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Dynamics of Consensus Formation among Agent Opinions
No full textThis chapter explores dynamics of consensus formation among a group of adaptive agents whose states are modeled as Dempster–Shafer theoretic (DST) body of evidence (BoE). In the consensus analyses, notions from graph theory and Dempster–Shafer (DS) belief theory are utilized for modeling agent interactions and complex agent opinions that consist of numerous uncertainties, respectively. Convergence properties of the DST belief revision process under these conditions are then established utilizing the properties of paracontracting operators. A consensus scenario of a group of adaptive agents is usually characterized by individual agents having access only to imperfect information, absence of global control, decentralized evidence and communication impairments. When the communication among agents is asynchronous, spatial coupling alone is insufficient for convergence analysis. The graph of an asynchronous iteration can be used to analyze temporal coupling among fusion operators. The chapter illustrates the spatial and temporal coupling of agents
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Multisensor Data Fusion: From Algorithms and Architectural Design to Applications (Book)
No full textInternational audienceThe technology of multisensor data fusion seeks to combine information coming from multiple anddifferent sources/sensors, resulting in an enhanced overall system performance with respect to separatesensors/sources. Multisensor data fusion has gained in importance over the last decades andfound applications in an impressive variety of areas within diverse disciplines: navigation, sensornetworks, intelligent transportation systems, security, medical diagnosis, biometrics, environmentalmonitoring, remote sensing, measurements, robotics, and so forth. Different concepts, techniques,and architectures have been developed to optimize the overall system output in applications forwhich sensor fusion might be useful and enables development of concrete solutions.The idea for this book therefore arose as a response to the immense interest and strong activitiesin the field of multisensor data fusion during the last few years, both in theoretical and practicalaspects. This book is targeted toward researchers, academics, engineers, and graduate studentsworking in the field of sensor fusion, estimation/observation, filtering, and signal processing.This book captures the latest data fusion concepts and techniques drawn from a broad array ofdisciplines. With contributions from the world’s leading fusion researchers and academicians, thisbook has 34 chapters, divided roughly into two sections, and covers the fundamental theory andrecent theoretical advances, as well as showcases applications of multisensor data fusion. Eachchapter is complete in itself and can be read in isolation or in conjunction with other chapters ofthe book. Chapters 1 to 23 in Section I are devoted to the state of the art and novel advances inmultisensor data fusion algorithm design. New materials and achievements on optimal fusion andmultisensor filters are provided. Chapters 24 to 34 in Section II mostly showcase multisensor datafusion advancements in fields such as medical applications, navigation, traffic analysis, and so on.We are grateful to all the contributors for sharing their valuable knowledge and we expect tooffer here a good balance between academic and industrial research through the different chapters.We sincerely hope that this book will be a source of inspiration for new concepts and applicationsand stimulate further the development of data fusion architecture. We would also like to acknowledgeCRC Press and its staff for technical and editorial assistance that improved the quality of thisbook and resulted in its publication. Finally, we hope readers will enjoy this book and that it willprove to be a useful addition to the increasingly important and expanding field of data fusion
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Multisensor data fusion: from algorithms and architectural design to applications
No full textMultisensor Data Fusion: From Algorithms and Architectural Design to Applications covers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines. Featuring contributions from the world's leading data fusion researchers and academicians, this authoritative book:
Presents state-of-the-art advances in the design of multisensor data fusion algorithms, addressing issues related to the nature, location, and computational ability of the sensors
Describes new materials and achievements in optimal fusion and multisensor filters
Discusses the advantages and challenges associated with multisensor data fusion, from extended spatial and temporal coverage to imperfection and diversity in sensor technologies
Explores the topology, communication structure, computational resources, fusion level, goals, and optimization of multisensor data fusion system architectures
Showcases applications of multisensor data fusion in fields such as medicine, transportation's traffic, defense, and navigation
Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies. The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution
Contributions to the attitude estimation of the animal or human based on inertial and magnetic data fusion,from the reconstitution of the posture toward the dead reckoning
No full textCe manuscrit est centré sur l'estimation de l'attitude d'un corps évoluant dans un espace 3D. Le cadre de l'étude est la reconstitution de la posture, des accélérations propres, des déplacements et de leur coût chez l'animal sauvage dans un contexte environnemental (application au Bio-logging). Dans ce contexte, la représentation de l'attitude choisie est le quaternion, et les données de mesures accessibles sont uniquement issues d'une triade de capteurs comportant un accéléromètre, un magnétomètre et un gyromètre. Trois approches différentes estimant le quaternion à partir de ces données ont alors été proposées. La première est écrite sous la forme d'un observateur non linéaire additif et utilise la technique d'addition de quaternion pour la mise à jour des estimés de l'attitude. La deuxième et la troisième approche sont représentées, respectivement, par un observateur à modes glissants et un filtre complémentaire. La technique de mise à jour utilisée au sein de ces deux dernières approches repose sur la multiplication de quaternion. Les résultats obtenus à l'issue des simulations théoriques et expérimentales sont satisfaisants en termes de précision de l'estimation de l'attitude et sont promoteurs par rapport à l'application au Bio-logging. Nous avons présenté à la fin de ce manuscrit une approche de navigation à l'estime permettant de remonter au parcours 3D et à la position d'un animal à locomotion pédestre en exploitant uniquement les données issues d'une unité inertielle. Les résultats expérimentaux obtenus par cette approche préliminaire sont encourageants. Ces résultats restent prometteurs pour une application au contexte du Bio-logging.This manuscript focuses on the attitude estimation problem of a body moving in 3D space. This study is devoted to the reconstruction of the posture, linear accelerations, positions and their cost in fre ranging animal where the access to GPS locations is limited (application in Bio-logging). In this context, the chosen attitude representation is the quaternion, and the available data are only from a triad of sensors including a 3-axis accelerometer, a 3-axis magnetometer and a 3-axis gyroscope. Three approaches to estimate the quaternion from these data set were then proposed. The first is based on an additive nonlinear observer design and uses the quaternion addition technique for updating attitude estimates. The second and third approaches propose the design of a sliding mode observer and a complementary filter, respectively. The update of the estimates used in these last two approaches is based on quaternion multiplication. This technique shows that it is a good alternative and seems more appropriate for the quaternion algebra. The obtained results from both simulations and experimental studies show the efficiency of these approaches to reconstruct the attitude with a good accuracy for the Biologging application and allow estimating also the linear acceleration and the energetic index of the animal. Moreover, a dead reckoning approach is proposed to estimate the 3D position of pedestrian locomotion animal by exploiting only data from an inertial measurement unit. The obtained experimental results in the case of human locomotion, with an adjusted velocity, are satisfactory and remain promising for the application of this approach in Bio-logging
Heterogeneous Data Fusion Algorithm for Pedestrian Navigation via Foot-Mounted Inertial Measurement Unit and Complementary Filter Design
No full textInternational audienceThis paper proposes a foot-mounted Zero Velocity Update (ZVU) aided Inertial Measurement Unit (IMU) filtering algorithm for pedestrian tracking in indoor environment. The algorithm outputs are the foot kinematic parameters, which include foot orientation, position, velocity, acceleration, and gait phase. The foot motion filtering algorithm incorporates methods for orientation estimation, gait detection, and position estimation. A novel Complementary Filter (CF) is introduced to better pre-process the sensor data from a foot-mounted IMU containing tri-axial angular rate sensors, accelerometers, and magnetometers and to estimate the foot orientation without resorting to GPS data. A gait detection is accomplished using a simple states detector that transitions between states based on acceleration and angular rate measurements. Once foot orientation is computed, position estimates are obtained by using integrating acceleration and velocity data, which has been corrected at step stance phase for drift using an implemented ZVU algorithm, leading to a position accuracy improvement.We illustrate our findings experimentally by using of a commercial IMU during regular human walking trials in a typical public building. Experiment results show that the positioning approach achieves approximately a position accuracy around 0.4% and improves the performance regarding recent works of literature
Contributions à l’estimation d’attitude chez l’animal ou l’homme par fusion de données inertielles et magnétiques : de la reconstitution de la posture vers la navigation à l’estime : une application au Bio-logging
No full textCe manuscrit est centré sur l’estimation de l’attitude d’un corps évoluant dans un espace 3D. Le cadre de l’étude est la reconstitution de la posture, des accélérations propres, des déplacements et de leur coût chez l’animal sauvage dans un contexte environnemental (application au Bio-logging). Dans ce contexte, la représentation de l’attitude choisie est le quaternion, et les données de mesures accessibles sont uniquement issues d’une triade de capteurs comportant un accéléromètre, un magnétomètre et un gyromètre. Trois approches différentes estimant le quaternion à partir de ces données ont alors été proposées. La première est écrite sous la forme d’un observateur non linéaire additif et utilise la technique d’addition de quaternion pour la mise à jour des estimés de l’attitude. La deuxième et la troisième approche sont représentées, respectivement, par un observateur à modes glissants et un filtre complémentaire. La technique de mise à jour utilisée au sein de ces deux dernières approches repose sur la multiplication de quaternion. Les résultats obtenus à l’issue des simulations théoriques et expérimentales sont satisfaisants en termes de précision de l’estimation de l’attitude et sont promoteurs par rapport à l’application au Bio-logging. Nous avons présenté à la fin de ce manuscrit une approche de navigation à l’estime permettant de remonter au parcours 3D et à la position d’un animal à locomotion pédestre en exploitant uniquement les données issues d’une unité inertielle. Les résultats expérimentaux obtenus par cette approche préliminaire sont encourageants. Ces résultats restent prometteurs pour une application au contexte du Bio-logging.This manuscript focuses on the attitude estimation problem of a body moving in 3D space. This study is devoted to the reconstruction of the posture, linear accelerations, positions and their cost in free ranging animal where the access to GPS locations is limited (application in Bio-logging). In this context, the chosen attitude representation is the quaternion, and the available data are only from a triad of sensors including a 3-axis accelerometer, a 3-axis magnetometer and a 3-axis gyroscope. Three approaches to estimate the quaternion from these data set were then proposed. The first is based on an additive nonlinear observer design and uses the quaternion addition technique for updating attitude estimates. The second and third approaches propose the design of a sliding mode observer and a complementary filter, respectively. The update of the estimates used in these last two approaches is based on quaternion multiplication. This technique shows that it is a good alternative and seems more appropriate for the quaternion algebra. The obtained results from both simulations and experimental studies show the efficiency of these approaches to reconstruct the attitude with a good accuracy for the Biologging application and allow estimating also the linear acceleration and the energetic index of the animal. Moreover, a dead reckoning approach is proposed to estimate the 3D position of pedestrian locomotion animal by exploiting only data from an inertial measurement unit. The obtained experimental results in the case of human locomotion, with an adjusted velocity, are satisfactory and remain promising for the application of this approach in Bio-logging
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