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International Journal of Social robotics 2019年第6期15卷 1077-1077页

作者： Ge, Shuzhi Sam Wykowska, Agnieszka Khatib, Oussama Social Robotics Laboratory Smart Systems Institute Department of Electrical and Computer Engineering The National University of Singapore Singapore Singapore Institute for Future (IFF) Qingdao University Qingdao China Centre for Robotics UESTC Chengdu China Social Cognition in Human-Robot Interaction Istituto Italiano di Tecnologia Genoa Italy Artificial Intelligence Laboratory Department of Computer Science Stanford University Stanford USA

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Compositional transient stability analysis of power systems via the computation of reachable sets

Compositional transient stability analysis of power systems ...

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American Control Conference

作者： Ahmed El-Guindy Yu Christine Chen Matthias Althoff Institute of Robotics and Embedded Systems Technische Universitat Munchen Department of Electrical and Computer Engineering at the University of British Columbia

ISBN: (纸本)9781509045839

The main challenge associated with the analysis of power systems via the computation of reachable sets is improving the algorithmic efficiency to scale towards industrially relevant problem sizes. In this paper, we present a compositional algorithm that can drastically reduce the computational effort required to assess the dynamical response of power systems during transients using reachability analysis. The main reason for the algorithmic efficiency is that we reformulate the transmission network into a set of subsystems, each consisting of a synchronous generator connected to a generator bus, whose algebraic constraints are unknown-but-bounded within some confidence intervals. This makes it possible to parallelize the computation of reachable sets for transient stability analysis and, more importantly, preserve the interaction and correlation between different machines connected to the grid. The applicability of the proposed compositional algorithm is illustrated on several benchmark examples and compared to other algorithms that compute the reachable set without employing any compositional techniques.

关键词： Transient stability analysis Dynamic security assessment Power systems Reachability analysis power systems transient stability reachability analysis dynamic security assessment transmission networks Stability analysis

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3D point cloud downsampling for 2D indoor scene modelling in mobile robotics

3D point cloud downsampling for 2D indoor scene modelling in...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Luís Garrote José Rosa João Paulo Cristiano Premebida Paulo Peixoto Urbano J. Nunes Institute of Systems and Robotics Electrical and Computer Engineering Department University of Coimbra Coimbra Portugal Universidade de Coimbra Coimbra Coimbra PT

Sensory perception and environment modelling are important for autonomous navigation in mobile robotics. 2D discrete grid representations such as the classic 2D occupancy grid maps are a widely used technique in scene representation because of the inherent simplicity and compact representation. In recent years, many 2.5D and 3D grid-based methods have been proposed however, as for the 2D case, a compromise between keeping a low computational bound and reliable sensor interpretation must be kept in order to perform real-world tasks. Assuming the input data in the form of a 3D point-cloud, in this paper we propose a 2D scene modelling approach which converts the 3D data to a 2.5D representation and then to a 2D grid map in an efficient and meaningful manner. The proposed approach incorporates a new rapidly exploring random tree inspired ground-plane detection (RRT-GPD), and an inverse sensor model (ISM) to correctly map 3D to 2.5D and then to 2D grid cells. Experiments were conducted in indoor scenarios with a robotic walker platform equipped with a Microsoft's Kinect One and a LeddarTech's Leddar IS16 sensor. Reported results show an improvement on the representation of non-trivial obstacles (stairs, floor outlets) over a ROS package solution, when applied to a 3D point cloud input.

关键词： Three-dimensional displays Two dimensional displays Robot sensing systems Solid modeling Computational modeling Mobile communication

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Integrating Artificial Intelligence with Real-time Intracranial EEG Monitoring to Automate Interictal Identification of Seizure Onset Zones in Focal Epilepsy

arXiv

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arXiv 2018年

作者： Varatharajah, Yogatheesan Berry, Brent Cimbalnik, Jan Kremen, Vaclav van Gompel, Jamie Stead, Matt Brinkmann, Benjamin Iyer, Ravishankar Worrell, Gregory Electrical and Computer Engineering University of Illinois UrbanaIL61801 United States Mayo Systems Electrophysiology Laboratory Department of Neurology Mayo Clinic RochesterMN55905 United States Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6166 36 Czech Republic Department of Neurosurgery Mayo Clinic RochesterMN55905 United States Department of Physiology & Biomedical Engineering Mayo Clinic RochesterMN55905 United States

An ability to map seizure-generating brain tissue, i.e., the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between ninety minutes and two hours are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in

关键词： Support vector machines

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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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Wheels for staircases 12th

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12th Portuguese Conference on Automatic Control, CONTROLO 2016

作者： Leite, Fátima Silva Batista, Jorge Krakowski, Krzysztof Carvalho, André Cruz, Tiago Domingues, Eduardo Lizardo, André Saraiva, Gonçalo Institute of Systems and Robotics University of Coimbra Coimbra3030-290 Portugal Department of Mathematics University of Coimbra Coimbra3001-501 Portugal Department of Electrical Engineering and Computers University of Coimbra Coimbra3030-290 Portugal Wydzial Matematyczno-Przyrodniczy Uniwersytet Kardynala Stefana Wyszyńskiego ul. Dewajtis 5 Warsaw01-815 Poland Department of Informatics Engineering University of Coimbra Coimbra3030-290 Portugal Department of Electrical Engineering and Computers University of Lisbon Lisboa1049-001 Portugal

ISBN: (纸本)9783319436708

Our objective is to design innovative robot wheels capable of rolling on staircases, without sliding and without bouncing. This is the first step to reach the ultimate goal of building wheelchairs capable to overcome the obstacles imposed by staircases on people with limited mobility. We show that, given a staircase with equal steps, there is an infinite number of wheels that roll over it, with the constraints of no-sliding and no-bouncing. Some of these wheels appear to be very interesting for real applications. We also present an algorithm for the construction of a wheel, which depends only on the measures of the tread (the part of the staircase that is stepped on) and the riser (the vertical portion between each tread) of the step. © Springer International Publishing Switzerland 2017.

关键词： Wheels

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Non-uniform time-scaling of carnatic music transients

arXiv

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arXiv 2017年

作者： Viraraghavan, Venkata Subramanian Pal, Arpan Aravind, R. Murthy, Hema TCS Research and Innovation Embedded Systems and Robotics Bangalore India Department of Electrical Engineering Indian Institute of Technology Madras Singapore Department of Computer Science and Engineering Indian Institute of Technology Madras India

Gamakas are an integral aspect of Carnatic Music, a form of classical music prevalent in South India. They are used in rāgas, which may be seen as melodic scales and/or a set of characteristic melodic phrases. Gamakas exhibit continuous pitch variation often spanning several semitones. In this paper, we study how gamakas scale with tempo and propose a novel approach to change the tempo of Carnatic music pieces. The music signal is viewed as consisting of constant-pitch segments and transients. The transients show continuous pitch variation and we consider their analyses from a theoretical stand-point. We next observe the non-uniform ratios of time-scaling of constantpitch segments, transients and silence in excerpts from nine concert renditions of varn. ams in six rāgas. The results indicate that the changing tempo of Carnatic music does not change the duration of transients significantly. We report listening tests on our algorithm to slow down Carnatic music that is consistent with this observation. Copyright © 2017, The Authors. All rights reserved.

关键词： Music

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Algorithms for joint operation of service robotic platform and set of UAVs in agriculture tasks 5

Algorithms for joint operation of service robotic platform a...

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5th IEEE Workshop on Advances in Information, Electronic and electrical engineering, AIEEE 2017

作者： Vu, Quyen Nguyen, Vinh Solenaya, Oksana Ronzhin, Andrey Mehmet, H. Department of Electromechanics and Robotics Saint Petersburg State University of Aerospace Instrumentation SUAI St. Petersburg Russia Laboratory of Autonomous Robotic Systems St. Petersburg Institute for Informatics and Automation Russian Academy of Sciences SPIIRAS St. Petersburg Russia Guzey Department of Electrical and Electronics Engineering Erzurum Technical University Erzurum Turkey

ISBN: (纸本)9781538641378

The problems of designing a mobile robotic platform carrying a set of unmanned aerial vehicles and containing a container for a payload are considered. The issues of transportation of robots and joint activity of robots with various functions in solving agriculture problems are discussed. The conceptual model of a mobile platform design is given. The main stages of the algorithmic model of the joint operation of the mobile platform and the set of unmanned aerial vehicles brought to the working area are described. © 2017 IEEE.

关键词： Manipulators

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Deep EndoVO: A recurrent convolutional neural network (RCNN) based visual odometry approach for endoscopic capsule robots

arXiv

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arXiv 2017年

作者： Turan, Mehmet Almalioglu, Yasin Araujo, Helder Konukoglu, Ender Sitti, Metin Physical Intelligence Department Max Planck Institute for Intelligent Systems Germany Computer Engineering Department Bogazici Univesity Turkey Institute for Systems and Robotics Universidade de Coimbra Portugal Computer Vision Laboratory Department of Information Technology and Electrical Engineering ETH Zurich Switzerland

Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Medical device companies and many research groups have recently made substantial progresses in converting passive capsule endoscopes to active capsule robots, enabling more accurate, precise, and intuitive detection of the location and size of the diseased areas. Since a reliable real time pose estimation functionality is crucial for actively controlled endoscopic capsule robots, in this study, we propose a monocular visual odometry (VO) method for endoscopic capsule robot operations. Our method lies on the application of the deep Recurrent Convolutional Neural Networks (RCNNs) for the visual odometry task, where Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are used for the feature extraction and inference of dynamics across the frames, respectively. Detailed analyses and evaluations made on a real pig stomach dataset proves that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories. Copyright © 2017, The Authors. All rights reserved.

关键词： Vision

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Low cost vision system for human gait acquisition and characterization

Low cost vision system for human gait acquisition and charac...

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2016 International Conference on Industrial engineering and engineering Management, IEEM 2016

作者： Ferreira, Paulo A. Ferreira, João P. Crisóstomo, Manuel Coimbra, A. Paulo Institute of Systems and Robotics Dept. of Electrical and Computer Engineering University of Coimbra Portugal Department of Electrical Engineering Superior Institute of Engineering of Coimbra Coimbra Portugal

ISBN: (纸本)9781509036653

This paper presents a low cost system for human gait analysis. Two opposite-faced web cameras are used to acquire images of the walking of a person carrying a set of passive marks, where the color is chosen to contrast with the ambient dominant color. It is also used a treadmill with passive marks, where the user walks at different speeds. The acquired trajectories of the marks are used to determine body joint angles and other 3D crossed angles, obtained by both opposite sides from video images processing. With this low cost measurement system the analysis and reconstruction of human gait can be done with a mean error of 2 degrees, becoming a good alternative to more expensive systems to be used in human gait characterization. The system can be used to detect human gait pathologies and to accomplish physical rehabilitation. © 2016 IEEE.

关键词： Cost benefit analysis

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