951 resultados para Bombing, Aerial
Resumo:
Understanding suicide bombing entails studying the phenomenon on three different dimensions: the suicide bomber, the terrorist organization, and the community from which suicide bombings emerge. Political and social psychology allow us to establish the reciprocal relationships that underpin the exchanges between the three dimensions. This method increases our theoretical understanding of suicide bombing by moving away from the unidimensional models that have previously dominated the terrorism literature.
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The application of pesticides and fertilizers in agricultural areas is of crucial importance for crop yields. The use of aircrafts is becoming increasingly common in carrying out this task mainly because of their speed and effectiveness in the spraying operation. However, some factors may reduce the yield, or even cause damage (e.g., crop areas not covered in the spraying process, overlapping spraying of crop areas, applying pesticides on the outer edge of the crop). Weather conditions, such as the intensity and direction of the wind while spraying, add further complexity to the problem of maintaining control. In this paper, we describe an architecture to address the problem of self-adjustment of the UAV routes when spraying chemicals in a crop field. We propose and evaluate an algorithm to adjust the UAV route to changes in wind intensity and direction. The algorithm to adapt the path runs in the UAV and its input is the feedback obtained from the wireless sensor network (WSN) deployed in the crop field. Moreover, we evaluate the impact of the number of communication messages between the UAV and the WSN. The results show that the use of the feedback information from the sensors to make adjustments to the routes could significantly reduce the waste of pesticides and fertilizers.
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A three-level satellite to ground monitoring scheme for conservation easement monitoring has been implemented in which high-resolution imagery serves as an intermediate step for inspecting high priority sites. A digital vertical aerial camera system was developed to fulfill the need for an economical source of imagery for this intermediate step. A method for attaching the camera system to small aircraft was designed, and the camera system was calibrated and tested. To ensure that the images obtained were of suitable quality for use in Level 2 inspections, rectified imagery was required to provide positional accuracy of 5 meters or less to be comparable to current commercially available high-resolution satellite imagery. Focal length calibration was performed to discover the infinity focal length at two lens settings (24mm and 35mm) with a precision of O.1mm. Known focal length is required for creation of navigation points representing locations to be photographed (waypoints). Photographing an object of known size at distances on a test range allowed estimates of focal lengths of 25.lmm and 35.4mm for the 24mm and 35mm lens settings, respectively. Constants required for distortion removal procedures were obtained using analytical plumb-line calibration procedures for both lens settings, with mild distortion at the 24mm setting and virtually no distortion found at the 35mm setting. The system was designed to operate in a series of stages: mission planning, mission execution, and post-mission processing. During mission planning, waypoints were created using custom tools in geographic information system (GIs) software. During mission execution, the camera is connected to a laptop computer with a global positioning system (GPS) receiver attached. Customized mobile GIs software accepts position information from the GPS receiver, provides information for navigation, and automatically triggers the camera upon reaching the desired location. Post-mission processing (rectification) of imagery for removal of lens distortion effects, correction of imagery for horizontal displacement due to terrain variations (relief displacement), and relating the images to ground coordinates were performed with no more than a second-order polynomial warping function. Accuracy testing was performed to verify the positional accuracy capabilities of the system in an ideal-case scenario as well as a real-world case. Using many welldistributed and highly accurate control points on flat terrain, the rectified images yielded median positional accuracy of 0.3 meters. Imagery captured over commercial forestland with varying terrain in eastern Maine, rectified to digital orthophoto quadrangles, yielded median positional accuracies of 2.3 meters with accuracies of 3.1 meters or better in 75 percent of measurements made. These accuracies were well within performance requirements. The images from the digital camera system are of high quality, displaying significant detail at common flying heights. At common flying heights the ground resolution of the camera system ranges between 0.07 meters and 0.67 meters per pixel, satisfying the requirement that imagery be of comparable resolution to current highresolution satellite imagery. Due to the high resolution of the imagery, the positional accuracy attainable, and the convenience with which it is operated, the digital aerial camera system developed is a potentially cost-effective solution for use in the intermediate step of a satellite to ground conservation easement monitoring scheme.
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This paper describes the creation of a GIS database index to the collection of historical aerial photographs of Connecticut housed in the Map and Geographic Information Center in the Homer Babbidge Library at the University of Connecticut. The index allows patrons to search for scanned aerial photograph images for a specific location across multiple years and to retrieve digital scans from the Library server. Procedures for scanning and georeferencing the images, preparing metadata for the images, and creating the GIS database index are described.
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The application of thematic maps obtained through the classification of remote images needs the obtained products with an optimal accuracy. The registered images from the airplanes display a very satisfactory spatial resolution, but the classical methods of thematic classification not always give better results than when the registered data from satellite are used. In order to improve these results of classification, in this work, the LIDAR sensor data from first return (Light Detection And Ranging) registered simultaneously with the spectral sensor data from airborne are jointly used. The final results of the thematic classification of the scene object of study have been obtained, quantified and discussed with and without LIDAR data, after applying different methods: Maximum Likehood Classification, Support Vector Machine with four different functions kernel and Isodata clustering algorithm (ML, SVM-L, SVM-P, SVM-RBF, SVM-S, Isodata). The best results are obtained for SVM with Sigmoide kernel. These allow the correlation with others different physical parameters with great interest like Manning hydraulic coefficient, for their incorporation in a GIS and their application in hydraulic modeling.
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Motivated by the growing interest in unmanned aerial system's applications in indoor and outdoor settings and the standardisation of visual sensors as vehicle payload. This work presents a collision avoidance approach based on omnidirectional cameras that does not require the estimation of range between two platforms to resolve a collision encounter. It will achieve a minimum separation between the two vehicles involved by maximising the view-angle given by the omnidirectional sensor. Only visual information is used to achieve avoidance under a bearing-only visual servoing approach. We provide theoretical problem formulation, as well as results from real flight using small quadrotors
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This article presents a novel system and a control strategy for visual following of a 3D moving object by an Unmanned Aerial Vehicle UAV. The presented strategy is based only on the visual information given by an adaptive tracking method based on the color information, which jointly with the dynamics of a camera fixed to a rotary wind UAV are used to develop an Image-based visual servoing IBVS system. This system is focused on continuously following a 3D moving target object, maintaining it with a fixed distance and centered on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation
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This work presents a solution for the aerial coverage of a field by using a fleet of aerial vehicles. The use of Unmanned Aerial Vehicles allows to obtain high resolution mosaics to be used in Precision Agriculture techniques. This report is focus on providing a solution for the full simultaneous coverage problem taking into account restrictions as the required spatial resolution and overlap while maintaining similar light conditions and safety operation of the drones. Results obtained from real field tests are finally reported
Resumo:
Remote sensing (RS) with aerial robots is becoming more usual in every day time in Precision Agriculture (PA) practices, do to their advantages over conventional methods. Usually, available commercial platforms providing off-the-shelf waypoint navigation are adopted to perform visual surveys over crop fields, with the purpose to acquire specific image samples. The way in which a waypoint list is computed and dispatched to the aerial robot when mapping non empty agricultural workspaces has not been yet discussed. In this paper we propose an offline mission planner approach that computes an efficient coverage path subject to some constraints by decomposing the environment approximately into cells. Therefore, the aim of this work is contributing with a feasible waypoints-based tool to support PA practices
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Remote sensed imagery acquired with mini aerial vehicles, in conjunction with GIS technology enable a meticulous analysis from surveyed agricultural sites. This paper sums up the ongoing work in area discretization and coverage with mini quad-?rotors applied to Precision Agriculture practices under the project RHEA.
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In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi-Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles' state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle's state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle's state for more than one minute, at real-time frame rates based, only on visual information.
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This article presents a visual servoing system to follow a 3D moving object by a Micro Unmanned Aerial Vehicle (MUAV). The presented control strategy is based only on the visual information given by an adaptive tracking method based on the colour information. A visual fuzzy system has been developed for servoing the camera situated on a rotary wing MAUV, that also considers its own dynamics. This system is focused on continuously following of an aerial moving target object, maintaining it with a fixed safe distance and centred on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation
Resumo:
In this paper, a system that allows applying precision agriculture techniques is described. The application is based on the deployment of a team of unmanned aerial vehicles that are able to take georeferenced pictures in order to create a full map by applying mosaicking procedures for postprocessing. The main contribution of this work is practical experimentation with an integrated tool. Contributions in different fields are also reported. Among them is a new one-phase automatic task partitioning manager, which is based on negotiation among the aerial vehicles, considering their state and capabilities. Once the individual tasks are assigned, an optimal path planning algorithm is in charge of determining the best path for each vehicle to follow. Also, a robust flight control based on the use of a control law that improves the maneuverability of the quadrotors has been designed. A set of field tests was performed in order to analyze all the capabilities of the system, from task negotiations to final performance. These experiments also allowed testing control robustness under different weather conditions.