autonomous search (46 Ergebnisse)

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Zustand: New. KlappentextrnrnThe purpose of this study is to investigate how a simulation model can accurately represent the performance of the autonomous wide area search munitions, and to find the effectiveness of the cooperative behavior on the autonomous .

Zustand: New. KlappentextrnrnThe problem being addressed is how to best find and engage an unknown number of targets in unknown locations (some moving) using multiple autonomous wide area search munitions. In this research cooperative behavior is being invest.

Zustand: New. KlappentextrnrnThis research investigates the effectiveness of autonomous wide area search munitions using cooperative and non-cooperative behavior algorithms under various scenarios. The scenarios involve multiple autonomous munitions searching.

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Zustand: New. KlappentextrnrnThis thesis considers the optimal employment of a wide area search munition in a battlespace where a target is known to be uniformly distributed among false targets which are Poisson distributed. The Poisson distribution s paramet.

Zustand: New. KlappentextrnrnThe purpose of this research is to investigate the effectiveness of wide-area search munitions in various scenarios using different cooperative behavior algorithms. The general scenario involves multiple autonomous munitions searc.

Zustand: New. KlappentextrnrnAnalytic system effectiveness measures are derived using applied probability theory. The effectiveness measures handle time-varying parameters which characterize the battle space environment and the performance of the system. This.

Taschenbuch. Zustand: Neu. Neuware - The purpose of this study is to investigate how a simulation model can accurately represent the performance of the autonomous wide area search munitions, and to find the effectiveness of the cooperative behavior on the autonomous munitions. As a prediction tool for measuring the performance of the virtual weapon systems, simulation models are established because there are insufficient analytical tool for the prediction of weapon system performance. Though the simulation models may not accurately represent the actual autonomous weapon system, the result of the simulation may provide expectations of the performance of the autonomous munitions in actual battlefield scenarios. Several assumptions and limitations are necessary in dealing with the problem for the purpose of the simplicity. The assumptions and limitations will be presented in this thesis. Two simulation models were used in this research. One is a highly simplified model for validity investigation, and the other is an AFRL/VACA model which is still in development phase to investigate the effectiveness of cooperative behavior. The simulation result from the simplified simulation model will be compared to the calculated performance predicted from an analytical tool for validity investigation, and it will also dominate the potential effectiveness of cooperative behavior. The result from the AFRL/VACA simulation will also present the effectiveness of cooperative behavior in the virtual weapon system.

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Taschenbuch. Zustand: Neu. Neuware - The problem being addressed is how to best find and engage an unknown number of targets in unknown locations (some moving) using multiple autonomous wide area search munitions. In this research cooperative behavior is being investigated to improve the overall mission effcctiveness. A cornputer simulation was used to emulate the behavior of autonomous wide area search munitions and measure their overall expected performance. This code was modified to incorporate the capability for cooperative engagement based on a parameterized decision rule. Using Design of Experiments (DOE) and Response Surface Methodologies (RSM), the simulation was run to achieve optimal decision rule pararneters for given scenarios and to determine the sensitivities of those parameters to the precision of the Autonomous Target Recognition (ATR) algorithm, guidance precision and lethality of the warhead, and the characteristics of the battlefield. Results show that the form of cooperative engagement used in this study is most useful in overcoming the limitations on warhead lethality and, to a lesser degree, probability of target report (PTR). However, cooperative engagement alone is not able to compensate for higher false target attack rates. Also, the selection of the optimal weights in the decision algorithm are very sensitive to all battlefield characteristics.

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Taschenbuch. Zustand: Neu. Neuware - This research investigates the effectiveness of autonomous wide area search munitions using cooperative and non-cooperative behavior algorithms under various scenarios. The scenarios involve multiple autonomous munitions searching for an unknown number of targets with different priorities at unknown locations. For the cooperative cases, communications are allowed between the munitions to help locate, identify, and decide to pursue an attack on a target or to continue searching the rest of the battlefield. For non cooperative cases, munitions independently search, detect, identify and decide to attack an identified target or continue to search. Performance of the cooperative munitions depends on numerous parameters such as target types, number, mobility, battlefield characteristics, warhead lethality, decision objectives, and variability in the battlefield. The results were examined under characteristics of warhead lethality, ATR capability, false target attack rate, number of munitions deployed in the simulation, and search weight. Cooperative munitions demonstrated significant decrease in the number of killed targets. Cooperative behavior reduced the number of false target attacks significantly.

Taschenbuch. Zustand: Neu. Neuware - This thesis considers the optimal employment of a wide area search munition in a battlespace where a target is known to be uniformly distributed among false targets which are Poisson distributed. The Poisson distribution's parameter is obtained from readily available battlespace intelligence. This work formulates and solves the optimal control problem for deriving the optimal sensor threshold schedule in order to maximize the probability of attacking the target during the battlespace sweep while constraining the probability of attacking a false target. The e ciency gained by optimally varying the sensor threshold is compared against the performance achieved with a static, optimum sensor threshold setting. The Weapon Operating Characteristic, the relationship between maximum achievable probability of target attack and maximum allowable probability of false target attack, is developed.

Taschenbuch. Zustand: Neu. Neuware - The purpose of this research is to investigate the effectiveness of wide-area search munitions in various scenarios using different cooperative behavior algorithms. The general scenario involves multiple autonomous munitions searching for an unknown number of targets of different priority in unknown locations. Three cooperative behavior algorithms are used in each scenario: no cooperation, cooperative attack only, and cooperative classification and attack. In the cooperative cases, the munitions allocate tasks on-line as a group, using linear programming techniques to determine the optimum allocation. Each munition provides inputs to the task allocation routine in the form of probabilities of successfully being able to complete the various tasks. These probabilities of success are based on statistical Poisson field theory. Weighting parameters are applied to the probabilities of success so that optimum settings can be determined via Response Surface Methodology. Results are compared within and across the various scenarios. Initial results did not reflect expected behavior (due to poor choice of responses to optimize). Experiments were modified and more desirable results obtained. In general, cooperative engagement alone attacks and kills fewer targets than no cooperation. Cooperative classification however, kills fewer targets at low false target attack rates (less than 0.005/km2), but outperforms the other algorithms as the false target attack rate increases. This is due primarily to the fact that cooperative classification significantly reduces and stabilizes the effective false target attack rate.

Taschenbuch. Zustand: Neu. Neuware - Analytic system effectiveness measures are derived using applied probability theory. The effectiveness measures handle time-varying parameters which characterize the battle space environment and the performance of the system. This allows the formulation and solution of optimization problems that maximize the probability of target attacks while at the same time constraining the probability of false target attacks.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Search and Classification Using Multiple Autonomous Vehicles provides a comprehensive study of decision-making strategies for domain search and object classification using multiple autonomous vehicles (MAV) under both deterministic and probabilistic frameworks. It serves as a first discussion of the problem of effective resource allocation using MAV with sensing limitations, i.e., for search and classification missions over large-scale domains, or when there are far more objects to be found and classified than there are autonomous vehicles available. Under such scenarios, search and classification compete for limited sensing resources. This is because search requires vehicle mobility while classification restricts the vehicles to the vicinity of any objects found. The authors develop decision-making strategies to choose between these competing tasks and vehicle-motion-control laws to achieve the proposed management scheme. Deterministic Lyapunov-based, probabilistic Bayesian-based, and risk-based decision-making strategies and sensor-management schemes are created in sequence. Modeling and analysis include rigorous mathematical proofs of the proposed theorems and the practical consideration of limited sensing resources and observation costs. A survey of the well-developed coverage control problem is also provided as a foundation of search algorithms within the overall decision-making strategies. Applications in both underwater sampling and space-situational awareness are investigated in detail. The control strategies proposed in each chapter are followed by illustrative simulation results and analysis. Academic researchers and graduate students from aerospace, robotics, mechanical or electrical engineering backgrounds interested in multi-agent coordination and control, in detection and estimation or in Bayes filtration will find this text of interest.

Taschenbuch. Zustand: Neu. Search and Classification Using Multiple Autonomous Vehicles | Decision-Making and Sensor Management | Yue Wang (u. a.) | Taschenbuch | Lecture Notes in Control and Information Sciences | xvi | Englisch | 2012 | Springer | EAN 9781447129561 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Improving Search Performance in Unstructured P2P Networks | Autonomous Data Replication and Distributed Search | Sabu M Thampi | Taschenbuch | 160 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838390666 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. USING AUTONOMOUS COLLABORATIVE SOFTWARE AGENTS | TO CREATE A PERSONAL INTERNET SEARCH ASSISTANT | David Byer | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639202137 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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