Publications
J. Aslam, Z. Butler, F. Constantin, V. Crespi, G. Cybenko, D. Rus. Tracking a moving object with a binary sensor network. To be presented at the ACM SenSys'03 Conference, November 5--7, 2003, Los Angeles.
Abstract: In this paper we examine the role of very simple and noisy sensors for the tracking problem. We propose a binary sensor model, where each sensor's value is converted reliably to one bit of information only: the object is moving toward the sensor or away from the sensor. We show that a network of binary sensors has geometric properties that can be used to develop a solution for tracking with binary sensors and present resulting algorithms and simulation experiments. We develop two classes of algorithms: one that assumes the sensors have no range limits and another that limits the sensor range. Our extensive simulations show low error that decreases with sensor density.
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Luis Caffarelli, Valentino Crespi, George Cybenko, Irene Gamba and Daniela Rus. Stochastic Distributed Algorithms for Target Surveillance. Accepted as a full paper for publication in the Proceedings of the conference: Intelligent Systems and Design Applications (ISDA2003), to be held in Tulsa, Oklahoma, August, 2003.
Abstract: In this paper we investigate problems of target surveillance with the aim of building a general framework for the evaluation of the performance of a system of autonomous agents. To this purpose we propose a class of semi-distributed stochastic navigation algorithms, that drive swarms of autonomous scouts to the surveillance of grounded targets, and we provide a novel approach to performance estimation based on analysing sequential observations of the system's state with information theoretical techniques. Our goal is to achieve a deeper understanding of the interrelations between randomness, resource consumption and ergodicity of a decentralized control system in which the decision--making process is stochastic.
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Valentino Crespi and George Cybenko. Decentralized Algorithms for Sensor Registration. Accepted for presentation at the 2003 International Joint Conference on Neural Networks (IJCNN2003), to be held in Portland, Oregon, July 2003, and for publication in the conference proceedings published annually by IEEE.
Abstract: In this paper we investigate a problem arising in decentralized registration of sensors. The application we consider involves a heterogeneous collection of sensors - some sensors have on-board Global Positioning System (GPS) capabilities while others do not. All sensors have wireless communications capability but the wirele ss communication has limited effective range. Sensors can communicate only with other sensors that are within a fixed distance of each other. Sensors with GPS capability are self-registering. Sensors without GPS capability are less expensive and smaller but they must compute estimates of their location using estimates of the distances between themselves and other sensors within their radio range. GPS-less sensors may be several radio hops away from GPS-capable sensors so registration must be inferred transitively. Our approach to solving this registration problem involves minimizing a global potential or penalty function by using only local information, determined by the radio range, available to each sensor. The algorithm we derive is a special case of a more general methodology we have developed called 'Emergence Engineering.'
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A. Das, G. Kantor, V. Kumar, G. Pereira, R. Peterson, D. Rus, S. Singh, J. Spletzer. Distributed Search and Rescue with Robot and Sensor Teams. In Field and Service Robotics 2003.
Q. Li, M. deRosa, D. Rus. Distributed algorithms for guiding navigation across sensor networks. In Mobicom 2003.
V. Crespi, G. Cybenko, D. Rus, M. Santini. Decentralized Control for Coordinated flow of Multi-Agent Systems. Dartmouth Technical Report TR2002-414, January, 2002. In Proceedings of the 2002 World Congress on Computational Intelligence. Honolulu, Hawaii, May 12--17, 2002.
Abstract: This paper describes a distributed algorithm for coordinating the flow of a mass of vehicles approaching a highway exit or a tollbooth. We provide the problem formulation, a general methodology for distributed control and an instantiation of this methodology to the coordinated flow problem. We analyze our algorithm and provide experimental data.
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Q. Li, J. Aslam, D. Rus. Distributed Energy-Conserving Routing Protocols for Sensor Networks. In the IEEE Hawaii International Conference on System Science, 2002.
R. Peterson and D. Rus. Interacting with a sensor network. In ACRA 2002 (November 2002).
Submitted Papers
P. Corke, R. Peterson and D. Rus. Flying robot navigation using a sensor net. Submitted to the 2003 International Symposium on Experimental Robotics.
White Papers
Valentino Crespi, George Cybenko. Agent-Based Systems Engineering and Intelligent Vehicles and Road Systems. DARPA PI TASK Meeting held in Santa Fe, NM, on April 2001.
Abstract: This report summarizes our preliminary efforts at applying the methodology and techniques of agent-based systems engineering (ABSE) to the problem of designing and operating Intelligent Roads and Vehicles Systems (IRVS). First, we briefly summarize the key elements of both agent-based systems engineering and IRVS. We then show how the taxonomy of ABSE applies to the IRVS concept and how some performance metrics can be introduced. The report concludes with plans for continued work in this direction.
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Valentino Crespi, George Cybenko, Daniela Rus. Decentralized Control and Agent-Based Systems in the framework of the IRVS. DARPA PI TASK Meeting held in Santa Fe, NM, on April 2001.
Abstract: We consider control problems that arise in the context of the IRVS. Specifically, we study the dynamics of systems of fully autonomous agents that are expected to optimize a global potential function of which they have only partial knowledge. Our ultimate goal is to characterize mathematically the global performance of agent-based systems in which the inter-agent cooperation is based on local exchange of information. First we introduce what we call the Opera Problem, a natural abstraction of a class of motion problems arising commonly in systems of autonomous vehicles. We then provide a centralized solution based on traditional control theory techniques. Finally, we present and analyze a decentralized solution.
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Other Papers
Jonathan Bredin, Daniela Rus, David Kotz. The Role of Information in Computational-Resource Allocation. Presented at the TASK Santa Fe PI meeting, held in Santa Fe, NM, on April 2001.
Abstract: We examine the role of information in markets that allocate computation to software agents. The comparison of two types of markets illuminates the importance of information and the incentives for buyers and sellers to share their preferences with each other. In our comparison, the distinguishing feature of the two markets types is the alignment of agents' interests. We define a closed-interest market as one where resources are collectively owned among the agents. An open-interest market makes no assumptions on the interests of agents or resource owners.
The incentives of agents in the two markets drastically differ. The open-interest model motivates agents to be less trusting and to not share information. This aspect stems from the model's greater applicability to resource allocation, but has a deep impact on system efficiency. In this paper, we summarize some economic theory and allegorical evidence from our models and system implementations that support the claim, and conclude with guidelines for system development.
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George Cybenko. Technical Proposal. Presented at the Kickoff TASK meeting held in Charleston, SC, on October 2000.
MS Word Document (233K)
