2,344 research outputs found

    Automated control of hierarchical systems using value-driven methods

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    An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques

    Service-oriented agent architecture for autonomous maritime vehicles

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    Advanced ocean systems are increasing their capabilities and the degree of autonomy more and more in order to perform more sophisticated maritime missions. Remotely operated vehicles are no longer cost-effective since they are limited by economic support costs, and the presence and skills of the human operator. Alternatively, autonomous surface and underwater vehicles have the potential to operate with greatly reduced overhead costs and level of operator intervention. This Thesis proposes an Intelligent Control Architecture (ICA) to enable multiple collaborating marine vehicles to autonomously carry out underwater intervention missions. The ICA is generic in nature but aimed at a case study where a marine surface craft and an underwater vehicle are required to work cooperatively. They are capable of cooperating autonomously towards the execution of complex activities since they have different but complementary capabilities. The architectural foundation to achieve the ICA lays on the flexibility of service-oriented computing and agent technology. An ontological database captures the operator skills, platform capabilities and, changes in the environment. The information captured, stored as knowledge, enables reasoning agents to plan missions based on the current situation. The ICA implementation is verified in simulation, and validated in trials by means of a team of autonomous marine robots. This Thesis also presents architectural details and evaluation scenarios of the ICA, results of simulations and trials from different maritime operations, and future research directions

    An Autonomous Navigation System for Unmanned Underwater Vehicle

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    Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation

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    The micro-scale and meso-scale ocean dynamic processes which are nonlinear and have large variability, have a significant impact on the fisheries, natural resources, and marine climatology. A rapid, refined and sophisticated observation system is therefore needed in marine scientific research. The maneuverability and controllability of mobile sensor platforms make them a preferred choice to establish ocean observing networks, compared to the static sensor observing platform. In this study, marine vehicles are utilized as the nodes of mobile sensor networks for coverage sampling of a regional ocean area and ocean feature tracking. A synoptic analysis about marine vehicle dynamic control, multi vehicles mission assignment and path planning methods, and ocean feature tracking and observing techniques is given. Combined with the observation plan in the South China Sea, we provide an overview of the mobile sensor networks established with marine vehicles, and the corresponding simulation results

    Underwater intervention robotics: An outline of the Italian national project Maris

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    The Italian national project MARIS (Marine Robotics for Interventions) pursues the strategic objective of studying, developing, and integrating technologies and methodologies to enable the development of autonomous underwater robotic systems employable for intervention activities. These activities are becoming progressively more typical for the underwater offshore industry, for search-and-rescue operations, and for underwater scientific missions. Within such an ambitious objective, the project consortium also intends to demonstrate the achievable operational capabilities at a proof-of-concept level by integrating the results with prototype experimental systems
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