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IEEE International Workshop on Advanced Robotics and its Social Impacts (ARSO)

作者： Rakotovao, Tiana Mottin, Julien Puschini, Diego Laugier, Christian CEA LETI MINATEC Campus17 Rue Martyrs F-38000 Grenoble France INRIA Grenoble Rhone Alpes F-38334 Saint Ismier France

ISBN: (纸本)9781467380294

Safe Autonomous Vehicles (AVs) will emerge when comprehensive perception systems will be successfully integrated into vehicles. Advanced perception algorithms based on occupancy grids were developed for AV prototypes. These algorithms estimate the position and speed of every obstacle in the environment by using data fusion from multiple sensors. Computational requirements of such fusion prevent their integration into AVs on current low-power embedded hardware. However, recent emerging many-core architectures offer opportunities to fulfill the automotive market constraints and efficiently support advanced perception applications. This paper explores the integration of the occupancy grid multi-sensor fusion algorithm into low power many-core architectures. The parallel properties of this function are used to achieve real-time performance with a power consumption less than 1W. The proposed implementation produces an occupancy grid of 500 x 300 cells within 6.26ms. The execution time is 6x faster than typical sensor output rates and 9x faster than previous embedded prototypes.

关键词： Integration

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Reliable sources and uncertain decisions in multisensor systems

Reliable sources and uncertain decisions in multisensor syst...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Minor, Christian Johnson, Kevin Nova Res Inc Alexandria VA 22308 USA Naval Res Lab Washington DC 20375 USA

ISBN: (纸本)9781628416145

Conflict among information sources is a feature of fused multisource and multisensor systems. Accordingly, the subject of conflict resolution has a long history in the literature of data fusion algorithms such as that of Dempster-Shafer theory (DS). Most conflict resolution strategies focus on distributing the conflict among the elements of the frame of discernment (the set of hypotheses that describe the possible decisions for which evidence is obtained) through rescaling of the evidence. These "closed-world" strategies imply that conflict is due to the uncertainty in evidence sources stemming from their reliability. An alternative approach is the "open-world" hypothesis, which allows for the presence of "unknown" elements not included in the original frame of discernment. Here, conflict must be considered as a result of uncertainty in the frame of the discernment, rather than solely the province of evidence sources. Uncertainty in the operating environment of a fused system is likely to appear as an open-world scenario. Understanding the origin of conflict (source versus frame of discernment uncertainty) is a challenging area for research in fused systems. Determining the ratio of these uncertainties provides useful insights into the operation of fused systems and confidence in their decisions for a variety of operating environments. Results and discussion for the computation of these uncertainties are presented for several combination rules with simulated data sets.

关键词： multisensor systems data fusion sensor reliability interferants open-world sensing Dempster-Shafer theory combination rules

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i-TEAMS: Cooperative GNC for small UAV formations 2

i-TEAMS: Cooperative GNC for small UAV formations

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2nd IEEE International Workshop on Metrology for Aerospace

作者： Vetrella, Amedeo Rodi Fasano, Giancarmine Accardo, Domenico Univ Naples Federico II Dept Ind Engn Naples Italy

ISBN: (纸本)9781479975693

The research project named "i-TEAMS" (innovative Techniques for Autonomous Micro-UAV Swarms) aims at developing new architectures and technologies for distributed guidance, navigation, and control of mini and/or micro Unmanned Aircraft Systems. Main research topics and the project strategy are described. Then, the basic logical steps of innovative cooperative navigation algorithms, and measurement uncertainty budgets, are provided. Experimental results demonstrate effective vision-based tracking and promising performance in terms of attitude estimation based on differential GPS and relative sensing.

关键词： Unmanned Aircraft Systems Cooperative Guidance Navigation and Control sensor fusion Vision-based Tracking Cooperative GNSS applications

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An asset valuation approach using fuzzy logic

An asset valuation approach using fuzzy logic

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Leung, Henry Univ Calgary Calgary AB Canada

ISBN: (纸本)9781628416145

Organisations that own operational networks have many networked assets to support daily business. For meaningful decision support on these assets and their services, network defenders need to know the values of their assets and services. Unfortunately, there is no easy way of knowing or determining these values, and no universally recognised approach to asset valuation exists. Proprietary and published approaches, mostly in risk analysis, tend to assume values whose significance may be hard to justify in practice. Fortunately, experienced computer security experts can give intuitive guidance on the relative importance of network assets in operational networks. Such experiential knowledge, though difficult to quantify through classical relational mathematics, can be generally effective in assigning relative values to assets. In this work, we propose to capitalise on this expertise by combining asset attribute factors with expert and experiential knowledge about assets to determine their values. We exploit the mathematical theory of fuzzy logic that can be used to model and quantify human expertise and experiential knowledge. Our approach starts by modeling experts' experiential knowledge about assets and their properties as fuzzy variables. Then we use a fuzzy inference system to translate that knowledge into an asset value. Our results show asset values that are a close match with what an experienced expert would infer local asset values to be.

关键词： Alert Correlation Detection Multi-sensor

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The Application of Machine Learning in Multi sensor Data fusion for Activity Recognition in Mobile Device Space 2

The Application of Machine Learning in Multi Sensor Data Fus...

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Conference on Image Sensing Technologies - Materials, Devices, Systems, and applications ii

作者： Marhoubi, Asmaa H. Saravi, Sara Edirisinghe, Eran A. Univ Loughborough Dept Comp Sci Loughborough Leics England

ISBN: (纸本)9781628415971

The present generation of mobile handheld devices comes equipped with a large number of sensors. The key sensors include the Ambient Light sensor, Proximity sensor, Gyroscope, Compass and the Accelerometer. Many mobile applications are driven based on the readings obtained from either one or two of these sensors. However the presence of multiple-sensors will enable the determination of more detailed activities that are carried out by the user of a mobile device, thus enabling smarter mobile applications to be developed that responds more appropriately to user behavior and device usage. In the proposed research we use recent advances in machine learning to fuse together the data obtained from all key sensors of a mobile device. We investigate the possible use of single and ensemble classifier based approaches to identify a mobile device's behavior in the space it is present. Feature selection algorithms are used to remove non-discriminant features that often lead to poor classifier performance. As the sensor readings are noisy and include a significant proportion of missing values and outliers, we use machine learning based approaches to clean the raw data obtained from the sensors, before use. Based on selected practical case studies, we demonstrate the ability to accurately recognize device behavior based on multi-sensor data fusion.

关键词： Activity Recognition Mobile phone Mobile sensors Gyroscope Accelerometer Multi sensor

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Real Time Transducer Signal Features Extraction: A Standard Approach 13

Real Time Transducer Signal Features Extraction: A Standard ...

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13th IEEE International Conference on Industrial Informatics (INDIN)

作者： Monte, G. Huang, V. Abate, F. Paciello, V. Pietrosanto, A. Univ Tecnol Nacl Fac Reg Neuquen Plaza Huincul Argentina Better World IES Stand Mishawaka IN USA Univ Salerno Dept Ind Engn I-84084 Fisciano SA Italy

ISBN: (纸本)9781479966493

This paper presents a real time algorithm, based on a segmentation and labelling technique, for analog transducer signals, which extracts information from the signal. The process of sampling is extremely important because it is the only one that connects the real world with the digital world. In addition, the proposed technique can be embedded into sensors, allowing applications in sensor networks and sensors data fusion architectures like Internet of Things. A simplified version of these algorithms has been proposed as a standard for transducer signal feature extraction. These algorithms are analysed and experimental results are tackled for representative signals, in different fields.

关键词： sampling sensor networks IoT standards real time smart sensors

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Distributed Consensus plus Innovation Particle Filtering for Bearing/Range Tracking With Communication Constraints

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2015年第3期63卷 620-635页

作者： Mohammadi, Arash Asif, Amir Univ Toronto Dept Elect & Comp Engn Toronto ON M3J 1P3 Canada Concordia Univ Dept Elect & Comp Engn Montreal PQ M3J 1P3 Canada

A constrained sufficient statistic (CSS)-based distributed particle filter (CSS/DPF) implementation is proposed for nonlinear bearing-only and joint bearing/range tracking applications in sensor networks. The CSS/DPF runs localized particle filters at nodes constituting the sensor network and uses the resulting local sufficient statistics (LSS) to compute the global sufficient statistics (GSS) for the overall system. The CSS/DPF is, therefore, a two-step procedure: i) the means of the LSSs for the local filters are computed by running average consensus algorithms, which are then used to derive the corresponding GSSs, and ii) each node renews the local weights of the localized particle filters using the updated GSSs. The attractive feature of the CSS/DPF is the reduced number of consensus runs as compared with the state-of-art consensus-based DPF implementations. To further reduce the consensus overhead, we couple the CSS/DPF with the distributed unscented particle filter (DUPF), collectively referred to as the CSS/DUPF, which extends the linear consensus and innovation framework to nonlinear distributed estimation. Our Monte Carlo simulations show that the performance of the CSS/DUPF follows that of the centralized particle filter, even with a limited number of iterations per consensus run.

关键词： Data fusion distributed estimation multi-sensor tracking nonlinear systems particle filters

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\"Found\" in Space - Helical Resonator Filters for Satellite Communication [Book\/Software Reviews]

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IEEE Microwave Magazine 2015年第11期16卷 80-82页

作者： James Chu Kennesaw State University Southern Polytechnic State University Marietta Georgia United States

This book's main objective is to offer a contemporary, comprehensive approach to the design of RF and microwave filters for satellite applications with an emphasis on helical resonator technology. By exploiting the synergies among available data, information fusion can reduce data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. The book examines the state of the art in information fusion. It presents the known methods, algorithms, architectures, and models of information fusion and discusses their applicability in the context of wireless sensor networks (WSNs). Paying particular attention to the wide range of topics that have been covered in recent literature, the text presents the results of a number of typical case studies. Complete with research-supported elements and comprehensive references, this teaching-oriented volume uses standard scientific terminology, conventions, and notations throughout. It applies recently developed convex-optimization theory and highly efficient algorithms in estimation fusion to open up discussion and provide researchers with an ideal starting point for further research on distributed estimation and fusion for WSNs. The book supplies a cohesive overview of the key results of theory and applications of information-fusion-related problems in networked systems in a unified framework. Providing advanced mathematical treatment of fundamental problems with information fusion, it will help readers broaden their understanding of prospective applications and how to address such problems in practice. After reading the book, readers will gain the understanding required to model parts of dynamic systems and use those models to develop distributed fusion control algorithms that are based on feedback control theory.

关键词： Book reviews Filtering theory Satellite communication Microwave filters Design methodology Wireless sensor networks Radio frequency Information filters Helical antennas

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Reviewing the process of data fusion in wireless sensor network: A brief survey

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International Journal of Wireless and Mobile Computing 2015年第2期8卷 130-140页

作者： Shivaprasad Yadav, S.G. Chitra, A. Lakshmi Deepika, C. Department of Telecommunication Engineering M.S. Ramaiah Institute of Technology Bangalore Karnataka India Department of Computer Applications P.S.G College of Technology Coimbatore Tamil Nadu India Department of Biomedical Engineering P.S.G College of Technology Coimbatore Tamil Nadu India

Wireless sensor network is deployed on human inaccessible region to perform a very sensitive task where various external and internal factors affect the results being accumulated by the sensing node. Data fusion is one such technique. With the upcoming applications of wireless sensor network, it is also accompanied by various power and quality related issues. However, it was seen that whatever are the challenges or issues, it affects basically the data collection techniques from sensor nodes and corresponding forwarding to sink node. Hence, this paper aims to perform an exclusive investigation of the data fusion with respect to various standard architectures, standard algorithms and techniques investigated in the past study for performing data fusion, followed by open issues and research gap in the existing system adopted for enhancing the efficiency of data fusion techniques. Copyright © 2015 Inderscience Enterprises Ltd.

关键词： sensor nodes

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Real-time power-efficient integration of multi-sensor occupancy grid on many-core

Real-time power-efficient integration of multi-sensor occupa...

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IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO

作者： Tiana Rakotovao Julien Mottin Diego Puschini Christian Laugier INRIA Grenoble Rhone-Alpes CEA-LETI MINATEC Campus Grenoble

Safe Autonomous Vehicles (AVs) will emerge when comprehensive perception systems will be successfully integrated into vehicles. Advanced perception algorithms based on occupancy grids were developed for AV prototypes. These algorithms estimate the position and speed of every obstacle in the environment by using data fusion from multiple sensors. Computational requirements of such fusion prevent their integration into AVs on current low-power embedded hardware. However, recent emerging many-core architectures offer opportunities to fulfill the automotive market constraints and efficiently support advanced perception applications. This paper explores the integration of the occupancy grid multi-sensor fusion algorithm into low power many-core architectures. The parallel properties of this function are used to achieve realtime performance with a power consumption less than 1W. The proposed implementation produces an occupancy grid of 500×300 cells within 6.26ms. The execution time is 6x faster than typical sensor output rates and 9x faster than previous embedded prototypes.

关键词： Computational modeling Mathematical model Hardware Laser radar Real-time systems Vehicles Computer architecture

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