903 resultados para Unmanned Aerial Vehicles (UAVs)


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Aerial view of the Chapman College campus residence halls, Orange, California.

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Aerial view of the Chapman College campus, Orange, California. Looking northwest; the Moulton Fine Arts complex is at lower right. After 1978.

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Color postcard featuring an aerial view of the Chapman College campus, Orange, California, ca. 1995. Looking north. On message side: "Produced by Wayne Salvatti/Photografx; Copyright Photografx"

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Aerial view of the Chapman College campus, Orange, California, looking east. Memorial Hall is in the center, facing lawn and North Glassell Street.

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Aerial view of the Hutton Sports Center, 219 E. Sycamore Street, Chapman College, Orange, California. The Harold Hutton Sports Center, completed in 1978, is named in honor of this former trustee, and made possible by a gift from his widow, Betty Hutton Williams. Renovated in the mid-1990s.

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This collection contains 129 aerial photographs of the Niagara region. The dates vary from 1921-1991, with some photos undated. Some of the areas covered include the Welland Canal, the Queen Elizabeth Way (QEW), Niagara Falls, the Short Hills, and St. Catharines. Most of the photos are black and white.

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A new localization approach to increase the navigational capabilities and object manipulation of autonomous mobile robots, based on an encoded infrared sheet of light beacon system, which provides position errors smaller than 0.02m is presented in this paper. To achieve this minimal position error, a resolution enhancement technique has been developed by utilising an inbuilt odometric/optical flow sensor information. This system respects strong low cost constraints by using an innovative assembly for the digitally encoded infrared transmitter. For better guidance of mobile robot vehicles, an online traffic signalling capability is also incorporated. Other added features are its less computational complexity and online localization capability all these without any estimation uncertainty. The constructional details, experimental results and computational methodologies of the system are also described

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Previous research has shown that site-specific nitrogen (N) fertilizer recommendations based on an assessment of a soil’s N supply (mineral N testing) and the crop’s N status (sap nitrate analysis) can help to decrease excessive N inputs for winter wheat on the North China Plain. However, the costs to derive such recommendations based on multiple sampling of a single field hamper the use of this approach at the on-farm level. In this study low-altitude aerial true-color photographs were used to examine the relationship between image-derived reflectance values and soil–plant data in an on-station experiment. Treatments comprised a conventional N treatment (typical farmers’ practice), an optimum N treatment (N application based on soil–plant testing) and six treatments without N (one to six cropping seasons without any N fertilizer input). Normalized intensities of the red, green and blue color bands on the photographs were highly correlated with total N concentrations, SPAD readings and stem sap nitrate of winter wheat. The results indicate the potential of aerial photography to determine in combination with on site soil–plant testing the optimum N fertilizer rate for larger fields and to thereby decrease the costs for N need assessments.

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Estudi de l’eficiència aerodinàmica de les carrosseries de vehicles pesants de cara a reduir el consum de combustible en autocars de llarg trajecte. L’estudi es basa en tres aspectes: validació del programa de simulació, estudi aerodinàmic de diferents carrosseries d’autocar de mercat i estudi aerodinàmic de diferents complements

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L’objecte d’aquest estudi consisteix en determinar la influència de l’ús del biodièsel en: 1.- Les variacions en comparació amb el combustible convencional (gasoil A) en les emissions de gasos i partícules contaminants en motors de vehicles pesants de transport de mercaderies. 2.- Les variacions en comparació amb el combustible convencional (gasoil A) en el nivell de so emès per motors de vehicles pesants de transport de mercaderies. 3.- Els canvis en el consum de combustible en vehicles pesants en comparació amb la utilització de gasoil A. 4.- Els problemes tècnics observats en motors de vehicles pesants de transport de mercaderies durant un període de funcionament elevat

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Investigacions recents revelen com l’acció del vent lateral és un efecte molt important en bona part dels accidents ocorreguts en vehicles pesants de transport per carretera. És per això que el perfil aerodinàmic del vehicle esdevé determinant en l’avaluació de les forces laterals que hi actuen. El present projecte té per objecte determinar les forces laterals que s’exerceixen en vehicles pesants de transport de passatgers degut a l’acció del vent i investigar-ne la seva perillositat. Per fer-ho s’utilitzen models numèrics de dinàmica de fluids i, per diferents velocitats del vehicle, es simulen vents amb diferent intensitat i direcció. D’aquí es determinen unes condicions de perillositat en funció, entre d’altres variables, de l’angle d’incidència del vent i de la seva velocitat

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L’objectiu d’aquest projecte fi de carrera és en primer lloc, determinar les modificacions a realitzar en el laboratori de lubricants i combustibles de l’EPS per a la utilització de l’espectrofotòmetre d’absorció atòmica de flama; en segon lloc, posar a punt l’aparell establint els paràmetres i les condicions d’assaig idònies per a portar a terme les anàlisis de metalls de desgast presents en olis lubricants usats de motors de combustió interna. I finalment, establir un protocol de treball al laboratori i estudiar la viabilitat d’oferir el servei d’anàlisi de lubricants a empreses i particulars

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This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

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This paper describes the improvements achieved in our mosaicking system to assist unmanned underwater vehicle navigation. A major advance has been attained in the processing of images of the ocean floor when light absorption effects are evident. Due to the absorption of natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination for processing underwater images. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion. In this paper a technique to correct non-uniform lighting is proposed. The acquired frames are compensated through a point-by-point division of the image by an estimation of the illumination field. Then, the gray-levels of the obtained image remapped to enhance image contrast. Experiments with real images are presented

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Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system