摘要 :
The development and extension of unmanned aerial vehicle (UAV) capabilities has ignited a renewed interest in aerial refueling. Two methods of aerial refueling still remain: boom-receptacle and probe-drogue. The receiver aircraft ...
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The development and extension of unmanned aerial vehicle (UAV) capabilities has ignited a renewed interest in aerial refueling. Two methods of aerial refueling still remain: boom-receptacle and probe-drogue. The receiver aircraft dynamics are complex, nonlinear and cross-coupled to that of the tanker, causing relative control to be a challenge. A survey of flight control systems as applied to the problem of UAV aerial refueling has been performed. Various techniques, both classical and novel, have been applied to this control problem. Trends indicate a focused research effort within specific aspects of aerial refueling. Even with much attention being given to this field, control system designs have by no means been exhausted.
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摘要 :
The development and extension of unmanned aerial vehicle (UAV) capabilities has ignited a renewed interest in aerial refueling. Two methods of aerial refueling still remain: boom-receptacle and probe-drogue. The receiver aircraft ...
展开
The development and extension of unmanned aerial vehicle (UAV) capabilities has ignited a renewed interest in aerial refueling. Two methods of aerial refueling still remain: boom-receptacle and probe-drogue. The receiver aircraft dynamics are complex, nonlinear and cross-coupled to that of the tanker, causing relative control to be a challenge. A survey of flight control systems as applied to the problem of UAV aerial refueling has been performed. Various techniques, both classical and novel, have been applied to this control problem. Trends indicate a focused research effort within specific aspects of aerial refueling. Even with much attention being given to this field, control system designs have by no means been exhausted.
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摘要 :
The development and extension of unmanned aerial vehicle (UAV) capabilities has ignited a renewed interest in aerial refueling. Two methods of aerial refueling still remain: boom-receptacle and probe-drogue. The receiver aircraft ...
展开
The development and extension of unmanned aerial vehicle (UAV) capabilities has ignited a renewed interest in aerial refueling. Two methods of aerial refueling still remain: boom-receptacle and probe-drogue. The receiver aircraft dynamics are complex, nonlinear and cross-coupled to that of the tanker, causing relative control to be a challenge. A survey of flight control systems as applied to the problem of UAV aerial refueling has been performed. Various techniques, both classical and novel, have been applied to this control problem. Trends indicate a focused research effort within specific aspects of aerial refueling. Even with much attention being given to this field, control system designs have by no means been exhausted.
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Unmanned Aerial Vehicles or UAVs have been growing at a rapid pace due to the huge range of operations they can perform on the field. These vehicles are currently present in military applications, agricultural, rescue missions or ...
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Unmanned Aerial Vehicles or UAVs have been growing at a rapid pace due to the huge range of operations they can perform on the field. These vehicles are currently present in military applications, agricultural, rescue missions or telecommunications, among many other fields. However, some of the existing UAV solutions in the market are quite costly, not only monetarily but also in the complexity they entail. The objective of this work is to build a low-cost quadcopter (a type of UAV) and integrate it in a multi-vehicle mission simulation platform. The quadcopter is built with the help of a mounting guide and must be able to perform all basic flight operations. The simulation platform provides a flexible configuration of missions and test scenarios that allows to study the performance of the UAVs. After the integration, we will be able to analyze the interactions between real and simulated UAVs. Several tests (individual and collective) on the components used and interaction with the simulation platform are taken into account to evaluate the performance of the flight and integration with the simulation platform. With the tuning and testing done, it was possible to perform a brief flight and the virtual quadcopter managed to follow the real quadcopter's movement. With these experiments, we can conclude that it is possible to mount a low-cost quadcopter without sacrificing flight or integration in other systems.
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UAVs (Unmanned Aerial Vehicle systems) are mostly low cost systems and flexible and therefore a suitable alternative solution for aerial photogrammetry at a large scale compared with other mobile mapping systems. Compared to metri...
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UAVs (Unmanned Aerial Vehicle systems) are mostly low cost systems and flexible and therefore a suitable alternative solution for aerial photogrammetry at a large scale compared with other mobile mapping systems. Compared to metric camera systems, non-metric digital cameras are relatively inexpensive, readily avalailable, small volume, light weigh. Therefore,they are suitble for application in mini UAVs. It is a foreland task to integrate both and form a new type photogrammetric system. The contribution of this paper is fourfold. First, we will introduce the system of "UAVRS-Ⅱ". Second, we will address the camera calibration and distortion analysis process for the non-metric cameras using in the system. Third, we proposes the automatic aerial triangulation process. In this part, we put forward the method to reject rough error in aerial triangulation step by step based on trifocal tensor in computer vision as well as the free net bundle adjustment in photogrammetry. Fourth, we not only generate the digital orthophotos at scale of 2000 with aerial photographs collected from a test flight executed in the city of Huishui ,Guizhou province at average scale of 1:9 000, but also give the accuracy of the results of aerial triangulation and the orthophotos.
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Unmanned Aerial Vehicles (UAVs) have become a major part of everyday life, as well as an emerging research field, by establishing their versatility in a variety of applications. Nevertheless, this rapid spread of UAVs reputation h...
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Unmanned Aerial Vehicles (UAVs) have become a major part of everyday life, as well as an emerging research field, by establishing their versatility in a variety of applications. Nevertheless, this rapid spread of UAVs reputation has provoked serious security issues that can probably affect homeland security. Defence communities have started to investigate large field-of-view sensor-based methods to enable various civil protection applications, including the detection and localisation of flying threat objects. Counter-UAV (c-UAV) detection challenges may be granted from a fusion of sensors to enhance the confidence of flying threats identification. The real-time monitoring of the environment is absolutely rigorous and demands accurate methods to detect promptly the occurrence of harmful conditions. Deep learning (DL) based techniques are capable of tackling the challenges that are associated with generic objects detection and explicitly UAV identification. In this paper, we present a novel multimodal DL methodology that combines data from individual unimodal approaches that are associated with UAV detection. Specifically, this work aims to identify and classify potential targets of UAVs based on fusion methods in two different cases of operational environments, i.e. rural and urban scenarios. A dedicated architecture is designed based on the development of deep neural networks (DNNs) frameworks that has been trained and validated employing real UAV flights scenarios. The proposed approach has achieved prominent detection accuracies over different background environments, exhibiting potential employment even in major defence applications.
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摘要 :
Unmanned Aerial Vehicles (UAVs) have become a major part of everyday life, as well as an emerging research field, by establishing their versatility in a variety of applications. Nevertheless, this rapid spread of UAVs reputation h...
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Unmanned Aerial Vehicles (UAVs) have become a major part of everyday life, as well as an emerging research field, by establishing their versatility in a variety of applications. Nevertheless, this rapid spread of UAVs reputation has provoked serious security issues that can probably affect homeland security. Defence communities have started to investigate large field-of-view sensor-based methods to enable various civil protection applications, including the detection and localisation of flying threat objects. Counter-UAV (c-UAV) detection challenges may be granted from a fusion of sensors to enhance the confidence of flying threats identification. The real-time monitoring of the environment is absolutely rigorous and demands accurate methods to detect promptly the occurrence of harmful conditions. Deep learning (DL) based techniques are capable of tackling the challenges that are associated with generic objects detection and explicitly UAV identification. In this paper, we present a novel multimodal DL methodology that combines data from individual unimodal approaches that are associated with UAV detection. Specifically, this work aims to identify and classify potential targets of UAVs based on fusion methods in two different cases of operational environments, i.e. rural and urban scenarios. A dedicated architecture is designed based on the development of deep neural networks (DNNs) frameworks that has been trained and validated employing real UAV flights scenarios. The proposed approach has achieved prominent detection accuracies over different background environments, exhibiting potential employment even in major defence applications.
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摘要 :
The effectiveness of Unmanned Aerial Vehicles (UAVs) is being increased to reduce the cost and risk of a mission [Doherty et al. 2000]. Since the advent of small sized but high performance UAVs, the use of a group of UAVs for perf...
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The effectiveness of Unmanned Aerial Vehicles (UAVs) is being increased to reduce the cost and risk of a mission [Doherty et al. 2000]. Since the advent of small sized but high performance UAVs, the use of a group of UAVs for performing a joint mission is of major interest. However, the development of a UAV is expensive, and a small error in automatic control results in a crash. Therefore, it is useful to develop and verify the coordination behavior of UAVs through software simulation prior to real testing. We describe how an actor-based simulation platform supports distributed simulators, and present three cooperation strategies: self-interested UAVs, sharing-based cooperation, and team-based coordination. Our experimental results show how communication among UAVs improves the overall performance of a collection of UAVs on a joint mission.
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摘要 :
The effectiveness of Unmanned Aerial Vehicles (UAVs) is being increased to reduce the cost and risk of a mission [Doherty et al. 2000]. Since the advent of small sized but high performance UAVs, the use of a group of UAVs for perf...
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The effectiveness of Unmanned Aerial Vehicles (UAVs) is being increased to reduce the cost and risk of a mission [Doherty et al. 2000]. Since the advent of small sized but high performance UAVs, the use of a group of UAVs for performing a joint mission is of major interest. However, the development of a UAV is expensive, and a small error in automatic control results in a crash. Therefore, it is useful to develop and verify the coordination behavior of UAVs through software simulation prior to real testing. We describe how an actor-based simulation platform supports distributed simulators, and present three cooperation strategies: self-interested UAVs, sharing-based cooperation, and team-based coordination. Our experimental results show how communication among UAVs improves the overall performance of a collection of UAVs on a joint mission.
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摘要 :
The recovery technology of unmanned aerial vehicle (UAV) is one of the difficulties of UAV development. This paper presents an automatic UAV recovery guide system, which is based on laser detection technology. The guide system ove...
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The recovery technology of unmanned aerial vehicle (UAV) is one of the difficulties of UAV development. This paper presents an automatic UAV recovery guide system, which is based on laser detection technology. The guide system overcomes the problem that the small-sized UAV is not suitable for accurate-point recovery. Comparing to traditional recovery system, this system has some advantage, such as high precision, round-the-clock, flexible and easy testing. Especially, it improved the application level of UAV recovery system with corresponding orientation guide model and accurate orientation tracking technology. High requirements are needed for UAV near field distance measurement with this method. This paper provides a method for UAV close quarters navigation based on laser detection technology. It is a new application for computer vision and photoelectric technology, with fast safe secret and nil interference. UAV recovery system can lead the UAV to tackle net safely. According to current UAV technology development, using laser tracking as terminal guide sensor measure equipment is feasible. The distribution of UAV collision network callback system put the laser recovery guide system behind the tackle net. When the UAV enter the callback phase, laser call back system made the UAV slide down follow the direct orbit by way of searching tracking and orientation. The UAV recovery system setups biaxial automatic turntable, measure the horizontal angle and pitch angle change, provide the deviation of current flight path and destine flight path, also provides the distance information between UAV recovery system by the way of laser measurement. This thesis analyzes the feasibility of this technology, provides the workflow of the UAV when entering the call back process. This paper also presents the correction method of laser error. The simulation result shows this distance measure system can lead the UAV call back safely.
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