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检索条件"任意字段=Conference on Sensor Fusion - Architectures, Algorithms, and Applications III"

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Multi-sensory architectures for action-oriented perception

Multi-sensory architectures for action-oriented perception

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conference on Bioengineered and Bioinspired Systems iii

作者： Alba, L. Arena, P. De Fiore, S. Listan, J. Patane, L. Salem, A. Scordino, G. Webb, B. Univ Catania Dipartimento Ingn Elettr Elettron & Sistemi I-95125 Catania Italy

ISBN: (纸本)9780819467201

In order to solve the navigation problem of a mobile robot in an unstructured environment a versatile sensory system and efficient locomotion control algorithms are necessary. In this paper an innovative sensory system for action-oriented perception applied to a legged robot is presented. An important problem we address is how to utilize a large variety and number of sensors, while having systems that can operate in real time. Our solution is to use sensory systems that incorporate analog and parallel processing, inspired by biological systems, to reduce the required data exchange with the motor control layer. In particular, as concerns the visual system, we use the Eye-RIS v1.1 board made by Anafocus, which is based on a fully-parallel mixed-signal array sensor-processor chip. The hearing sensor is inspired by the cricket hearing system and allows efficient localization of a specific sound source with a very simple analog circuit. Our robot utilizes additional sensors for touch, posture, load, distance, and heading, and thus requires customized and parallel processing for concurrent acquisition. Therefore a Field Programmable Gate Array (FPGA) based hardware was used to manage the multi-sensory acquisition and processing. This choice was made because FPGAs permit the implementation of customized digital logic blocks that can operate in parallel allowing the sensors to be driven simultaneously. With this approach the multi-sensory architecture proposed can achieve real time capabilities.

关键词： FPGA multi-sensory fusion vision system hearing tactile sensors

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From Vision to Realtime Motion Control for the RoboCup Domain

From Vision to Realtime Motion Control for the RoboCup Domai...

引用

IEEE conference on Control Technology and applications (CCTA)

作者： Dennis Bruijnen Wouter Aangenent Jeroen van Helvoort Rene van de Molengraft Faculty of Mechanical Engineering Technische Universiteit Eindhoven The Netherlands

In this paper, an overview is given of how the path from vision to motion has been developed in the TechUnited team. The vision module includes: (i) color calibration using a union of convex hulls to select an area in the 3D-colorspace, (ii) automatic calibration of the mapping from the camera image to the field via a genetic algorithm, (iii) self localization based on field lines. The output of the vision module is used by the motion module which includes: (i) vision and encoder sensor fusion by monitoring the drift caused by odometry, (ii) generating a motion path complying with the robot's limitations to prevent wheel slippage, (iii) collocated motion control. In contrast to closing the loop on vision, our approach uses wheel encoders as the basis for motion control, which has several advantages such as less delay due to a higher sampling frequency. Vision is only used to compensate for slow drift caused by slip in the wheel-surface contact.

关键词： Motion control Calibration Wheels Motion planning Cameras Genetic algorithms sensor fusion Monitoring fusion power generation Mobile robots

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A fusion approach for coarse-to-fine target recognition

A fusion approach for coarse-to-fine target recognition

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conference on Multisensor, Multisource Information fusion

作者： Folkesson, Martin Gronwall, Christina Jungert, Erland Swedish Def Res Agcy FOI Box 1165 Linkoping Sweden

ISBN: (纸本)0819462985

A fusion approach in a query based information system is presented. The system is designed for querying multimedia data bases, and here applied to target recognition using heterogeneous data sources. The recognition process is coarse-to-fine, with an initial attribute estimation step and a following matching step. Several sensor types and algorithms are involved in each of these two steps. An independence of the matching results, on the origin of the estimation results, is observed. It allows for distribution of data between algorithms in an intermediate fusion step, without risk of data incest. This increases the overall chance of recognising the target. An implementation of the system is described.

关键词： fusion information system target recognition query language attribute knowledge system

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The challenge of scalable and distributed fusion of disparate sources of information

The challenge of scalable and distributed fusion of disparat...

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conference on Multisensor, Multisource Information fusion

作者： Julier, Simon J. Uhlmann, Jeffrey K. Walters, Joshua Mittu, Ranjeev Palaniappan, Kannappan ITT AES NRL 4555 Overlook Ave Washington DC 20375 USA Univ Missouri Dept Comp Sci Columbia MO 65211 USA Naval Res Lab Washington DC 20375 USA

ISBN: (纸本)0819462985

A key enabler for Network Centric Warfare (NCW) is a sensor network that can collect and fuse vast amounts of disparate and complementary information from sensors that are geographically dispersed throughout the battlespace. This information will lead to better situation awareness so that commanders will be able to act faster and more effectively. However, these benefits are possible only if the sensor data can be fused and synthesized for distribution to the right user in the right form at the right time within the constraints of available bandwidth. In this paper we consider the problem of developing Level 1 data fusion algorithms for disparate fusion in NCW. These algorithms must be capable of operating in a fully distributed (or decentralized) manner;must be able to scale to extremely large numbers of entities;and must be able to combine many disparate types of data. To meet these needs we propose a framework that consists of three main components: an attribute-based state representation that treats an entity state as a collection of attributes, new methods or interpretations of uncertainty, and robust algorithms for distributed data fusion. We illustrate the discussion in the context of maritime domain awareness, mobile adhoc networks, and multispectral image fusion.

关键词： distributed data fusion disparate data fusion generalized Covariance Intersection correlated data MANET maritime domain awareness

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Distributed sensor data compression algorithm

Distributed sensor data compression algorithm

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conference on Multisensor, Multisource Information fusion

作者： Ambrose, Barry Lin, Freddie Broadata Commun Inc 2545 W 237th St Torrance CA 90505 USA

ISBN: (纸本)0819462985

Theoretically it is possible for two sensors to reliably send data at rates smaller than the sum of the necessary data rates for sending the data independently, essentially taking advantage of the correlation of sensor readings to reduce the data rate. In 200 1, Caltech researchers Michelle Effros and Qian Zhao developed new techniques for data compression code design for correlated sensor data, which were published in a paper at the 2001 Data Compression conference (DCC 2001). These techniques take advantage of correlations between two or more closely positioned sensors in a distributed sensor network. Given two signals, X and Y, the X signal is sent using standard data compression. The goal is to design a partition tree for the Y signal. The Y signal is sent using a code based on the partition tree. At the receiving end, if ambiguity arises when using the partition tree to decode the Y signal, the X signal is used to resolve the ambiguity. We have extended this work to increase the efficiency of the code search algorithms. Our results have shown that development of a highly integrated sensor network protocol that takes advantage of a correlation in sensor readings can result in 20-30% sensor data transport cost savings. In contrast, the best possible compression using state-of-the-art compression techniques that did not take into account the correlation of the incoming data signals achieved only 9-10% compression at most. This work was sponsored by MDA, but has very widespread applicability to ad hoc sensor networks, hyperspectral imaging sensors and vehicle health monitoring sensors for space applications.

关键词： information theory data compression sensor networks

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Noise reduction method for the multi-sensor system measuring DC current

Noise reduction method for the multi-Sensor system measuring...

引用

conference on Multisensor, Multisource Information fusion

作者： Wang, Jing Geng, Yingsan Song, Zhengxiang Wang, Jianhua Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian 710049 Peoples R China

ISBN: (纸本)0819462985

Multi-sensor system has been proposed to measure electric current in a non-contact way. According to the Ampere's Law, the value of the current flowing in a conductor can be obtained through processing the outputs of the magnetic sensors around the conductor. As the discrete form of the Ampere's Law is applied, measurement noises are introduced when there exists the interference magnetic field induced by nearby current flowing conductors. In this paper, the measurement noises of the multi-sensor system measuring DC current are examined to reveal the impact of the interference magnetic field and the number of the magnetic sensors on the measurement accuracy. A noise reduction method based on Kalman filtering is presented. Computer simulation and experiment results show that the method greatly improves the accuracy without seriously increasing the computation load in comparison with other approaches.

关键词： multi-sensor noises DC current

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Decision fusion strategy for target recognition in hyperspectral images

Decision fusion strategy for target recognition in hyperspec...

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conference on Unmanned/Unattended sensors and sensor Networks iii

作者： Acito, N. Greco, M. Diani, M. Corsini, G. Dipartimento Ingn Informaz Via G Caruso 14 I-56122 Pisa Italy

ISBN: (纸本)9780819464927

Hyperspectral sensors allow a considerable improvement in the performance of a target recognition process to be achieved. This characteristic is particular interesting in a lot of military and civilian remote sensing applications, such as automatic target recognition (ATR) and surveillance of wide areas. In this framework, real time processing of the observed scenario is becoming a key issue, because it permits the operator to provide immediate assessment of the surveyed area. In the literature is presented a line-by-line real time implementation of the widely used Constrained Energy Minimization (CEM) target detector. However, experimental results show that sometimes the CEM filter produces False Alarms (FAs) corresponding to rare objects, whose spectra are angularly very different from the target signature and from the natural background classes in the image. A solution to such a problem is presented in this work: the proposed strategy is based on the decision fusion of the CEM and the SAM algorithms. Only those pixels that pass the CEM-stage are processed by the SAM algorithm. The second stage allows false alarms to be reduced by preserving most of target pixels. The fusion strategy is applied to an experimental hyperspectral data set to recognize a known green target. Detection performance is numerically evaluated and compared to the one of the classical CEM detector.

关键词： hyperspectral target recognition CEM SAM decision fusion real time implementation

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Classifiers and distance-based evidential fusion for road travel time estimation

Classifiers and distance-based evidential fusion for road tr...

引用

conference on Multisensor, Multisource Information fusion

作者： El Faouzi, N. -E. Lefevre, E. ENTPE INRETS Lab Ingn Circulat Transport 25 Ave Francois Mitterand Case 24 F-69675 Bron France Univ Artois Fac Sci Appl Lab Informat & Automat Artois LGI2A EA 3926 F-62400 Bethune France

ISBN: (纸本)0819462985

This paper addresses the road travel time estimation on an urban axis by classification method based on evidence theory. The travel time (IT) indicator can be used either for traffic management or for drivers' information. The information used to estimate the travel time (induction loop sensor, cameras, probe vehicle,...) is complementary and redundant. It is then necessary to implement strategies of multi-sensors data fusion. The selected framework is the evidence theory. This theory takes more into account the imprecision and uncertainty of multisource information. Two strategies were implemented. The first one is classifier fusion where each information source, was considered as a classifier. The second approach is a distance-based classification for belief functions modelling. Results of these approaches, on data collected on an urban axis in the South of France, show the outperformance of fusion strategies within this application.

关键词： evidence theory classifier combination travel time estimation

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Investigation of target tracking performance for unattended ground sensor networks employing Distributed Cluster Management

Investigation of target tracking performance for unattended ...

引用

conference on Multisensor, Multisource Information fusion

作者： Stelzig, Chad A. Essawy, Magdi A. Minor, Sharon Gen Dynam Adv Informat Syst 8800 Queen Ave S Bloomington MN 55431 USA US Army CECOM Ctr Night Vis & Electroopt Ft Belvoir VA 22060 USA

ISBN: (纸本)0819462985

Interest in the distribution of processing in unattended ground sensing (UGS) networks has resulted in new technologies and system designs targeted at reduction of communication bandwidth and resource consumption through managed sensor interactions. A successful management algorithm should not only address the conservation of resources, but also attempt to optimize the information gained through each sensor interaction so as to not significantly deteriorate target tracking performance. This paper investigates the effects of Distributed Cluster Management (DCM) on tracking performance when operating in a deployed UGS cluster. Originally designed to reduce communications bandwidth and allow for sensor field scalability, the DCM has also been shown to simplify the target tracking problem through reduction of redundant information. It is this redundant information that in some circumstances results in secondary false tracks due to multiple intersections and increased uncertainty during track initiation periods. A combination of field test data playback and Monte Carlo simulations are used to analyze and compare the performance of a distributed UGS cluster to that of an unmanaged centralized cluster.

关键词： unattended ground sensors Distributed Cluster Management target tracking

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A compact Millimeter Wave radar sensor for Unmanned Air Vehicles

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4th International conference on Field and Service Robotics

作者： Goktogan, Ali Haydar Brooker, Graham Sukkarieh, Salah Univ Sydney Australian Ctr Field Robot Sch Aerosp Mech & Mechatron Engn Rose St Bldg J04 Sydney NSW 2006 Australia

ISBN: (纸本)3540328017

This paper presents a compact Millimeter Wave (MMW) radar unit that has been developed to be used as a Range, Bearing and Elevation (RBE) sensor on the Brumby Mk iii Unmanned Air Vehicles (UAV). The Brumby Mkiii is the flight platform used in the Autonomous Navigation and Sensing Experimental Research (ANSER) project which is focused on the development and demonstration of the Decentralised Data fusion (DDF) and Simultaneous Localisation and Map Building (SLAM) algorithms on multiple UAVs. In the airborne DDF and SLAM demonstrations with UAVs, it is essential to have a terrain sensor on board for the RBE measurements of the ground targets. The focus of this paper is the hardware and software components of the MMW radar as an RBE sensor in the context of the ANSER project.

关键词： Unmanned aerial vehicles (UAV)

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