 1.15 mm and 33.17 dB, respectively. The results proved the feasibility of the co-robotic STRATUS imaging, and dynamic error compensation improved the system's tolerance to errors.

关键词： Ultrasonic imaging Probes Apertures Robot sensing systems Imaging Robot kinematics

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