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检索条件"任意字段=Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2014"

共 283 条记录，以下是111-120 订阅

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Using Conceptual Spaces to Fuse Knowledge from Heterogeneous Robot Platforms

Using Conceptual Spaces to Fuse Knowledge from Heterogeneous...

引用

Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Kira, Zsolt Georgia Tech Mobile Robot Lab Atlanta GA 30308 USA

ISBN: (纸本)9780819481740

As robots become more common, it becomes increasingly useful for many applications to use them in teams that sense the world in a distributed manner. In such situations, the robots or a central control center must communicate and fuse information received from multiple sources. A key challenge for this problem is perceptual heterogeneity, where the sensors, perceptual representations, and training instances used by the robots differ dramatically. In this paper, we use Gardenfors' conceptual spaces, a geometric representation with strong roots in cognitive science and psychology, in order to represent the appearance of objects and show how the problem of heterogeneity can be intuitively explored by looking at the situation where multiple robots differ in their conceptual spaces at different levels. To bridge low-level sensory differences, we abstract raw sensory data into properties (such as color or texture categories), represented as Gaussian Mixture Models, and demonstrate that this facilitates both individual learning and the fusion of concepts between robots. Concepts (e.g. objects) are represented as a fuzzy mixture of these properties. We then treat the problem where the conceptual spaces of two robots differ and they only share a subset of these properties. In this case, we use joint interaction and statistical metrics to determine which properties are shared. Finally, we show how conceptual spaces can handle the combination of such missing properties when fusing concepts received from different robots. We demonstrate the fusion of information in real-robot experiments with a Mobile Robots Amigobot and Pioneer 2DX with significantly different cameras and (on one robot) a SICK lidar.

关键词： Conceptual Spaces Cognitive Sensor fusion Heterogeneous Robot Teams

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Integrating perception and problem solving to predict complex object behaviours

Integrating perception and problem solving to predict comple...

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Lyons, Damian M. Chaudhry, Sirhan Agica, Marius Monaco, John Vincent Fordham Univ Robot & Comp Lab Bronx NY 10458 USA Pace Univ Dept Comp Sci New York NY 10023 USA

ISBN: (纸本)9780819481740

One of the objectives of Cognitive Robotics is to construct robot systems that can be directed to achieve real-world goals by high-level directions rather than complex, low-level robot programming. Such a system must have the ability to represent, problem-solve and learn about its environment as well as communicate with other agents. In previous work, we have proposed ADAPT, a Cognitive Architecture that views perception as top-down and goal-oriented and part of the problem solving process. Our approach is linked to a SOAR-based problem-solving and learning framework. In this paper, we present an architecture for the perceptive and world modelling components of ADAPT and report on experimental results using this architecture to predict complex object behaviour. A novel aspect of our approach is a 'mirror system' that ensures that the modelled background and foreground objects are synchronized with observations and task-based expectations. This is based on our prior work on comparing real and synthetic images. We show results for a moving object that collides and rebounds from its environment, hence showing that this perception-based problem solving approach has the potential to be used to predict complex object motions.

关键词： cognitive robotics problem-solving simulation computer vision sensory fusion

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Data fusion and Classification Using a Hybrid Intrinsic Cellular Inference Network

Data Fusion and Classification Using a Hybrid Intrinsic Cell...

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Woodley, Robert Walenz, Brett Seiffertt, John Robinette, Paul Wunsch, Donald 21st Century Syst Inc 199 E 4th St Ft Leonard Wood MO 65473 USA 21st Century Syst Inc Omaha NE 68106 USA Missouri Univ Sci & Technol Rolla MO 65409 USA

ISBN: (纸本)9780819481740

Hybrid Intrinsic Cellular Inference Network (HICIN) is designed for battlespace decision support applications. We developed an automatic method of generating hypotheses for an entity-attribute classifier. The capability and effectiveness of a domain specific ontology was used to generate automatic categories for data classification. Heterogeneous data is clustered using an Adaptive Resonance Theory (ART) inference engine on a sample (unclassified) data set. The data set is the Lahman baseball database. The actual data is immaterial to the architecture, however, parallels in the data can be easily drawn (i.e., "Team" maps to organization, "Runs scored/allowed" to Measure of organization performance (positive/negative), "Payroll" to organization resources, etc.). Results show that HICIN classifiers create known inferences from the heterogonous data. These inferences are not explicitly stated in the ontological description of the domain and are strictly data driven. HICIN uses data uncertainty handling to reduce errors in the classification. The uncertainty handling is based on subjective logic. The belief mass allows evidence from multiple sources to be mathematically combined to increase or discount an assertion. In military operations the ability to reduce uncertainty will be vital in the data fusion operation.

关键词： Data fusion Data Reasoning Adaptive Resonance Theory Machine learning Heterogeneous data sources Data uncertainty handling Battlespace situational awareness Agent-based software

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fusion of ESM reports through Dempster-Shafer and Dezert-Smarandache theories

Fusion of ESM reports through Dempster-Shafer and Dezert-Sma...

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Valin, Pierre Djiknavorian, Pascal Bosse, Eloi Grenier, Dominic R&D Canada Valcartier Decis Support Syst Sect C2 2459 Blvd Pie XI Nord Quebec City PQ G3J 1X5 Canada Univ Laval Dept Genie Electr & Genie Informat Laval G1V 0A6 PQ Canada

ISBN: (纸本)9780819481740

We address the problem of fusing ESM reports by two evidential reasoning schemes, namely Dempster-Shafer theory and Dezert-Smarandache theory. These schemes provide results in different frames of discernment, but are able to fuse realistic ESM data. We discuss their advantages and disadvantages under varying conditions of sensor data certainty and fusion reliability, the latter coming from errors in the association process. A thresholded version of Dempster-Shafer theory is fine-tuned for performance across a wide range of values for certainty and reliability. The results are presented first for typical scenarios, and secondly for Monte-Carlo studies of scenarios under varying sensor certainty and fusion reliability. The results exhibit complex non-linear functions, but for which clear trends can nevertheless be extracted. A compromise has to be achieved between stability under occasional miss-associations, and reaction time latency under a real change of allegiance. The alternative way of reporting results through Dezert-Smarandache theory is studied under similar conditions, and shown to provide good results, which are however more dependent on the unreliability, and slightly less stable. In this case however, the frame of discernment is larger, and permits additional interpretations, which are outside the scope of Dempster-Shafer.

关键词： Evidential reasoning realistic data Dempster-Shafer Dezert-Smarandache

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Capturing Dynamics on Multiple Time Scales: A Multilevel fusion Approach for Cluttered Electromagnetic Data

Capturing Dynamics on Multiple Time Scales: A Multilevel Fus...

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Conference on multisensor, multisource information fusion - architectures, algorithms and applications 2010

作者： Brumby, Steven P. Myers, Kary L. Pawley, Norma H. Los Alamos Natl Lab Los Alamos NM 87545 USA

ISBN: (纸本)9780819481740

Many problems in electromagnetic signal analysis exhibit dynamics on a wide range of time scales. Further, these dynamics may involve both continuous source generation processes and discrete source mode dynamics. These rich temporal characteristics can present challenges for standard modeling approaches, particularly in the presence of nonstationary noise and clutter sources. Here we demonstrate a hybrid algorithm designed to capture the dynamic behavior at all relevant time scales while remaining robust to clutter and noise at each time scale. We draw from techniques of adaptive feature extraction, statistical machine learning, and discrete process modeling to construct our hybrid algorithm. We describe our approach and present results applying our hybrid algorithm to a simulated dataset based on an example radio beacon identification problem: civilian air traffic control. This application illustrates the multi-scale complexity of the problems we wish to address. We consider a multi-mode air traffic control radar emitter operating against a cluttered background of competing radars and continuous-wave communications signals (radios, TV broadcasts). Our goals are to find a compact representation of the radio frequency measurements, identify which pulses were emitted by the target source, and determine the mode of the source.

关键词： chirplets fast ridge pursuit logistic regression trees Kolmogorov-Smirnov test discrete process modeling

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Proceedings of SPIES: multisensor, multisource information fusion: architectures, algorithms, and applications 2008

Proceedings of SPIES: Multisensor, Multisource Information F...

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multisensor, multisource information fusion: architectures, algorithms, and applications 2008

ISBN: (纸本)9780819471659

The proceedings contain 26 papers. The topics discussed include: portable real-time color night vision;method for applying daytime colors to nighttime imagery in realtime;advances in image registration and fusion;further exploration of the object-image metric with image registration in mind;fusion of combined stereo and spectral series for obtaining 3D information;multi-class classification fusion using boosting for identifying steganography methods;comparing discrimination and CFA for selecting tracking features;real-time object-based image registration using multilayer perceptron;a heterogeneous sensor network simulation system with integrated terrain data for real-time target detection in 3D space;vehicle tracking in UAV video using multi-spectral spatiogram models;and the use of a multidimensional space for fusion candidate representation in a maritime domain awareness application.

关键词： information fusion

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information fusion across expert groups with dependent and independent components

Information fusion across expert groups with dependent and i...

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multisensor, multisource information fusion: architectures, algorithms, and applications 2009

作者： Vergara, Victor M. Xia, Shan Caudell, Thomas P. Center for High Performance Computing Center University of New Mexico Albuquerque NM 87131 United States

ISBN: (纸本)9780819476111

Predicting a single agency's effectiveness to reduce the consequences of a malicious event is a complex problem. It is even more complex to predict the overall effectiveness of a group of agencies considering the possible interdependency of their portfolio of actions. However, this is an essential task in disaster management arena. This work proposes a method to fuse individual effectiveness provided by subject matter experts, considering the dependency among agencies, to predict the holistic effectiveness. It can be applied to agency groups that are dependent, partially dependent, or completely independent. Simulation results illustrate the method. © 2009 SPIE.

关键词： information fusion

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Enhancing image fusion performance and utility for defence and security applications

Enhancing image fusion performance and utility for defence a...

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multisensor, multisource information fusion: architectures, algorithms, and applications 2009

作者： Sadler, J. Smith, M.I. Waterfall Solutions Ltd Parklands Guildford Surrey GU2 9JX United Kingdom

ISBN: (纸本)9780819476111

The real-time fusion of imagery from two or more complementary sensors offers significant operational benefits for both operator-in-the-loop and automated processing systems. This paper reports on a new image fusion framework that can be used to maximise detection, recognition and identification performance within the context of low false-alarm rate operation. The Intelligent Image fusion (I2F) architecture presented here allows exploitation of data at the information level as well as at the pixel-level, and can do so in an adaptable and intelligent manner. In this paper the architecture is examined in terms of design, applicability to a range of tasks, and performance factors such as adaptability, flexibility and utility. The relationship between algorithm design and hardware implementation, and the consequential impact on system performance, is also reviewed. Particular consideration is given to size, weight and power constraints that exist for some systems and their implications for processing optimisation and implementation on different processing platforms. Results are presented from the outcome of quantitative studies, development programmes and system trials. © 2009 SPIE.

关键词： Image fusion

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Sharing and fusing landmark information in a team of autonomous robots

Sharing and fusing landmark information in a team of autonom...

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multisensor, multisource information fusion: architectures, algorithms, and applications 2009

作者： Lyons, Damian M. Robotics and Computer Vision Laboratory Department of Computer and Information Science Fordham University Bronx NY 10458 United States

ISBN: (纸本)9780819476111

A team of robots working to explore and map a space may need to share information about landmarks so as register local maps and to plan effective exploration strategies. In this paper we investigate the use of spatial histograms (spatiograms) as a common representation for exchanging landmark information between robots. Each robot can use sonar, stereo, laser and image information to identify potential landmarks. The sonar, laser and stereo information provide the spatial dimension of the spatiogram in a landmark-centered coordinate frame while video provides the image information. We call the result a terrain spatiogram. This representation can be shared between robots in a team to recognize landmarks and to fuse observations from multiple sensors or multiple platforms. We report experimental results sharing indoor and outdoor landmark information between a two different models of robot equipped with differently configured stereocameras and show that the terrain spatiogram (1) allows the robots to recognize landmarks seen only by the other with high confidence and, (2) allows multiple views of a landmark to be fused in a useful fashion. © 2009 SPIE.

关键词： Mobile robots

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FuzzyfusionTM, an application architecture for multisource information fusion

FuzzyFusionTM, an application architecture for multisource i...

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multisensor, multisource information fusion: architectures, algorithms, and applications 2009

作者： Fox, Kevin L. Henning, Ronda R. Harris Corporation Melbourne FL 32902 United States

ISBN: (纸本)9780819476111

The correlation of information from disparate sources has long been an issue in data fusion research. Traditional data fusion addresses the correlation of information from sources as diverse as single-purpose sensors to all-source multi-media information. information system vulnerability information is similar in its diversity of sources and content, and in the desire to draw a meaningful conclusion, namely, the security posture of the system under inspection. FuzzyfusionTM A data fusion model that is being applied to the computer network operations domain is presented. This model has been successfully prototyped in an applied research environment and represents a next generation assurance tool for system and network security. © 2009 SPIE.

关键词： Data fusion

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