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International conference on Mobile Ad-hoc and sensor Networks, MSN

作者： Damianos Gavalas Ioannis E. Venetis Grammati Pantziou Charalampos Konstantopoulos Department of Cultural Technology and Communication Greece & Computer Technology Institute and Press ‘Diophantus' (CTI) Patras Greece Department of Informatics Technological Educational Institution of Athens Athens Greece Department of Informatics University of Piraeus Piraeus Greece

The investigation of mobile agent (MA) middleware as a technology for implementing efficient data fusion schemes on wireless sensor networks (WSN) has been a subject of intense research in the past few years. Nevertheless, the itineraries followed by travelling MAs largely determine the overall performance of the data fusion applications. Along this line, this article introduces a novel algorithmic approach for efficient itinerary planning of MA objects engaged in data fusion tasks. Our algorithm adopts an iterated local search (ILS) approach in deriving the hop sequence of multiple travelling MAs over the deployed source nodes. Simulation results demonstrate the performance gain of our method against existing multiple MA itinerary planning methods.

关键词： Wireless sensor networks Planning Algorithm design and analysis Data integration Clustering algorithms Mobile agents Energy consumption

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sensor fusion method for altitude estimation in mini-UAV applications

Sensor fusion method for altitude estimation in mini-UAV app...

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International conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Grigore Stamatescu Iulia Stamatescu Dan Popescu Cristian Mateescu Dpt. of Automatic Control and Industrial Informatics University “Politehnica” of Bucharest Romania Teamnet International Bucharest Romania

The emergence of unmanned aerial vehicles for large scale monitoring of ground infrastructure has challenged new designs for electronic sensor systems capable of timely, accurate and compntationally effective measurements. A conventional design issue is balancing the complexity of the sensing subsystem with advanced data processing algorithms in order to obtain quality information regarding the airplane's posture and orientation. The paper presents the generic architecture of the navigation sensing system for a fixed-wing mini-UAV, at both the physical and algorithm levels. The focus is set on a sub-problem, namely altitude estimation by sensor fusion using barometric pressure and GPS data. Results are discussed based on actual flight log data and the approach is extended towards speed estimation: air, ground and wind influence. Conclusions are drawn regarding efficient implementation of the method in relation to the onboard embedded processing capabilities.

关键词： Robot sensing systems Global Positioning System Estimation sensor fusion Pressure measurement Unmanned aerial vehicles

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PerSEE: A central sensors fusion electronic control unit for the development of perception-based ADAS

PerSEE: A central sensors fusion electronic control unit for...

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IAPR International conference on Machine Vision applications (MVA)

作者： Dominique Gruyer Rachid Belaroussi Xuanpeng Li Benoit Lusetti Marc Revilloud Sebastien Glaser Development and network Component and Systems Department Laboratory on Vehicle-Infrastructure-Driver Interactions Versailles

Automated vehicles and Advanced Driver Assistance Systems (ADAS) face a variety of complex situations that are dealt with numerous sensors for the perception of the local driving area. Going forward, we see an increasing use of multiple, different sensors inputs with radar, camera and inertial measurement the most common sensor types. Each system has its own purpose and either displays information or performs an activity without consideration for any other ADAS systems, which does not make the best use of the systems. This paper presents an embedded real-time system to combine the attributes of obstacles, roadway and ego-vehicle features in order to build a collaborative local map. This embedded architecture is called PerSEE: a library of vision-based state-of-the-art algorithms was implemented and distributed in processors of a main fusion electronic board and on smart-cameras board. The embedded hardware architecture of the full PerSEE platform is detailed, with block diagrams to illustrate the partition of the algorithm on the different processors and electronic boards. The communications interfaces as well as the development environment are described.

关键词： Vehicles Radar tracking Roads Cameras sensor fusion

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Real-time arm tracking for HMI applications

Real-time arm tracking for HMI applications

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International Workshop on Wearable and Implantable Body sensor Networks (BSN)

作者： Matthew Masters Luke Osborn Nitish Thakor Alcimar Soares Department of Biomedical Engineering Johns Hopkins University Baltimore Maryland Department of Electrical Engineering Federal University of Uberlandia Brazil

Limb tracking is an important aspect of human-machine interfaces (HMI). These systems, however, can often be limited by complex algorithms requiring significant processing power, obtrusive and immobile sensing techniques, and high costs. In this work, we utilize a sensor fusion algorithm implemented in commercial inertial measurement units (IMU) to combine accelerometer and gyroscope measurements in an effort to minimize computational requirements of the limb tracking system. In addition, previously developed methods were implemented to eliminate sensor drift by including information from a magnetometer. We tested the accuracy of our system by computing the root mean squared error (RMSE) of the true angle between the headings of two sensors and the estimate of that angle through quaternion-vector manipulations. An average RMSE of approximately 2.9° was achieved. Our limb tracking system is wearable, minimally complex, low-cost, and simple to use which has proven useful in multiple HMI applications discussed herein.

关键词： Quaternions sensor fusion Real-time systems Prosthetics Trajectory Target tracking

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Object Classification in a High-Level sensor Data fusion Architecture for Advanced Driver Assistance Systems

Object Classification in a High-Level Sensor Data Fusion Arc...

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International conference on Intelligent Transportation

作者： Michael Aeberhard Torsten Bertram Group ConnectedDrive at BMW Group Research and Technology Munich Germany Institute of Control Theory and Systems Engineering Technical University of Dortmund

Reliable estimation of an object's type is an important aspect of advanced driver assistance systems (ADAS) and automated driving applications. A type-specific ADAS reaction or object prediction can therefore be realized, improving the performance of the system. Object detection research usually focuses strongly on the state and existence estimation of detected objects. In this paper, an approach is presented for estimating an the class type of an object within the framework of a high-level sensor data fusion architecture. A novel classification fusion approach using the Dempster-Shafer evidence theory is presented. The performance of the algorithms are evaluated using a test vehicle with 12 sensors for surround environment perception in an overtaking scenario on a closed test track and on the highway in real traffic.

关键词： Vehicles Data models Data integration Training data Advanced driver assistance systems Probability Object detection

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The future of MEMS sensors in our connected world

The future of MEMS sensors in our connected world

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IEEE International conference on Micro Electro Mechanical Systems

作者： Gerhard Lammel Bosch Sensortec GmbH Reutlingen GERMANY

The MEMS market is year after year growing faster than the average semiconductor industry. Over that time the largest technology driver for MEMS changed from automotive applications to consumer electronics dominated by smartphones. Beyond that, MEMS sensors become the heart of whole classes of new devices like fitness trackers, smart watches, virtual reality glasses and smart sensor nodes for the Internet of Things. Silicon chips are only one part of the MEMS story, you need as well special mixed signal circuitry, low power data processing, smart algorithms and connectivity to transform raw signals into meaningful information. Multi-sensor applications & modules are playing an increasingly important role.

关键词： Micromechanical devices Intelligent sensors Magnetic sensors Smart phones Gyroscopes sensor fusion

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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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Data fusion Strategy for Precise Vehicle Location for Intelligent Self-Aware Maintenance Systems

Data Fusion Strategy for Precise Vehicle Location for Intell...

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International conference on Intelligent Systems, Modelling and Simulation (ISMS)

作者： M. Bevilacqua A. Tsourdos A. Starr I. Durazo-Cardenas Cranfield University United Kingdom

Nowadays careful measurement applications are handed over to Wired and Wireless sensor Network. Taking the scenario of train location as an example, this would lead to an increase in uncertainty about position related to sensors with long acquisition times like Balises, RFID and Transponders along the track. We take into account the data without any synchronization protocols, for increase the accuracy and reduce the uncertainty after the data fusion algorithms. The case studies, we have analysed, derived from the needs of the project partners: train localization, head of an auger in the drilling sector localization and the location of containers of radioactive material waste in a reprocessing nuclear plant. They have the necessity to plan the maintenance operations of their infrastructure basing through architecture that taking input from the sensors, which are localization and diagnosis, maps and cost, to optimize the cost effectiveness and reduce the time of operation.

关键词： Data integration sensor fusion Data models conferences Uncertainty Maintenance engineering

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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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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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