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18th International conference on Information fusion (fusion)

作者： Das, Subrata Machine Analyt Cambridge MA 02138 USA

ISBN: (纸本)9780982443866

A distributed net-centric environment consist of a large variety of data fusion nodes, where each node represents a sensor, software program, machine, human operator, warfighter, or a combat unit. fusion nodes can be conceptualized as intelligent autonomous agents that communicate, coordinate, and cooperate with each other in order to improve their local situational awareness (SA), and to assess the situation of the operational environment as a whole. In this paper, we describe how we model this net-centric SA problem using a distributed belief propagation paradigm. A local fusion node maintains the joint state of the set of variables modeling a local SA task at hand using Bayesian network (BN) fragments. Local fusion nodes communicate their beliefs and coordinate with each other to update their local estimates of the situation and contribute to the global SA of the environment. We have implemented the propagation paradigm to determine threat out of terrorist dirty bombs with agents searching unstructured intelligence reports for evidence and assessing local situations via BN fragments. The paradigm provides an important foundation of our company's cutting-edge predictive analytics platforms offering to solve enterprise distributed big data search and analytics problems.

关键词： Net-centric environment high-level fusion situation assessment distributed belief propagation Bayesian networks

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Adaptive remote-sensing techniques implementing swarms of mobile agents

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3713卷 160-177页

作者： Cameron, Stewart M. Loubriel, Guillermo M. Robinett, Rush D. III Stantz, Keith M. Trahan, Michael W. Wagner, John S. Sandia Natl Lab Albuquerque United States

ISBN: (纸本)0819431877

Measurement and signal intelligence (MASINT) of the battlespace has created new requirements in information management, communication and interoperability as they effect surveillance and situational awareness. In many situations, stand-off remote-sensing and hazard-interdiction techniques over realistic operational areas are often impractical and difficult to characterize. An alternative approach is to implement adaptive remote-sensing techniques with swarms of mobile agents employing collective behavior for optimization of mapping signatures and positional orientation (registration). We have expanded intelligent control theory using physics-based collective behavior models and genetic algorithms to produce a uniquely powerful implementation of distributed ground-based measurement incorporating both local collective behavior, and inter-operative global optimization for sensor fusion and mission oversight. By using a layered hierarchical control architecture to orchestrate adaptive reconfiguration of semi-autonomous robotic agents, we can improve overall robustness and functionality in dynamic tactical environments without information bottlenecking. In our concept, each sensor is equipped with a miniaturized optical reflectance modulator which is interactively monitored as a remote transponder using a laser communication protocol from a remote mothership or operative. Robot data-sharing at the ground level can be leveraged with global evaluation criteria, including terrain overlays and remote imaging data. Information sharing and distributed intelligence opens up a new class of remote sensing applications in which small single-function autonomous observers at the local level can collectively optimize and measure large scale ground-level signatures. As the need for coverage and the number of agents grows to improve spatial resolution, cooperative behavior orchestrated by a global situational awareness umbrella will be an essential ingredient to offset increasing bandw

关键词： Remote sensing

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Multi-sensor integration in intelligent robotic workstation

Multi-sensor integration in intelligent robotic workstation

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Proceedings of the 1992 IEEE International conference on robotics and Automation

作者： Chen, Qin Luh, J.Y.S.

ISBN: (纸本)0818627204

The method of relaxation labeling, which is a parallel distributed processing mechanism, is presented. Relaxation labeling is able to integrate the sensor data with some known knowledge. Such an integration is implemented by forcing constraint satisfaction. One type of constraint satisfaction in intelligent robotic systems is described. A relaxation labeling algorithm is presented. The local convergence properties of a labeling process are established. Its global behavior was examined numerically. To illustrate its potential applications in robotic workstations, the relaxation labeling algorithm was applied to perform an object identification task in an intelligent robotic workstation with two cameras.

关键词： sensor data fusion

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Collaborative multi-modality target classification in distributed sensor networks

Collaborative multi-modality target classification in distri...

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5th International conference on Information fusion, fusion 2002

作者： Wang, Xiaoling Qi, Hairong Iyengar, S. Sitharama Department of Electrical and Computer Engineering University of Tennessee Knoxville TN 37996 United States Department of Computer Science Louisiana State University Baton Rouge LA 70803 United States

ISBN: (纸本)0972184414

A new computing paradigm which utilizes mobile agents to carry out collaborative target classification in distributed sensor networks is presented in this paper. Instead of each sensor sending local classification results to a processing center where the fusion process is taken place, a mobile agent is dispatched from the processing center and the fusion process is executed at each sensor node. The advantage of using mobile agent is that it achieves progressive accuracy and is task-adaptive. To improve the accuracy of classification, we implement Behavior Knowledge Space method for multi-modality fusion. We also modified the classical k-nearest-neighbor method to be adaptive to collaborative classification in a distributed network of sensor nodes. Experimental results based on a field demo are presented at the end of the paper. © 2002 Int. Soc. of Information fusion.

关键词： Mobile agents

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Using Trust in distributed Consensus with Adversaries in sensor and Other Networks 17

Using Trust in Distributed Consensus with Adversaries in Sen...

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17th International conference on Information fusion (fusion)

作者： Liu, Xiangyang Baras, John S. Univ Maryland Coll Pk Syst Res Inst College Pk MD 20742 USA

ISBN: (纸本)9781479916344

Extensive research efforts have been devoted to distributed consensus with adversaries. Many diverse applications drive this increased interest in this area including distributed collaborative sensor networks, sensor fusion and distributed collaborative control. We consider the problem of detecting Byzantine adversaries in a network of agents with the goal of reaching consensus. We propose a novel trust model that establishes both local trust based on local evidences and global trust based on local exchange of local trust values. We describe a trust-aware consensus algorithm that integrates the trust evaluation mechanism into the traditional consensus algorithm and propose various local decision rules based on local evidence. To further enhance the robustness of trust evaluation itself, we also provide a trust propagation scheme in order to take into account evidences of other nodes in the network. The algorithm is flexible and extensible to incorporate more complicated designs of decision rules and trust models. Then we show by simulation that the trust-aware consensus algorithm can effectively detect Byzantine adversaries and excluding them from consensus iterations even in sparse networks with connectivity less than 2f + 1, where f is the number of adversaries. These results can be applied for fusion of trust evidences as well as for sensor fusion when malicious sensors are present like for example in power grid sensing and monitoring.

关键词： distributed consensus trust adversaries

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Real-Time Common Awareness in Communication Constrained sensor Systems

Real-Time Common Awareness in Communication Constrained Sens...

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12th International conference on Information fusion

作者： van Foeken, Eelke Kester, L. J. H. M. van Iersel, M. TNO Def & Secur UvA Oude Waalsdorperweg 63 NL-2597 AK The Hague Netherlands

ISBN: (纸本)9780982443804

sensor systems need to be more adaptive to perform well in dynamically changing environments. Common awareness in sensor systems enables distributed agents to perform. coordinated actions and reason about other agents. In addition, physical distribution of the agents in the network prevent a single point of failure and provides distributed sensing, but introduces the problem of communication constraints (e.g. bandwidth and latency), especially in complex sensors with large amounts of data. Therefore, the general aim is to develop evaluation methods that enable each agent to determine the reward of information coming from its own sensors by balancing the value and the cost (determined by the communication constraints). The value of information is determined by the global need for information. These evaluation methods are adaptive to changing, and possibly multiple and multi-dimensional requests and to changing communication constraints. In this paper the main focus lies on how to deal with latency.

关键词： Intelligent sensor Network Information Value Communication Constraints Timeliness NAIHS

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Self-organized task assignment for distributed sensors

Self-organized task assignment for distributed sensors

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conference on sensor fusion and Decentralized Control in robotic Systems III

作者： Molnár, P Lockett, EJ Kaplan, LM Clark Atlanta Univ Ctr Theoret Studies Phys Syst Atlanta GA 30314 USA

ISBN: (纸本)0819438618

A new paradigm in ground surveillance consists of swarms of autonomous internetted sensors that can be used for target localization and environmental monitoring. The individual component is an inexpensive device containing multiple sensor types, a processor and wireless communication hardware. Scattered over a certain region, these devices are able to detect the direction or proximity of targets. One of the most limiting factor of the devices is the battery supply. In order to conserve power, these units should be able to adjust their activities to the current situations. Energy consuming signal processing should only be performed if the quality of the raw sensor data promises a significant improvement to the localization results. We propose a self-organized control system that allows the devices to select the algorithm complexity which balances the requirements for good localization performance and energy conservation. The devices make their selection autonomously, based on their own sensor data, information that they receive from other devices in the region, and the amount of energy they have left. The capability of this system will be demonstrated via computer simulations.

关键词： acoustic sensors ground sensors distributed decision making self-organization

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A distributed MULTIsensor BLACKBOARD SYSTEM FOR AN AUTONOMOUS ROBOT 7

A DISTRIBUTED MULTISENSOR BLACKBOARD SYSTEM FOR AN AUTONOMOU...

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sensor fusion VII conference

作者： KAPPEY, D POKRANDT, P SCHLOEN, J UNIV KARLSRUHE INST REAL TIME COMP SYST & ROBOTD-76128 KARLSRUHEGERMANY

ISBN: (纸本)0819416908

sensoric data enable a robotic system to react to events occurring in its environment Much work has been done on the development of various sensors and algorithms to extrt information from an environment On the other hand, only little work has been done in the field of multisensor communication. This paper presents a shared memory based communication protocol that has been developed for the autonomous robot system KAMRO. This system consists of two PUMA 260 manipulators and an omnidirectionally driven mobile platform. The proposed approach is based on logical sensors, which can be used to dynamically build hierarchical sensor units. The protocol uses a distributed blackboard structure for the transmission of sensor data and commands. To support asynchronous coupling of robots and sensors, it not only transfers single sensor values, but also offers functions to estimate future values. © 1994 SPIE. All rights reserved.

关键词： sensor BLACKBOARD distributed MULTIsensor SYSTEM sensor SYSTEMS FOR ROBOTS

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Deployment of an unreliable robotic sensor network for spatial estimation 49

Deployment of an unreliable robotic sensor network for spati...

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49th IEEE conference on Decision and Control (CDC)

作者： Cortes, Jorge Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92103 USA

ISBN: (纸本)9781424477463

This paper studies an optimal deployment problem for a network of robotic sensors moving in the real line. Consider the scenario where each sensor is to take a measurement of a spatial process of interest and send it back to a data fusion center. Assume only a specific fraction of the messages containing the measurements will arrive at the center. We show that, for several fraction values, the optimal deployment configurations have the following features: agents are grouped into clusters, the clusters are deployed optimally as if at least a message from each cluster was guaranteed to reach the center, and for each fraction value, there is a specific optimal cluster size. The technical approach combines convex analysis, nonsmooth analysis, and combinatorics.

关键词： sensor networks

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distributed data fusion in a ground sensor network

Distributed data fusion in a ground sensor network

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Proceedings of the Seventh International conference on Information fusion, fusion 2004

作者： Brännström, Mikael Lennartsson, Ron Lauberts, Andris Habberstad, Hans Holmberg, Martin Swedish Defence Research Agency P.O. Box 1165 SE-581 11 Linköping Sweden

ISBN: (纸本)917056115X

In order to fuse data from a distributed sensor system, different fusion architectures can be chosen. In this work, distributed data fusion has been applied to data from a ground sensor network. Measurements have been made using five seismic and five acoustic sensor nodes, each consisting of three sensors, on vehicles of five different types. The data were analyzed off-line to achieve tracking and classification of the vehicles. The tracking was made using standard Kalman filters, and classification was made by a combination of a Bayes' classifier and voting. The information system, which made distributed data fusion possible, was based on a combination of intelligent agents and a distributed look-up table for data storage and retrieval. The results indicate that this system can operate on-line with a high accuracy in both tracking and classification.

关键词： sensor data fusion

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