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IEEE International Conference on robotics and Automation

作者： Spyros Maniatopoulos Philipp Schillinger Vitchyr Pong David C. Conner Hadas Kress-Gazit Verifiable Robotics Research Group Sibley School of Mechanical and Aerospace Engineering Cornell University Ithaca NY 14853 USA Robert Bosch GmbH Corporate Research Department for Cognitive Systems 70442 Stuttgart Germany Capable Humanitarian Robotics & Intelligent Systems Lab Department of Physics Computer Science and Engineering Christopher Newport University Newport News VA 23606 USA

ISBN: (纸本)9781467380270

In this work, we take a step towards bridging the gap between the theory of formal synthesis and its application to real-world, complex, robotic systems. In particular, we present an end-to-end approach for the automatic generation of code that implements high-level robot behaviors in a verifiably correct manner, including reaction to the possible failures of low-level actions. We start with a description of the system defined a priori. Thus, a non-expert user need only specify a high-level task. We automatically construct a formal specification, in a fragment of Linear Temporal Logic (LTL), that encodes the system's capabilities and constraints, the task, and the desired reaction to low-level failures. We then synthesize a reactive mission plan that is guaranteed to satisfy the formal specification, i.e., achieve the task's goals or correctly react to failures. Lastly, we automatically generate a state machine that instantiates the synthesized symbolic plan in software. We showcase our approach using Team ViGIR's software and Atlas humanoid robot and present lab experiments, thus demonstrating the application of formal synthesis techniques to complex robotic systems. The proposed approach has been implemented and open-sourced as a collection of Robot Operating System (ROS) packages, which are adaptable to other systems.

关键词： Atlas Humanoid Robot formal synthesis ROS

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Guest-editorial computer-based intelligent technologies for improving the quality of life

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IEEE Journal of Biomedical and Health Informatics 2015年第1期19卷 4-5页

作者： Mozos, Oscar Martinez Galindo, Cipriano Tapus, Adriana School of Computer Science University of Lincoln LincolnLN6 7TS United Kingdom System Engineering and Automation Department University of Malaga Malaga29071 Spain Robotics and Computer Vision Lab ENSTA-ParisTech Palaiseau91120 France

The eight papers in this special section focus on computer-based intelligent technologies for improving the quality of life.

关键词： Special issues and sections Electroencephalography Collision avoidance Assistive technology Mobile radio mobility management Robot monitoring Brain-computer interfaces

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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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Active tactile object exploration with Gaussian processes

Active tactile object exploration with Gaussian processes

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Zhengkun Yi Roberto Calandra Filipe Veiga Herke van Hoof Tucker Hermans Yilei Zhang Jan Peters Intelligent Autonomous Systems Lab Department of Computer Science Technische Universitat Darmstadt Hochschulstr. 10 64289 Germany School of Mechanical and Aerospace Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 University of Utah Robotics Center School of Computing University of Utah USA

ISBN: (纸本)9781509037636

Accurate object shape knowledge provides important information for performing stable grasping and dexterous manipulation. When modeling an object using tactile sensors, touching the object surface at a fixed grid of points can be sample inefficient. In this paper, we present an active touch strategy to efficiently reduce the surface geometry uncertainty by leveraging a probabilistic representation of object surface. In particular, we model the object surface using a Gaussian process and use the associated uncertainty information to efficiently determine the next point to explore. We validate the resulting method for tactile object surface modeling using a real robot to reconstruct multiple, complex object surfaces.

关键词： Gaussian processes Touch tactile sensors grid point

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Easy-to-use, General, and Accurate Multi-Kinect Calibration and its Application to Gait Monitoring for Fall Prediction

Easy-to-use, General, and Accurate Multi-Kinect Calibration ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Aaron N. Staranowicz Christopher Ray Gian-Luca Mariottini the ASTRA Robotics Lab at the Department of Computer Science and Engineering University of Texas at Arlington 500 UTA Boulevard Arlington TX 76019 USA the Department of Kinesiology University of Texas at Arlington 500 West Nedderman Drive Arlington TX 76019 USA

ISBN: (纸本)9781424492695

Falls are the most-common causes of unintentional injury and death in older adults. Many clinics, hospitals, and health-care providers are urgently seeking accurate, low-cost, and easy-to-use technology to predict falls before they happen, e.g., by monitoring the human walking pattern (or "gait"). Despite the wide popularity of Microsoft's Kinect and the plethora of solutions for gait monitoring, no strategy has been proposed to date to allow non-expert users to calibrate the cameras, which is essential to accurately fuse the body motion observed by each camera in a single frame of reference. In this paper, we present a novel multi-Kinect calibration algorithm that has advanced features when compared to existing methods: 1) is easy to use, 2) it can be used in any generic Kinect arrangement, and 3) it provides accurate calibration. Extensive real-world experiments have been conducted to validate our algorithm and to compare its performance against other multi-Kinect calibration approaches, especially to show the improved estimate of gait parameters. Finally, a MATlab Toolbox has been made publicly available for the entire research community.

关键词： Easy-to-use General Fall Prediction

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DWT-DCT based individuals identification using robust gait feature images

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2015年第4期8卷 113-124页

作者： Ibrahim Khalilullah, K.M. Hossain, Delowar Hamid, Ekramul Department of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka Bangladesh Intelligent Robotics Lab Department of Electrical and Electronics System Engineering University of Toyama Japan Department of Computer Science and Engineering University of Rajshahi Rajshahi Bangladesh

Individual identification at a distance using gait features has newly gained growing interest from biometrics researchers. Most of the researchers have been shown that different covariate factors can affect different parts of the human body. In this paper, we propose a new approach that minimizes these difficulties, especially for carrying objects by combining static, dynamic, and part-based features. The Gait Features of the walking sequences are extracted by selecting only four sub bands of the Discrete Wavelet Transform (DWT) of the individual images. Moreover, Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT) are implemented to extract lowest and middle frequency components that are used to create robust gait feature images (RGFIs). Then we select effective parts of the body from the Robust Gait Feature Images. After that, these parts of the body are trained using Principal Component Analysis (PCA) and Multiple Discriminant Analysis (MDA) to identify individuals. Experimental result shows promising performance in comparison with other methods. © 2015 SERSC.

关键词： Discrete cosine transforms

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROscience 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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Assisting Blind People to Avoid Obstacles: An Wearable Obstacle Stereo Feedback System Based on 3D Detection

Assisting Blind People to Avoid Obstacles: An Wearable Obsta...

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IEEE International Conference on robotics and Biomimetics

作者： Bing Li Xiaochen Zhang J. Pablo Mu?oz Jizhong Xiao Xuejian Rong Yingli Tian Electrical Engineering Department CCNY Robotics Lab The City College The City University of New York NY 10031 USA Computer Science Department at Graduate Center of The City University of New York and CCNY Robotics Lab NY 10031 USA Electrical Engineering Department CCNY Media Lab The City College The City University of New York NY 10031 USA

ISBN: (纸本)9781467396769

A wearable Obstacle Stereo Feedback (OSF) System for the Blind people based on 3D space obstacle detection is presented to assist the navigation. The OSF system embedded with a depth sensor to perceive the in-front 3D spatial information in the form of point clouds. We implemented the downsampling Random Sample Consensus (RANSAC) algorithm to process the perceived point cloud, and detect the obstacles in front of the user. Finally, Head-Related Transfer Functions (HRTF) are applied to create the virtual stereo sound which represents the obstacles according to its coordinate in the 3D space. The experiment shows that OSF system can detect the obstacle in the indoor environment effectively and provides a feasible auditory perception to indicate the in-front safety zone for the blind user.

关键词： OSF RANSAC indoor environment

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Safety challenges in using *** to collaborate with humans in indoor environments 14

Safety challenges in using *** to collaborate with humans in...

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7th ACM International Conference on Pervasive Technologies Related to Assistive Environments, PETRA 2014

作者： Lioulemes, Alexandros Galatas, Georgios Metsis, Vangelis Mariottini, Gian Luca Makedon, Fillia Heracleia Laboratory Department of Computer Science and Engineering University of Texas at Arlington ArlingtonTX76015 United States ASTRA Robotics Lab. Department of Computer Science and Engineering University of Texas at Arlington ArlingtonTX76015 United States

ISBN: (纸本)9781450327466

This paper presents an Unmanned Aerial Vehicle (UAV), based on the AR. Drone platform, which can perform an autonomous navigation in indoor (e.g. corridor, hallway) and industrial environments (e.g. production line). It also has the ability to avoid pedestrians while they are working or walking in the vicinity of the robot. The only sensor in our system is the front camera. For the navigation part our system rely on the vanishing point algorithm, the Hough transform for the wall detection and avoidance, and the HOG descriptors for pedestrian detection using SVM classifier. Our experiments show that our vision navigation procedures are reliable and enable the aerial vehicle to y without humans intervention and coordinate together in the same workspace. We are able to detect human motion with high confidence of 85% in a corridor and to confirm our algorithm in 80% successful fight experiments. Copyright is held by the owner/author(s).

关键词： Drones

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Motion-oriented attention for a social gaze robot behavior 6

Motion-oriented attention for a social gaze robot behavior

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6th International Conference on Social robotics, ICSR 2014

作者： Sorostinean, Mihaela Ferland, François Dang, Thi-Hai-Ha Tapus, Adriana Computer Vision and Robotics Lab Computer Science and System Engineering Department ENSTA-ParisTech Palaiseau France

ISBN: (纸本)9783319119724

Various studies have shown that human visual attention is generally attracted by motion in the field of view. In order to embody this kind of social behavior in a robot, its gaze should focus on key points in its environment, such as objects or humans moving. In this paper, we have developed a social natural attention system and we explore the perception of people while interacting with a robot in three different situations: one where the robot has a totally random gaze behavior, one where its gaze is fixed on the person in the interaction, and one where its gaze behavior adapts to the motion-based environmental context. We conducted an online survey and an on-site experiment with the Meka robot so as to evaluate people’s perception towards these three types of gaze. Our results show that motion-oriented gaze can help to make the robot more engaging and more natural to people. © Springer International Publishing Switzerland 2014.

关键词： Robots

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