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    Authors: Rolinat, Clément; Grossard, Mathieu; Aloui, Saifeddine; Godin, Christelle;

    Grasp planning and most specifically the grasp space exploration is still an open issue in robotics. This article presents a data-driven oriented methodology to model the grasp space of a multi-fingered adaptive gripper for known objects. This method relies on a limited dataset of manually specified expert grasps, and uses variational autoencoder to learn grasp intrinsic features in a compact way from a computational point of view. The learnt model can then be used to generate new non-learnt gripper configurations to explore the grasp space. Comment: accepted at SYSID 2021 conference

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    arXiv.org e-Print Archive
    Other literature type . Preprint . 2021
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    Article . 2021 . Peer-reviewed
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    Article . 2021
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    https://doi.org/10.48550/arxiv...
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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      arXiv.org e-Print Archive
      Other literature type . Preprint . 2021
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    Authors: Alemanno, Alberto;

    The European response to COVID-19 has revealed an inconvenient truth. Despite having integrated public health concerns across all its policies – be it agriculture, consumer protection, or security –, the Union cannot directly act to save people’s lives. Only member states can do so. Yet when they adopted unilateral measures to counter the spread of the virus, those proved not only ineffective but also disruptive on vital supply chains, by ultimately preventing the flow of essential goods and people across the Union. These fragmented efforts in tackling cross-border health threats have almost immediately prompted political calls for the urgent creation of a European Health Union. Yet this call raises more questions than answers. With the aim to offer a rigorous and timely blueprint to decision-makers and the public at large, this Special Issue of the European Journal of Risk Regulation contextualizes such a new political project within the broader constitutional and institutional framework of EU public health law and policy. By introducing the Special, this paper argues that unless the envisaged Health Union will tackle the root causes of what prevented the Union from effectively responding to COVID-19 – the divergent health capacity across the Union –, it might fall short of its declared objective of strengthening the EU’resilience for cross-border health threats.

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    European Journal of Risk Regulation
    Article . 2020 . Peer-reviewed
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    SSRN Electronic Journal
    Article . 2020 . Peer-reviewed
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      European Journal of Risk Regulation
      Article . 2020 . Peer-reviewed
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    Authors: Lu, Jinzhi; Zheng, Xiaochen; Gharaei, Ali; Kalaboukas, Kostas; +1 Authors

    Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for identifying the dynamics of virtual model evolution, promoting the understanding of interrelationships between virtual models and enhancing the decision-making based on DT. The CT ensures that assets of Internet of Things (IoT) systems are well-managed and concerns beyond technical stakeholders are addressed during IoT system development. In this paper, a Knowledge Graph (KG) centric framework is proposed to develop CT. Based on the framework, a future tool-chain is proposed to develop the CT for the initiatives of H2020 project FACTLOG. Based on the comparison between DT and CT, we infer the CT is a more comprehensive approach to support IoT-based systems development than DT. 11pages

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    arXiv.org e-Print Archive
    Other literature type . Preprint . 2019
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    http://arxiv.org/pdf/1912.0854...
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Lecture Notes in Mechanical Engineering
    Other literature type . Part of book or chapter of book . 2020 . Peer-reviewed
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    https://doi.org/10.48550/arxiv...
    Article . 2019
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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      arXiv.org e-Print Archive
      Other literature type . Preprint . 2019
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      http://arxiv.org/pdf/1912.0854...
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Lecture Notes in Mechanical Engineering
      Other literature type . Part of book or chapter of book . 2020 . Peer-reviewed
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      https://doi.org/10.48550/arxiv...
      Article . 2019
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    Authors: Quan Nguyen; Koushil Sreenath;

    We present a novel method of optimal robust control through quadratic programs that offers tracking stability while subject to input and state-based constraints as well as safety-critical constraints for nonlinear dynamical robotic systems in the presence of model uncertainty. The proposed method formulates robust control Lyapunov and barrier functions to provide guarantees of stability and safety in the presence of model uncertainty. We evaluate our proposed control design on dynamic walking of a five-link planar bipedal robot subject to contact force constraints as well as safety-critical precise foot placements on stepping stones, all while subject to model uncertainty. We conduct preliminary experimental validation of the proposed controller on a rectilinear spring-cart system under different types of model uncertainty and perturbations.

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    arXiv.org e-Print Archive
    Other literature type . Preprint . 2020
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    IEEE Transactions on Automatic Control
    Article . 2022 . Peer-reviewed
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    Article . 2020
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      arXiv.org e-Print Archive
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      IEEE Transactions on Automatic Control
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    Authors: HENRI, PIERRE REMI ANTOINE; CALIFANO, FRANCESCO; Briand C; Mangeney A.;

    Recent observation of large amplitude Langmuir waveforms during a Type III event in the solar wind have been interpreted as the signature of the electrostatic decay of beam-driven Langmuir waves. This mechanism is thought to be a first step to explain the generation of solar Type III radio emission. The threshold for this parametric instability in typical solar wind condition is investigated here by means of 1D-1V Vlasov-Poisson simulations. We show that the amplitude of the observed Langmuir beat-like waveforms is of the order of the effective threshold computed from the full kinetic simulations. The expected level of associated ion acoustic density fluctuations have also been computed for comparison with observations. Comment: 20 pages, 8 figures, accepted for publication in Journal of Geophysical Research (Space Physics)

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    arXiv.org e-Print Archive
    Other literature type . Preprint . 2013
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    Journal of Geophysical Research Atmospheres
    Article . 2010 . Peer-reviewed
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    Authors: Bochanski, John J.; Hennawi, Joseph F.; Simcoe, Robert A.; Prochaska, J. Xavier; +6 Authors

    We introduce a data-reduction package written in Interactive Data Language (IDL) for the Magellan Echellete Spectrograph (MAGE). MAGE is a medium-resolution (R 4100), cross-dispersed, optical spectrograph, with coverage from . The MAGE Spectral Extractor (MASE) incorporates the entire image reduction and calibration process, including bias subtraction, flat fielding, wavelength calibration, sky subtraction, object extraction, and flux calibration of point sources. We include examples of the user interface and reduced spectra. We show that the wavelength calibration is sufficient to achieve 5 km s-1 rms accuracy and relative flux calibrations better than 10%. A lightweight version of the full reduction pipeline has been included for real-time source extraction and signal-to-noise estimation at the telescope. Massachusetts Institute of Technology. School of Science National Science Foundation (AST- 0215989) Carnegie Observatories

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    DSpace@MIT
    Article . 2007
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    arXiv.org e-Print Archive
    Other literature type . Preprint . 2009
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    https://doi.org/10.48550/arxiv...
    Article . 2009
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  • Authors: Torre, André; Wallet, Frederic;

    ISBN 978-3-319-02372-4 (eBook) ISSN 2192-0435 (electronic); International audience

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    Authors: Schoorlemmer, Harm; López-Coto, Rubén; Hinton, Jim;

    The TeV gamma ray sky is observable by recording footprints of extensive air showers with an array of particle detectors. In the northern hemisphere there are currently two projects employing this technique: The HAWC gamma ray observatory which is currently operational in Mexico and LHAASO in the Sichuan region in China which is currently under development. In the southern hemisphere several efforts are currently ongoing to investigate the feasibility of a similar observatory at very high altitude sites in the Andes. The science case for such an observatory should be complementary to the science to be performed by the future Cherenkov Telescope Array. There are two clear directions in which such an observatory could optimize its performance. Firstly, optimize the performance of sub-TeV energies. This is especially important to provide an unbiased monitoring of a large fraction of the sky for observations of transient and extended sources. Secondly, to obtain the largest photon statistics above roughly 50 TeV, which requires a large collection area with sufficient performance in angular and energy resolution. This would enable to extend spectral measurements of Galactic sources and gives the opportunity to search for dark matter and exotic physics in a new energy range. Using simulated air showers and a generalized detector description the performance of a conceptual observatory is studied and the ways to optimize it will be discussed. With this approach the baseline design of such an observatory can be obtained without the need of detailed simulations of the detector hardware. Comment: Proceeding if the 35th International Cosmic Ray Conference

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    Authors: Ivan Y. Tyukin; Ivan Y. Tyukin; Alexander N. Gorban; Alexander N. Gorban; +3 Authors

    We consider the fundamental question: how a legacy ``student'' Artificial Intelligent (AI) system could learn from a legacy ``teacher'' AI system or a human expert without re-training and, most importantly, without requiring significant computational resources. Here ``learning'' is broadly understood as an ability of one system to mimic responses of the other to an incoming stimulation and vice-versa. We call such learning an Artificial Intelligence knowledge transfer. We show that if internal variables of the ``student'' Artificial Intelligent system have the structure of an $n$-dimensional topological vector space and $n$ is sufficiently high then, with probability close to one, the required knowledge transfer can be implemented by simple cascades of linear functionals. In particular, for $n$ sufficiently large, with probability close to one, the ``student'' system can successfully and non-iteratively learn $k\ll n$ new examples from the ``teacher'' (or correct the same number of mistakes) at the cost of two additional inner products. The concept is illustrated with an example of knowledge transfer from one pre-trained convolutional neural network to another.

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    Authors: Hoque, Ryan; Seita, Daniel; Balakrishna, Ashwin; Ganapathi, Aditya; +5 Authors

    Robotic fabric manipulation has applications in home robotics, textiles, senior care and surgery. Existing fabric manipulation techniques, however, are designed for specific tasks, making it difficult to generalize across different but related tasks. We extend the Visual Foresight framework to learn fabric dynamics that can be efficiently reused to accomplish different fabric manipulation tasks with a single goal-conditioned policy. We introduce VisuoSpatial Foresight (VSF), which builds on prior work by learning visual dynamics on domain randomized RGB images and depth maps simultaneously and completely in simulation. We experimentally evaluate VSF on multi-step fabric smoothing and folding tasks against 5 baseline methods in simulation and on the da Vinci Research Kit (dVRK) surgical robot without any demonstrations at train or test time. Furthermore, we find that leveraging depth significantly improves performance. RGBD data yields an 80% improvement in fabric folding success rate over pure RGB data. Code, data, videos, and supplementary material are available at https://sites.google.com/view/fabric-vsf/. Comment: Robotics: Science and Systems (RSS) 2020

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    Authors: Rolinat, Clément; Grossard, Mathieu; Aloui, Saifeddine; Godin, Christelle;

    Grasp planning and most specifically the grasp space exploration is still an open issue in robotics. This article presents a data-driven oriented methodology to model the grasp space of a multi-fingered adaptive gripper for known objects. This method relies on a limited dataset of manually specified expert grasps, and uses variational autoencoder to learn grasp intrinsic features in a compact way from a computational point of view. The learnt model can then be used to generate new non-learnt gripper configurations to explore the grasp space. Comment: accepted at SYSID 2021 conference

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    Authors: Alemanno, Alberto;

    The European response to COVID-19 has revealed an inconvenient truth. Despite having integrated public health concerns across all its policies – be it agriculture, consumer protection, or security –, the Union cannot directly act to save people’s lives. Only member states can do so. Yet when they adopted unilateral measures to counter the spread of the virus, those proved not only ineffective but also disruptive on vital supply chains, by ultimately preventing the flow of essential goods and people across the Union. These fragmented efforts in tackling cross-border health threats have almost immediately prompted political calls for the urgent creation of a European Health Union. Yet this call raises more questions than answers. With the aim to offer a rigorous and timely blueprint to decision-makers and the public at large, this Special Issue of the European Journal of Risk Regulation contextualizes such a new political project within the broader constitutional and institutional framework of EU public health law and policy. By introducing the Special, this paper argues that unless the envisaged Health Union will tackle the root causes of what prevented the Union from effectively responding to COVID-19 – the divergent health capacity across the Union –, it might fall short of its declared objective of strengthening the EU’resilience for cross-border health threats.

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    European Journal of Risk Regulation
    Article . 2020 . Peer-reviewed
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      European Journal of Risk Regulation
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    Authors: Lu, Jinzhi; Zheng, Xiaochen; Gharaei, Ali; Kalaboukas, Kostas; +1 Authors

    Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for identifying the dynamics of virtual model evolution, promoting the understanding of interrelationships between virtual models and enhancing the decision-making based on DT. The CT ensures that assets of Internet of Things (IoT) systems are well-managed and concerns beyond technical stakeholders are addressed during IoT system development. In this paper, a Knowledge Graph (KG) centric framework is proposed to develop CT. Based on the framework, a future tool-chain is proposed to develop the CT for the initiatives of H2020 project FACTLOG. Based on the comparison between DT and CT, we infer the CT is a more comprehensive approach to support IoT-based systems development than DT. 11pages

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    Lecture Notes in Mechanical Engineering
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      Lecture Notes in Mechanical Engineering
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    Authors: Quan Nguyen; Koushil Sreenath;

    We present a novel method of optimal robust control through quadratic programs that offers tracking stability while subject to input and state-based constraints as well as safety-critical constraints for nonlinear dynamical robotic systems in the presence of model uncertainty. The proposed method formulates robust control Lyapunov and barrier functions to provide guarantees of stability and safety in the presence of model uncertainty. We evaluate our proposed control design on dynamic walking of a five-link planar bipedal robot subject to contact force constraints as well as safety-critical precise foot placements on stepping stones, all while subject to model uncertainty. We conduct preliminary experimental validation of the proposed controller on a rectilinear spring-cart system under different types of model uncertainty and perturbations.

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    IEEE Transactions on Automatic Control
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      IEEE Transactions on Automatic Control
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    Authors: HENRI, PIERRE REMI ANTOINE; CALIFANO, FRANCESCO; Briand C; Mangeney A.;

    Recent observation of large amplitude Langmuir waveforms during a Type III event in the solar wind have been interpreted as the signature of the electrostatic decay of beam-driven Langmuir waves. This mechanism is thought to be a first step to explain the generation of solar Type III radio emission. The threshold for this parametric instability in typical solar wind condition is investigated here by means of 1D-1V Vlasov-Poisson simulations. We show that the amplitude of the observed Langmuir beat-like waveforms is of the order of the effective threshold computed from the full kinetic simulations. The expected level of associated ion acoustic density fluctuations have also been computed for comparison with observations. Comment: 20 pages, 8 figures, accepted for publication in Journal of Geophysical Research (Space Physics)

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    Journal of Geophysical Research Atmospheres
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    Authors: Bochanski, John J.; Hennawi, Joseph F.; Simcoe, Robert A.; Prochaska, J. Xavier; +6 Authors

    We introduce a data-reduction package written in Interactive Data Language (IDL) for the Magellan Echellete Spectrograph (MAGE). MAGE is a medium-resolution (R 4100), cross-dispersed, optical spectrograph, with coverage from . The MAGE Spectral Extractor (MASE) incorporates the entire image reduction and calibration process, including bias subtraction, flat fielding, wavelength calibration, sky subtraction, object extraction, and flux calibration of point sources. We include examples of the user interface and reduced spectra. We show that the wavelength calibration is sufficient to achieve 5 km s-1 rms accuracy and relative flux calibrations better than 10%. A lightweight version of the full reduction pipeline has been included for real-time source extraction and signal-to-noise estimation at the telescope. Massachusetts Institute of Technology. School of Science National Science Foundation (AST- 0215989) Carnegie Observatories

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  • Authors: Torre, André; Wallet, Frederic;

    ISBN 978-3-319-02372-4 (eBook) ISSN 2192-0435 (electronic); International audience

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    Authors: Schoorlemmer, Harm; López-Coto, Rubén; Hinton, Jim;

    The TeV gamma ray sky is observable by recording footprints of extensive air showers with an array of particle detectors. In the northern hemisphere there are currently two projects employing this technique: The HAWC gamma ray observatory which is currently operational in Mexico and LHAASO in the Sichuan region in China which is currently under development. In the southern hemisphere several efforts are currently ongoing to investigate the feasibility of a similar observatory at very high altitude sites in the Andes. The science case for such an observatory should be complementary to the science to be performed by the future Cherenkov Telescope Array. There are two clear directions in which such an observatory could optimize its performance. Firstly, optimize the performance of sub-TeV energies. This is especially important to provide an unbiased monitoring of a large fraction of the sky for observations of transient and extended sources. Secondly, to obtain the largest photon statistics above roughly 50 TeV, which requires a large collection area with sufficient performance in angular and energy resolution. This would enable to extend spectral measurements of Galactic sources and gives the opportunity to search for dark matter and exotic physics in a new energy range. Using simulated air showers and a generalized detector description the performance of a conceptual observatory is studied and the ways to optimize it will be discussed. With this approach the baseline design of such an observatory can be obtained without the need of detailed simulations of the detector hardware. Comment: Proceeding if the 35th International Cosmic Ray Conference

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    Authors: Ivan Y. Tyukin; Ivan Y. Tyukin; Alexander N. Gorban; Alexander N. Gorban; +3 Authors

    We consider the fundamental question: how a legacy ``student'' Artificial Intelligent (AI) system could learn from a legacy ``teacher'' AI system or a human expert without re-training and, most importantly, without requiring significant computational resources. Here ``learning'' is broadly understood as an ability of one system to mimic responses of the other to an incoming stimulation and vice-versa. We call such learning an Artificial Intelligence knowledge transfer. We show that if internal variables of the ``student'' Artificial Intelligent system have the structure of an $n$-dimensional topological vector space and $n$ is sufficiently high then, with probability close to one, the required knowledge transfer can be implemented by simple cascades of linear functionals. In particular, for $n$ sufficiently large, with probability close to one, the ``student'' system can successfully and non-iteratively learn $k\ll n$ new examples from the ``teacher'' (or correct the same number of mistakes) at the cost of two additional inner products. The concept is illustrated with an example of knowledge transfer from one pre-trained convolutional neural network to another.

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    Frontiers in Neurorobotics
    Article . 2018 . Peer-reviewed
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    DOAJ
    Article . 2018
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    Frontiers in Neurorobotics
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    arXiv.org e-Print Archive
    Other literature type . Preprint . 2017
    https://doi.org/10.48550/arxiv...
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      Frontiers in Neurorobotics
      Article . 2018 . Peer-reviewed
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    Authors: Hoque, Ryan; Seita, Daniel; Balakrishna, Ashwin; Ganapathi, Aditya; +5 Authors

    Robotic fabric manipulation has applications in home robotics, textiles, senior care and surgery. Existing fabric manipulation techniques, however, are designed for specific tasks, making it difficult to generalize across different but related tasks. We extend the Visual Foresight framework to learn fabric dynamics that can be efficiently reused to accomplish different fabric manipulation tasks with a single goal-conditioned policy. We introduce VisuoSpatial Foresight (VSF), which builds on prior work by learning visual dynamics on domain randomized RGB images and depth maps simultaneously and completely in simulation. We experimentally evaluate VSF on multi-step fabric smoothing and folding tasks against 5 baseline methods in simulation and on the da Vinci Research Kit (dVRK) surgical robot without any demonstrations at train or test time. Furthermore, we find that leveraging depth significantly improves performance. RGBD data yields an 80% improvement in fabric folding success rate over pure RGB data. Code, data, videos, and supplementary material are available at https://sites.google.com/view/fabric-vsf/. Comment: Robotics: Science and Systems (RSS) 2020

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    Conference object . 2020 . Peer-reviewed
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