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Titre : Advanced sensors for real-time monitoring applications Type de document : Monographie Auteurs : Olga Korostynska, Éditeur scientifique ; Alex Mason, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 350 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-3-0365-0427-8 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] capteur actif
[Termes IGN] capteur imageur
[Termes IGN] capteur ultrasonore
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] surveillance
[Termes IGN] temps réelRésumé : (éditeur) It is impossible to imagine the modern world without sensors, or without real-time information about almost everything—from local temperature to material composition and health parameters. We sense, measure, and process data and act accordingly all the time. In fact, real-time monitoring and information is key to a successful business, an assistant in life-saving decisions that healthcare professionals make, and a tool in research that could revolutionize the future. To ensure that sensors address the rapidly developing needs of various areas of our lives and activities, scientists, researchers, manufacturers, and end-users have established an efficient dialogue so that the newest technological achievements in all aspects of real-time sensing can be implemented for the benefit of the wider community. This book documents some of the results of such a dialogue and reports on advances in sensors and sensor systems for existing and emerging real-time monitoring applications. Note de contenu : 1- Real-time water quality monitoring with chemical sensors
2- Body condition score estimation based on regression analysis using a 3D camera
3- Wireless module for nondestructive testing/structural health monitoring applications based on solitary waves
4- Quantified activity measurement for medical use in movement disorders through IR-UWB radar sensor
5- Pre-pressure optimization for ultrasonic motors based on multi-sensor fusion
6- On-line monitoring of pipe wall thinning by a high temperature ultrasonic waveguide system at the flow accelerated corrosion proof facility
7- A low-cost continuous turbidity monitor
8- Laboratory calibration and field validation of soil water content and salinity measurements using the 5TE sensor
9- Quantitative analysis of elements in fertilizer using laser-induced breakdown spectroscopy coupled with support vector regression model
10- Univariate and multivariate analysis of phosphorus element in fertilizers using laser-induced breakdown spectroscopy
11- The efficiency of color space channels to quantify color and color intensity change in liquids, pH strips, and lateral flow assays with smartphones
12- An innovative ultrasonic apparatus and technology for diagnosis of freeze-drying process
13- Temperature and strain correlation of bridge parallel structure based on vibrating wire strain sensor
14- Train hunting related fast degradation of a railway crossing—condition monitoring and numerical verification
15- Correlation analysis and verification of railway crossing condition monitoring
16- A novel monitoring approach for train tracking and incursion detection in underground structures based on ultra-weak FBG sensing array
17- Digital approach to rotational speed measurement using an electrostatic sensor
18- Multi-factor operating condition recognition using 1D convolutional long short-term network
19- Comprehensive improvement of the sensitivity and detectability of a large-aperture electromagnetic wear particle detector
20- Analysis of satellite compass error’s spectrumNuméro de notice : 28598 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-0427-8 En ligne : https://doi.org/10.3390/books978-3-0365-0427-8 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99377
Titre : An introduction to ethics in robotics and AI Type de document : Monographie Auteurs : Christoph Bartneck, Auteur ; Christoph Lütge, Auteur ; Alan Wagner, Auteur ; Sean Welsch, Auteur Editeur : Springer International Publishing Année de publication : 2021 Importance : 117 p Présentation : . Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-030-51110-4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] données massives
[Termes IGN] édition en libre accès
[Termes IGN] éthique
[Termes IGN] navigation autonome
[Termes IGN] protection de la vie privée
[Termes IGN] robotique
[Termes IGN] utilisateur militaire
[Termes IGN] véhicule sans piloteRésumé : (éditeur) This open access book introduces the reader to the foundations of AI and ethics. It discusses issues of trust, responsibility, liability, privacy and risk. It focuses on the interaction between people and the AI systems and Robotics they use. Designed to be accessible for a broad audience, reading this book does not require prerequisite technical, legal or philosophical expertise. Throughout, the authors use examples to illustrate the issues at hand and conclude the book with a discussion on the application areas of AI and Robotics, in particular autonomous vehicles, automatic weapon systems and biased algorithms. A list of questions and further readings is also included for students willing to explore the topic further. Note de contenu : 1- What is AI?
2- What is ethics?
3- Trust and fairness in AI systems
4- Responsibility and liability in the case of AI systems
5- Risks in the business of AI
6- Psychological aspects of AI
7- Privacy issues of AI
8- Application areas of AI
9- Autonomous vehicles
10- Military uses of AI
11- Ethics in AI and Robotics: A Strategic ChallengeNuméro de notice : 28570 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Monographie DOI : 10.1007/978-3-030-51110-4 En ligne : https://doi.org/10.1007/978-3-030-51110-4 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97726
Titre : Benefiting from local rigidity in 3D point cloud processing Type de document : Thèse/HDR Auteurs : Zan Gojcic, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2021 Importance : 141 p. Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of Doctor of Sciences of ETH ZurichLangues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] capteur actif
[Termes IGN] champ vectoriel
[Termes IGN] déformation d'image
[Termes IGN] données lidar
[Termes IGN] effondrement de terrain
[Termes IGN] enregistrement de données
[Termes IGN] filtrage du bruit
[Termes IGN] flux
[Termes IGN] image 3D
[Termes IGN] navigation autonome
[Termes IGN] orientation du capteur
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] téléphone intelligent
[Termes IGN] traitement de semis de points
[Termes IGN] voxelIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Incorporating 3D understanding and spatial reasoning into (intelligent) algorithms is crucial for solving several tasks in fields such as engineering geodesy, risk assessment, and autonomous driving. Humans are capable of reasoning about 3D spatial relations even from a single 2D image. However, making the priors that we rely on explicit and integrating them into computer programs is very challenging. Operating directly on 3D input data, such as 3D point clouds, alleviates the need to lift 2D data into a 3D representation within the task-specific algorithm and hence reduces the complexity of the problem. The 3D point clouds are not only a better-suited input data representation, but they are also becoming increasingly easier to acquire. Indeed, nowadays, LiDAR sensors are even integrated into consumer devices such as mobile phones. However, these sensors often have a limited field of view, and hence multiple acquisitions are required to cover the whole area of interest. Between these acquisitions, the sensor has to be moved and pointed in a different direction. Moreover, the world that surrounds us is also dynamic and might change as well. Reasoning about the motion of both the sensor and the environment, based on point clouds acquired in two-time steps, is therfore an integral part of point cloud processing. This thesis focuses on incorporating rigidity priors into novel deep learning based approaches for dynamic 3D perception from point cloud data. Specifically, the tasks of point cloud registration, deformation analysis, and scene flow estimation are studied. At first, these tasks are incorporated into a common framework where the main difference is in the level of rigidity assumptions that are imposed on the motion of the scene or
the acquisition sensor. Then, the tasks specific priors are proposed and incorporated into novel deep learning architectures. While the global rigidity can be assumed in point cloud registration, the motion patterns in deformation analysis and scene flow estimation are more complex. Therefore, the global rigidity prior has to be relaxed to local or instancelevel rigidity, respectively. Rigidity priors not only add structure to the aforementioned tasks, which prevents physically implausible estimates and improves the generalization of the algorithms, but in some cases also reduce the supervision requirements. The proposed approaches were quantitatively and qualitatively evaluated on several datasets, and they yield favorable performance compared to the state-of-the-art.Numéro de notice : 28660 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD : Sciences : ETH Zurich : 2021 DOI : sans En ligne : https://www.research-collection.ethz.ch/handle/20.500.11850/523368 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99817 Benefits from a multi-receiver architecture for GNSS RTK positioning and attitude determination / Xiao Hu (2021)
Titre : Benefits from a multi-receiver architecture for GNSS RTK positioning and attitude determination Type de document : Thèse/HDR Auteurs : Xiao Hu, Auteur ; Christophe Macabiau, Directeur de thèse ; Paul Thevenon, Directeur de thèse Editeur : Toulouse : Université de Toulouse Année de publication : 2021 Importance : 217 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse délivré par l'institut National Polytechnique de ToulouseLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] capteur d'orientation
[Termes IGN] dégradation du signal
[Termes IGN] erreur de mesure
[Termes IGN] filtre de Kalman
[Termes IGN] mesurage de phase
[Termes IGN] milieu urbain
[Termes IGN] modèle stochastique
[Termes IGN] orientation de véhicule
[Termes IGN] phase GNSS
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] récepteur GPS
[Termes IGN] résolution d'ambiguïté
[Termes IGN] signal GNSS
[Termes IGN] trajet multipleIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Precise positioning with a stand-alone GPS receiver or using differential corrections is known to be strongly degraded in an urban or sub-urban environment due to frequent signal masking, strong multipath effect, frequent cycle slips on carrier phase, etc. The objective of this Ph.D. thesis is to
explore the possibility of achieving precise positioning with a low-cost architecture using multiple installed low-cost single-frequency receivers with known geometry whose one of them is RTK positioned w.r.t an external reference receiver. This setup is thought to enable vehicle attitude determination and RTK performance amelioration. In this thesis, we firstly proposed a method that includes an array of receivers with known geometry to enhance the performance of the RTK in different environments. Taking advantage of the attitude information and the known geometry of the installed array of receivers, the improvement of some internal steps of RTK w.r.t an external reference receiver can be achieved. The navigation module to be implemented in this work is an Extended Kalman Filter (EKF). The performance of a proposed two-receiver navigation architecture is then studied to quantify the improvements brought by the measurement redundancy. This concept is firstly tested on a simulator in order to validate the proposed algorithm and to give a reference result of our multi-receiver system’s performance. The pseudo-range measurements and carrier phase measurements mathematical models are implemented in a realistic simulator. Different
scenarios are conducted, including varying the distance between the 2 antennas of the receiver array, the satellite constellation geometry, and the amplitude of the noise measurement, in order to determine the influence of the use of an array of receivers. The simulation results show that our multi-receiver RTK system w.r.t an external reference receiver is more robust to noise and degraded satellite geometry, in terms of ambiguity fixing rate, and gets a better position accuracy under the same conditions when compared with the single receiver system. Additionally, our method achieves a relatively accurate estimation of the attitude of the vehicle which provides additional information beyond the positioning. In order to optimize our processing, the correlation of the measurement errors affecting observations taken by our array of receivers has been determined. Then, the performance of our real-time single frequency cycle-slip detection and repair algorithm has been assessed. These two investigations yielded important information so as to tune our Kalman Filter. The results obtained from the simulation made us eager to use actual data to verify and improve our multi-receiver RTK and attitude system. Tests based on real data collected around Toulouse, France, are used to test the performance of the whole methodology, where different scenarios are conducted, including varying the distance between the 2 antennas of the receiver array as well as the environmental conditions (open sky, suburban, and constrained urban environments). The thesis also tried to take advantage of a dual GNSS constellation, GPS and Galileo, to further strengthen the position solution and the reliable use of carrier phase measurements. The results show that our multi-receiver RTK system is more robust to degraded GNSS environments. Our experiments correlate favorably with our previous simulation results and further support the idea of using an array of receivers with known geometry to improve the RTK performance.Note de contenu : 1- Introduction
2- GNSS functional and stochastic model
3- GNSS-based precise positioning and attitude estimation
4- Proposed multi-receiver architecture for GNSS precise positioning and attitude estimation
5- Simulation results and performance analysis
6- real data tests and results
7- Conclusions and perspectivesNuméro de notice : 15216 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique et Télécommunications : Toulouse : 2021 Organisme de stage : ENAC-LAB DOI : sans En ligne : https://hal.science/tel-03506304/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100473 Cartographie dense et compacte par vision RGB-D pour la navigation d’un robot mobile / Bruce Canovas (2021)
Titre : Cartographie dense et compacte par vision RGB-D pour la navigation d’un robot mobile Type de document : Thèse/HDR Auteurs : Bruce Canovas, Auteur ; Michèle Rombaut, Directeur de thèse Editeur : Grenoble [France] : Université Grenoble Alpes Année de publication : 2021 Importance : 148 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse pour obtenir le titre de Docteur en Sciences de l'Université Grenoble Alpes, spécialité Signal, Image, Parole, TélécomsLangues : Français (fre) Descripteur : [Vedettes matières IGN] Informatique
[Termes IGN] algorithme ICP
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] image 3D
[Termes IGN] image RVB
[Termes IGN] instrument embarqué
[Termes IGN] modélisation 3D
[Termes IGN] navigation autonome
[Termes IGN] Ransac (algorithme)
[Termes IGN] robot mobile
[Termes IGN] vision par ordinateurIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Les capacités de perception et de localisation sont des enjeux majeurs de la robotique mobile, nécessaires dans la réalisation de missions impliquant des processus décisionnels autonomes. Elles s'appuient sur les mesures d'un ou plusieurs capteurs embarqués sur la plateforme robotique mobile en question. Dans cette thèse, on s'intéresse à des techniques de perception visuelle basées sur une caméra RGB-D pour permettre la navigation d'un robot compagnon dans un milieu intérieur inconnu. Afin de pouvoir se déplacer de façon autonome, ce robot doit avoir accès à une carte représentative de la structure de son environnement et être capable de s'y repérer.Bien que de nombreuses méthodes de localisation et cartographie simultanées (SLAM - Simultaneous Localization And Mapping) RGB-D capables de résultats impressionnants aient été développées, elles sont bien souvent trop coûteuses en termes de ressources informatiques pour être exécutées sur les cartes embarquées de robots mobiles d'intérieur. Elles font aussi la plupart du temps l'hypothèse que la scène observée par la caméra est statique, ce qui limite leur utilisation dans de nombreuses situations où des personnes sont présentes. De plus, les cartes qu'elles produisent sont souvent inadéquates pour la planification de trajectoires et ne peuvent pas être utilisées directement pour de tâches de navigation.Dans le but de répondre à ces problèmes, nous proposons une nouvelle forme de représentation 3D pour la reconstruction basse résolution, mais compacte rapide et légère d'environnements, au contraire des approches conventionnelles qui se focalisent sur la production de modèles 3D complexes avec un haut niveau détails. Un système de SLAM RGB-D dense complet, robuste aux éléments dynamiques, est conçu autour de cette représentation, puis porté sur une plateforme robotique mobile à conduite différentielle. En outre, une stratégie de navigation efficace est proposée en couplant l'algorithme de SLAM développé à un planificateur de trajectoires. Les différentes solutions proposées sont évaluées et comparées avec les méthodes de l'état de l'art, pour les valider et montrer leurs forces et faiblesses. Note de contenu : 1- Introduction générale
2- Prérequis
3- Modélisation 3D compacte à partir de caméra RGB-D
4- SLAM RGB-D dense, rapide et léger en milieu dynamique
5- Application de SupersurfelFusion à la navigation autonome d’un robot mobile
6- Conclusion et perspectivesNuméro de notice : 15283 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Signal, Image, Parole, Télécoms : Grenoble : 2021 Organisme de stage : Laboratoire Grenoble Images Parole Signal Automatique DOI : sans En ligne : https://tel.hal.science/tel-03647103 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101409 PermalinkDeep convolutional neural networks for scene understanding and motion planning for self-driving vehicles / Abdelhak Loukkal (2021)PermalinkDétection et géoréférencement des réseaux enterrés / Chloé Morgat (2021)PermalinkDetermination of the lunar body tide from global laser altimetry data / Robin N. Thor in Journal of geodesy, vol 95 n° 1 (January 2021)PermalinkDetermination of the under water position of objects by reflectorless total stations / Štefan Rákay in Survey review, vol 53 n°376 (January 2021)PermalinkDéveloppement d’une méthode innovante pour l’ajustement des paramètres internes du système de gravimétrie sous-marine GraviMob / Ossama Kharbou (2021)PermalinkExpérience professionnelle en bureau d'étude / Hugo Cornille (2021)PermalinkExploiting multi-camera constraints within bundle block adjustment: an experimental comparison / Eleonora Maset (2021)PermalinkExploration of reinforcement learning algorithms for autonomous vehicle visual perception and control / Florence Carton (2021)PermalinkFusion of ground penetrating radar and laser scanning for infrastructure mapping / Dominik Merkle in Journal of applied geodesy, vol 15 n° 1 (January 2021)Permalink