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IEEE International Conference on Industrial Informatics (INDIN)

作者： G. Monte V. Huang F. Abate V. Paciello A. Pietrosanto Facultad Regional Del Neuquén Universidad Tecnológica Nacional Plaza Huincul Argentina Better World- IES Standards USA Department of Industrial Engineering University of Salerno Giovanni Paolo II Fisciano(SA) Italy

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： Interpolation Intelligent sensors Shape Transducers Real-time systems Standards

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i-TEAMS: Cooperative GNC for small UAV formations

i-TEAMS: Cooperative GNC for small UAV formations

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IEEE Metrology for Aerospace

作者： Amedeo Rodi Vetrella Giancarmine Fasano Domenico Accardo Department of Industrial Engineering University of Naples “Federico II” Naples Italy

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： Decision support systems Global Positioning System Unmanned aerial vehicles Aircraft navigation sensor fusion Estimation Position measurement

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Guest editorial: Collaborative wireless sensor networks: architectures, algorithms and applications

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Information fusion 2015年 22卷 1-2页

作者： Fortino, Giancarlo Bal, Mert Li, Wenfeng Shen, Weiming DIMES University of Calabria Via. P. Bucci cubo 41C Rende CS87036 Italy Department of Engineering Technology Miami University Mosler Hall HamiltonOH45011 United States School of Logistics Engineering Wuhan University of Technology Wuhan430063 China National Research Council of Canada 800 Collip Circle LondonONN6G 4X8 Canada

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Integrated Multi-sensor fusion for Mapping and Localization in Outdoor Environments for Mobile Robots

Integrated Multi-sensor Fusion for Mapping and Localization ...

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

作者： Emter, Thomas Petereit, Janko Fraunhofer Inst Optron Syst Technol & Image Explo Karlsruhe Germany

ISBN: (纸本)9781628410587

An integrated multi-sensor fusion framework for localization and mapping for autonomous navigation in unstructured outdoor environments based on extended Kalman filters (EKF) is presented. The sensors for localization include an inertial measurement unit, a GPS, a fiber optic gyroscope, and wheel odometry. Additionally a 3D LIDAR is used for simultaneous localization and mapping (SLAM). A 3D map is built while concurrently a localization in a so far established 2D map is estimated with the current scan of the LIDAR. Despite of longer run-time of the SLAM algorithm compared to the EKF update, a high update rate is still guaranteed by sophisticatedly joining and synchronizing two parallel localization estimators.

关键词： multi-sensor fusion extended Kalman filter particle filter SLAM autonomous mobile robot asynchronous fusion 3D LIDAR mapping

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A Metamaterial-Inspired Combined Inductive-Capacitive sensor

A Metamaterial-Inspired Combined Inductive-Capacitive Sensor

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

作者： Long, Jiang Wang, Bingnan Mitsubishi Elect Res Labs Cambridge MA 02139 USA

ISBN: (纸本)9781628410587

This paper reports a metamaterial inspired combined inductive-capacitive sensing method for detecting and distinguishing metallic and non-metallic objects. Metallic and non-metallic objects can be distinguished by measuring both of their inductive and capacitive responses based on the fact that they respond differently to inductive and capacitive sensing. The proposed method is inspired by metamaterial structures. Both inductive and capacitive sensing are simultaneously realized when the sensor is operating at off-resonant frequencies. The proposed method is demonstrated with typical printed circuit board (PCB) technology. The designed sensor can distinguish the metallic and dielectric objects with a sensing range about 10 mm, showing a competitive performance compared with commercially available proximity sensors.

关键词： proximity sensor metamaterials combined sensing

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Multisensor fusion with non-optimal decision rules: the challenges of "open world" sensing

Multisensor fusion with non-optimal decision rules: the chal...

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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)9781628410587

In this work, simple, generic models of chemical sensing are used to simulate sensor array data and to illustrate the impact on overall system performance that specific design choices impart. The ability of multisensor systems to perform multianalyte detection (i.e., distinguish multiple targets) is explored by examining the distinction between fundamental design-related limitations stemming from mismatching of mixture composition to fused sensor measurement spaces, and limitations that arise from measurement uncertainty. Insight on the limits and potential of sensor fusion to robustly address detection tasks in realistic field conditions can be gained through an examination of a) the underlying geometry of both the composition space of sources one hopes to elucidate and the measurement space a fused sensor system is capable of generating, and b) the informational impact of uncertainty on both of these spaces. For instance, what is the potential impact on sensor fusion in an open world scenario where unknown interferants may contaminate target signals? Under complex and dynamic backgrounds, decision rules may implicitly become non-optimal and adding sensors may increase the amount of conflicting information observed. This suggests that the manner in which a decision rule handles sensor conflict can be critical in leveraging sensor fusion for effective open world sensing, and becomes exponentially more important as more sensors are added. Results and design considerations for handling conflicting evidence in Bayes and Dempster-Shafer fusion frameworks are presented. Bayesian decision theory is used to provide an upper limit on detector performance of simulated sensor systems.

关键词： multisensor systems data fusion interferants open-world sensing Dempster-Shafer theory

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IVVI 2.0: An intelligent vehicle based on computational perception

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EXPERT SYSTEMS WITH applications 2014年第17期41卷 7927-7944页

作者： Martin, D. Garcia, F. Musleh, B. Olmeda, D. Pelaez, G. Marin, P. Ponz, A. Rodriguez, C. Al-Kaff, A. de la Escalera, A. Armingol, J. M. Univ Carlos III Madrid Intelligent Syst Lab Leganes Spain

This paper presents the IVVI 2.0 a smart research platform to foster intelligent systems in vehicles. Computational perception in intelligent transportation systems applications has advantages, such as huge data from vehicle environment, among others, so computer vision systems and laser scanners are the main devices that accomplish this task. Both have been integrated in our intelligent vehicle to develop cutting-edge applications to cope with perception difficulties, data processing algorithms, expert knowledge, and decision-making. The long-term in-vehicle applications, that are presented in this paper, outperform the most significant and fundamental technical limitations, such as, robustness in the face of changing environmental conditions. Our intelligent vehicle operates outdoors with pedestrians and others vehicles, and outperforms illumination variation, i.e.: shadows, low lighting conditions, night vision, among others. So, our applications ensure the suitable robustness and safety in case of a large variety of lighting conditions and complex perception tasks. Some of these complex tasks are overcome by the improvement of other devices, such as, inertial measurement units or differential global positioning systems, or perception architectures that accomplish sensor fusion processes in an efficient and safe manner. Both extra devices and architectures enhance the accuracy of computational perception and outreach the properties of each device separately. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Intelligent transportation systems Computer vision IR detection Data fusion Vehicle positioning

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MTS in False Positive Reduction for Multi-sensor fusion

MTS in False Positive Reduction for Multi-Sensor Fusion

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

作者： Woodley, Robert Gosnell, Michael Cudney, Elizabeth 21st Century Syst Inc Omaha NE 68106 USA

ISBN: (纸本)9781628410587

The Mahalanobis Taguchi System (MTS) is a relatively new tool in the vehicle health maintenance domain, but has some distinct advantages in current multi-sensor implementations. The use of Mahalanobis Spaces (MS) allows the algorithm to identify characteristics of sensor signals to identify behaviors in machines. MTS is extremely powerful with the caveat that the correct variables are selected to form the MS. In this research work, 56 sensors monitor various aspects of the vehicles. Typically, using the MTS process, identification of useful variables is preceded by validation of the measurements scale. However, the MTS approach doesn't directly include any mitigating steps should the measurement scale not be validated. Existing work has performed outlier removal in construction of the MS, which can lead to better validation. In our approach, we modify the outlier removal process with more liberal definitions of outliers to better identify variables' impact prior to identification of useful variables. This subtle change substantially lowered the false positive rate due to the fact that additional variables were retained. Traditional MTS approaches identify useful variables only to the extent they provide usefulness in identifying the positive (abnormal) condition. The impact of removing false negatives is not included. Initial results show our approach can reduce false positive values while still maintaining complete fault identification for this vehicle data set.

关键词： Mahalanobis-Taguchi System Multi-sensor fusion Variable Selection Threshold Selection Vehicle Health Maintenance Fault Detection False Positive Reduction Comparison of Methods

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architectures and algorithms for Non-cooperative Sense and Avoid

Architectures and Algorithms for Non-cooperative Sense and A...

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IEEE International Workshop on Metrology for Aerospace (MetroAeroSpace)

作者： Tirri, Anna Elena Fasano, Giancarmine Accardo, Domenico Moccia, Antonio Univ Naples Federico II DII Naples Italy

ISBN: (纸本)9781479920693

The paper focuses on research results relevant to non-cooperative sense and avoid based on different sensing architectures and algorithms. In particular, first a radar/electrooptical system is presented where real time data fusion is based on a central level scheme and an Extended Kalman Filter. It was validated in flight tests carried out in the framework of TECVOL project carried out by the Italian Aerospace Research Centre (CIRA) and the University of Naples "Federico ii". In order to evaluate the impact of innovative technologies on system performance, solutions based on Particle Filtering are then introduced which have been developed and implemented in radar-only framework for off-line simulations, taking advantage from sensor data gathered in flight. Finally, algorithms relevant to vision-based sense and avoid are briefly presented, and preliminary results based on flight images in near collision scenarios are discussed.

关键词： Unmanned Aircraft Systems Non-cooperative Sense and Avoid Multi-sensor Systems Vision-based detection and tracking

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Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2014

Multisensor, Multisource Information Fusion: Architectures, ...

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Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2014

ISBN: (纸本)9781628410587

The proceedings contain 22 papers. The topics discussed include: embedding the results of focused Bayesian fusion into a global context;new results in semi-supervised learning using adaptive classifier fusion;probabilistic multi-source multi-INT Intel fusion benefit analysis;multi-sensor fusion with non-optimal decision rules: the challenges of open world sensing;characterization of computer network events through simultaneous feature selection and clustering of intrusion alerts;a metamaterial-inspired combined inductive-capacitive sensor;synchronous radiation sensing and 3D urban mapping for improved source identification;on an efficient and effective intelligent transportation system (ITS) using field and simulation data;and detection of oil pollution along the pipeline routes in tropical ecosystem from multi-spectral data.

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