953 resultados para Navigation (Aeronautics)


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Waterways have many more ties with society than as a medium for the transportation of goods alone. Waterway systems offer society many kinds of socio-economic value. Waterway authorities responsible for management and (re)development need to optimize the public benefits for the investments made. However, due to the many trade-offs in the system these agencies have multiple options for achieving this goal. Because they can invest resources in a great many different ways, they need a way to calculate the efficiency of the decisions they make. Transaction cost theory, and the analysis that goes with it, has emerged as an important means of justifying efficiency decisions in the economic arena. To improve our understanding of the value-creating and coordination problems for waterway authorities, such a framework is applied to this sector. This paper describes the findings for two cases, which reflect two common multi trade-off situations for waterway (re)development. Our first case study focuses on the Miami River, an urban revitalized waterway. The second case describes the Inner Harbour Navigation Canal in New Orleans, a canal and lock in an industrialized zone, in need of an upgrade to keep pace with market developments. The transaction cost framework appears to be useful in exposing a wide variety of value-creating opportunities and the resistances that come with it. These insights can offer infrastructure managers guidance on how to seize these opportunities.

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This paper assesses the departure and approach operations of unmanned aircraft systems in one of the most challenging scenarios: flying under visual flight rules. Inspired by some existing procedures for (manned) general aviation, some automatic and predefined procedures for unmanned aircraft systems are proposed. Hence, standardized paths to specific waypoints close to the airport are defined for departure operations, just before starting the navigation phase. Conversely, and for the approach maneuvers, a first integration into a holding pattern near the landing runway (ideally, above it) is foreseen, followed by a standard visual-flight-rule airfield traffic pattern. This paper discuses the advantages of these operations, which aim to minimize possible conflicts with other existing aircraft while reducing the pilot-in-command workload. Finally, some preliminary simulations are shown in which these procedures have been successfully tested with simulated surrounding traffic.

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[EN]Polygonal meshes are powerful structures to represent geometric information of the Earth’s surface. In particular, triangle meshes have been massively used as a reliable way to efficiently represent the land surface with real time responses in virtual navigation. In this work we present new ideas for the underlying treatment of a mesh that improve efficiency and quality in the navigation.

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International audience

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Robot-control designers have begun to exploit the properties of the human immune system in order to produce dynamic systems that can adapt to complex, varying, real-world tasks. Jerne’s idiotypic-network theory has proved the most popular artificial-immune-system (AIS) method for incorporation into behaviour-based robotics, since idiotypic selection produces highly adaptive responses. However, previous efforts have mostly focused on evolving the network connections and have often worked with a single, preengineered set of behaviours, limiting variability. This paper describes a method for encoding behaviours as a variable set of attributes, and shows that when the encoding is used with a genetic algorithm (GA), multiple sets of diverse behaviours can develop naturally and rapidly, providing much greater scope for flexible behaviour-selection. The algorithm is tested extensively with a simulated e-puck robot that navigates around a maze by tracking colour. Results show that highly successful behaviour sets can be generated within about 25 minutes, and that much greater diversity can be obtained when multiple autonomous populations are used, rather than a single one.

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The role of odors in the long-distance navigation of birds has elicited intense debate for more than half a century. Failure to resolve many of the issues fueling this debate is due at least in part to the absence of controls for a variety of non-specific effects that odors have on the navigational process. The present experiments were carried out to investigate whether the olfactory inputs are involved only in “activation” of neuronal circuitry involved in navigation or are also playing a role in providing directional information. Experienced adult pigeons were exposed to controlled olfactory stimuli during different segments of the journey (release site vs. displacement + release site). Protein levels of IEGs (immediate early genes used to mark synaptic activity) were analyzed in areas within the olfactory/navigation avian circuitry. The results indicate that 1) exposure to natural odors at the release site (and not before) elicit greater activation across brain regions than exposure to filtered air, artificial odors, and natural odors along the entire outward journey (from home to the release site, inclusive); 2) activation of the piriform cortex in terms of odor discrimination is lateralized; 3) activation of the navigation circuitry is achieved by means of lateralized activation of piriform cortex neurons. Altogether, the findings provide the first direct evidence that activation of the avian navigation circuitry is mediated by asymmetrical processing of olfactory input occurring in the right piriform cortex.

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Telepresence robots have emerged as a new means of interaction in remote environments. However, the use of such robots is still limited due to safety and usability issues when operating in human-like environments. This work addresses these issues by enhancing the robot navigation through a collaborative control method that assists the user to negotiate obstacles. The method has been implemented in a commercial telepresence robot and a user study has been conducted in order to test the suitability of our approach.

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Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.

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