968 resultados para Inertial Navigation System


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No espaço tridimensional, um corpo rígido qualquer pode efetuar translações e ou rotações em relação a cada um de seus eixos. Identificar com precisão o deslocamento realizado por um corpo é fundamental para alguns tipos de sistemas em engenharia. Em sistemas de navegação inercial tradicionais, utilizam-se acelerômetros para reconhecer a aceleração linear e giroscópios para reconhecer a velocidade angular registrada durante o deslocamento. O giroscópio, entretanto, é um dispositivo de custo mais elevado e com alto consumo de energia quando comparado a um acelerômetro. Essa desvantagem deu origem a pesquisas a respeito de sistemas e unidades de medidas inerciais que não utilizam giroscópios. A ideia de utilizar apenas acelerômetros para calcular o movimento linear e angular surgiu no início da década de 60 e vem se desenvolvendo através de modelos que variam no número de sensores, na maneira como estes são organizados e no modelo matemático que é utilizado para derivar o movimento do corpo. Esse trabalho propõe um esquema de configuração para construção de uma unidade de medida inercial que utiliza três acelerômetros triaxiais. Para identificar o deslocamento de um corpo rígido a partir deste esquema, foi utilizado um modelo matemático que utiliza apenas os nove sinais de aceleração extraídos dos três sensores. A proposta sugere que os sensores sejam montados e distribuídos em formato de L . Essa disposição permite a utilização de um único plano do sistema de coordenadas, facilitando assim a instalação e configuração destes dispositivos e possibilitando a implantação dos sensores em uma única placa de circuito integrado. Os resultados encontrados a partir das simulações iniciais demonstram a viabilidade da utilização do esquema de configuração proposto

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Nel seguente elaborato si espone l’utilizzo del sistema GPS/INS per la valutazione del moto di un ciclomotore. Tale sistema è composto da sensori GPS ( Global Navigation System ) per la misurazione della posizione, e da sensori INS ( Inertial Navigation System) per la misurazione dell’accelerazione e delle velocità angolari rispetto a tre assi coordinati. Chiaramente le misure di accelerazioni e di velocità angolari da parte dei sensori, presentano dei minimi errori, che però si ripercuotono sul posizionamento finale. Per limitare questo fenomeno e rendere la misura di velocità e posizione utilizzabile, un filtro di Kalman viene impiegato per correggere il risultato dell'integrazione usando le misurazioni del GPS. Il connubio tra il sistema INS e il sistema GPS è molto efficacie anche quando si ha una assenza di ricezione satellitare o perdita parziale dei satelliti (cycle slip). Infine è stato utilizzato uno smartphone sfruttando i sensori in esso presenti : accelerometri, giroscopi, GPS, per analizzare la dinamica di un ciclomotore, concentrandosi sull’assetto in particolar modo l’angolo di rollio. Tale prova è stata affrontata non tanto per validare il sistema GPS/INS, ma per provare una soluzione comoda e di basso costo per analizzare il moto di un ciclomotore.

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Within the context of the overall ecological working programme Dynamics of Antarctic Marine Shelf Ecosystems (DynAMo) of the PS96 (ANT-XXXI/2) cruise of RV "Polarstern" to the Weddell Sea (Dec 2015 to Feb 2016), seabed imaging surveys were carried out along drift profiles by means of the Ocean Floor Observation System (OFOS) of the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Bremerhaven. The setup and mode of deployment of the OFOS was similar to that described by Bergmann and Klages (2012, doi:10.1016/j.marpolbul.2012.09.018). OFOS is a surface-powered gear equipped with two downward-looking cameras installed side-by-side: one high-resolution, wide-angle still camera (CANON® EOS 5D Mark III; lens: Canon EF 24 f/1.4L II, f stop: 13, exposure time: 1/125 sec; in-air view angles: 74° (horizontal), 53° (vertical), 84° (diagonal); image size: 5760 x 3840 px = 21 MPix; front of pressure resistant camera housing consisting of plexiglass dome port) and one high-definition color video camera (SONY® FCB-H11). The system was vertically lowered over the stern of the ship with a broadband fibre-optic cable, until it hovers approximately 1.5 m above the seabed. It was then towed after the slowly sailing ship at a speed of approximately 0.5 kn (0.25 m/s). The ship's Global Acoustic Positioning System (GAPS), combining Ultra Short Base Line (USBL), Inertial Navigation System (INS) and satellite-based Global Positioning System (GPS) technologies, was used to gain highly precise underwater position data of the OFOS. During the profile, OFOS was kept hanging at the preferred height above the seafloor by means of the live video feed and occasional minor cable-length adjustments with the winch to compensate small-scale bathymetric variations in seabed morphology. Information on water depth and height above the seafloor were continuously recorded by means of OFOS-mounted sensors (GAPS transponder, Tritech altimeter). Three lasers, which are placed beside the still camera, emit parallel beams and project red light points, arranged as an equilateral triangle with a side length of 50 cm, in each photo, thus providing a scale that can be used to calculate the seabed area depicted in each image and/or measure the size of organisms or seabed features visible in the image. In addition, the seabed area depicted was estimated using altimeter-derived height above seafloor and optical characteristics of the OFOS still camera. In automatic mode, a seabed photo, depicting an area of approximately 3.45 m**2 (= 2.3 m x 1.5 m; with variations depending on the actual height above ground), was taken every 30 seconds to obtain series of "TIMER" stills distributed at regular distances along the profiles that vary in length depending on duration of the cast. At a ship speed of 0.5 kn, the average distance between seabed images was approximately 5 m. Additional "HOTKEY" photos were taken from interesting objects (organisms, seabed features, such as putative iceberg scours) when they appeared in the live video feed (which was also recorded, in addition to the stills, for documentation and possible later analysis). If any image from this collection is used, please cite the reference as given above.

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Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.

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An Approach with Vertical Guidance (APV) is an instrument approach procedure which provides horizontal and vertical guidance to a pilot on approach to landing in reduced visibility conditions. APV approaches can greatly reduce the safety risk to general aviation by improving the pilot’s situational awareness. In particular the incidence of Controlled Flight Into Terrain (CFIT) which has occurred in a number of fatal air crashes in general aviation over the past decade in Australia, can be reduced. APV approaches can also improve general aviation operations. If implemented at Australian airports, APV approach procedures are expected to bring a cost saving of millions of dollars to the economy due to fewer missed approaches, diversions and an increased safety benefit. The provision of accurate horizontal and vertical guidance is achievable using the Global Positioning System (GPS). Because aviation is a safety of life application, an aviation-certified GPS receiver must have integrity monitoring or augmentation to ensure that its navigation solution can be trusted. However, the difficulty with the current GPS satellite constellation alone meeting APV integrity requirements, the susceptibility of GPS to jamming or interference and the potential shortcomings of proposed augmentation solutions for Australia such as the Ground-based Regional Augmentation System (GRAS) justifies the investigation of Aircraft Based Augmentation Systems (ABAS) as an alternative integrity solution for general aviation. ABAS augments GPS with other sensors at the aircraft to help it meet the integrity requirements. Typical ABAS designs assume high quality inertial sensors to provide an accurate reference trajectory for Kalman filters. Unfortunately high-quality inertial sensors are too expensive for general aviation. In contrast to these approaches the purpose of this research is to investigate fusing GPS with lower-cost Micro-Electro-Mechanical System (MEMS) Inertial Measurement Units (IMU) and a mathematical model of aircraft dynamics, referred to as an Aircraft Dynamic Model (ADM) in this thesis. Using a model of aircraft dynamics in navigation systems has been studied before in the available literature and shown to be useful particularly for aiding inertial coasting or attitude determination. In contrast to these applications, this thesis investigates its use in ABAS. This thesis presents an ABAS architecture concept which makes use of a MEMS IMU and ADM, named the General Aviation GPS Integrity System (GAGIS) for convenience. GAGIS includes a GPS, MEMS IMU, ADM, a bank of Extended Kalman Filters (EKF) and uses the Normalized Solution Separation (NSS) method for fault detection. The GPS, IMU and ADM information is fused together in a tightly-coupled configuration, with frequent GPS updates applied to correct the IMU and ADM. The use of both IMU and ADM allows for a number of different possible configurations. Three are investigated in this thesis; a GPS-IMU EKF, a GPS-ADM EKF and a GPS-IMU-ADM EKF. The integrity monitoring performance of the GPS-IMU EKF, GPS-ADM EKF and GPS-IMU-ADM EKF architectures are compared against each other and against a stand-alone GPS architecture in a series of computer simulation tests of an APV approach. Typical GPS, IMU, ADM and environmental errors are simulated. The simulation results show the GPS integrity monitoring performance achievable by augmenting GPS with an ADM and low-cost IMU for a general aviation aircraft on an APV approach. A contribution to research is made in determining whether a low-cost IMU or ADM can provide improved integrity monitoring performance over stand-alone GPS. It is found that a reduction of approximately 50% in protection levels is possible using the GPS-IMU EKF or GPS-ADM EKF as well as faster detection of a slowly growing ramp fault on a GPS pseudorange measurement. A second contribution is made in determining how augmenting GPS with an ADM compares to using a low-cost IMU. By comparing the results for the GPS-ADM EKF against the GPS-IMU EKF it is found that protection levels for the GPS-ADM EKF were only approximately 2% higher. This indicates that the GPS-ADM EKF may potentially replace the GPS-IMU EKF for integrity monitoring should the IMU ever fail. In this way the ADM may contribute to the navigation system robustness and redundancy. To investigate this further, a third contribution is made in determining whether or not the ADM can function as an IMU replacement to improve navigation system redundancy by investigating the case of three IMU accelerometers failing. It is found that the failed IMU measurements may be supplemented by the ADM and adequate integrity monitoring performance achieved. Besides treating the IMU and ADM separately as in the GPS-IMU EKF and GPS-ADM EKF, a fourth contribution is made in investigating the possibility of fusing the IMU and ADM information together to achieve greater performance than either alone. This is investigated using the GPS-IMU-ADM EKF. It is found that the GPS-IMU-ADM EKF can achieve protection levels approximately 3% lower in the horizontal and 6% lower in the vertical than a GPS-IMU EKF. However this small improvement may not justify the complexity of fusing the IMU with an ADM in practical systems. Affordable ABAS in general aviation may enhance existing GPS-only fault detection solutions or help overcome any outages in augmentation systems such as the Ground-based Regional Augmentation System (GRAS). Countries such as Australia which currently do not have an augmentation solution for general aviation could especially benefit from the economic savings and safety benefits of satellite navigation-based APV approaches.

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Ensuring the long term viability of reef environments requires essential monitoring of many aspects of these ecosystems. However, the sheer size of these unstructured environments (for example Australia’s Great Barrier Reef pose a number of challenges for current monitoring platforms which are typically remote operated and required significant resources and infrastructure. Therefore, a primary objective of the CSIRO robotic reef monitoring project is to develop and deploy a large number of AUV teams to perform broadscale reef surveying. In order to achieve this, the platforms must be cheap, even possibly disposable. This paper presents the results of a preliminary investigation into the performance of a low-cost sensor suite and associated processing techniques for vision and inertial-based navigation within a highly unstructured reef environment.

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Современный этап развития комплексов автоматического управления и навигации малогабаритными БЛА многократного применения предъявляет высокие требования к автономности, точности и миниатюрности данных систем. Противоречивость требований диктует использование функционального и алгоритмического объединения нескольких разнотипных источников навигационной информации в едином вычислительном процессе на основе методов оптимальной фильтрации. Получили широкое развитие бесплатформенные инерциальные навигационные системы (БИНС) на основе комплексирования данных микромеханических датчиков инерциальной информации и датчиков параметров движения в воздушном потоке с данными спутниковых навигационных систем (СНС). Однако в современных условиях такой подход не в полной мере реализует требования к помехозащищённости, автономности и точности получаемой навигационной информации. Одновременно с этим достигли значительного прогресса навигационные системы, использующие принципы корреляционно экстремальной навигации по оптическим ориентирам и цифровым картам местности. Предлагается схема построения автономной автоматической навигационной системы (АНС) для БЛА многоразового применения на основе объединения алгоритмов БИНС, спутниковой навигационной системы и оптической навигационной системы. The modern stage of automatic control and guidance systems development for small unmanned aerial vehicles (UAV) is determined by advanced requirements for autonomy, accuracy and size of the systems. The contradictory of the requirements dictates novel functional and algorithmic tight coupling of several different onboard sensors into one computational process, which is based on methods of optimal filtering. Nowadays, data fusion of micro-electro mechanical sensors of inertial measurement units, barometric pressure sensors, and signals of global navigation satellite systems (GNSS) receivers is widely used in numerous strap down inertial navigation systems (INS). However, the systems do not fully comply with such requirements as jamming immunity, fault tolerance, autonomy, and accuracy of navigation. At the same time, the significant progress has been recently demonstrated by the navigation systems, which use the correlation extremal principle applied for optical data flow and digital maps. This article proposes a new architecture of automatic navigation management system (ANMS) for small UAV, which combines algorithms of strap down INS, satellite navigation and optical navigation system.

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In this paper we describe a low-cost flight control system for a small (60 class) helicopter which is part of a larger project to develop an autonomous flying vehicle. Our approach differs from that of others in not using an expensive inertial/GPS sensing system. The primary sensors for vehicle stabilization are a low-cost inertial sensor and a pair of CMOS cameras. We describe the architecture of our flight control system, the inertial and visual sensing subsystems and present some flight control results.

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This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

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This thesis develops the hardware and software framework for an integrated navigation system. Dynamic data fusion algorithms are used to develop a system with a high level of resistance to the typical problems that affect standard navigation systems.

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This thesis describes the investigation of an Aircraft Dynamic Navigation (ADN) approach, which incorporates an Aircraft Dynamic Model (ADM) directly into the navigation filter of a fixed-wing aircraft or UAV. The result is a novel approach that offers both performance improvements and increased reliability during short-term GPS outages. This is important in allowing future UAVs to achieve routine, unconstrained, and safe operations in commercial environments. The primary contribution of this research is the formulation Unscented Kalman Filter (UKF) which incorporates a complex, non-linear, laterally and longitudinally coupled, ADM, and sensor suite consisting of a Global Positioning System (GPS) receiver, Inertial Measurement Unit (IMU), Electronic Compass (EC), and Air Data (AD) Pitot Static System.

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In this paper we present an approach to build a prototype. model of a first-responder localization system intended for disaster relief operations. This system is useful to monitor and track the positions of the first-responders in an indoor environment, where GPS is not available. Each member of the first responder team is equipped with two zero-velocity-update-aided inertial navigation systems, one on each foot, a camera mounted on a helmet, and a processing platform strapped around the waist of the first responder, which fuses the data from the different sensors. The fusion algorithm runs real-time on the processing platform. The video is also processed using the DSP core of the computing machine. The processed data consisting of position, velocity, heading information along with video streams is transmitted to the command and control system via a local infrastructure WiFi network. A centralized cooperative localization algorithm, utilizing the information from Ultra Wideband based inter-agent ranging devices combined with the position estimates and uncertainties of each first responder, has also been implemented.

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In this thesis, extensive experiments are firstly conducted to characterize the performance of using the emerging IEEE 802.15.4-2011 ultra wideband (UWB) for indoor localization, and the results demonstrate the accuracy and precision of using time of arrival measurements for ranging applications. A multipath propagation controlling technique is synthesized which considers the relationship between transmit power, transmission range and signal-to-noise ratio. The methodology includes a novel bilateral transmitter output power control algorithm which is demonstrated to be able to stabilize the multipath channel, and enable sub 5cm instant ranging accuracy in line of sight conditions. A fully-coupled architecture is proposed for the localization system using a combination of IEEE 802.15.4-2011 UWB and inertial sensors. This architecture not only implements the position estimation of the object by fusing the UWB and inertial measurements, but enables the nodes in the localization network to mutually share positional and other useful information via the UWB channel. The hybrid system has been demonstrated to be capable of simultaneous local-positioning and remote-tracking of the mobile object. Three fusion algorithms for relative position estimation are proposed, including internal navigation system (INS), INS with UWB ranging correction, and orientation plus ranging. Experimental results show that the INS with UWB correction algorithm achieves an average position accuracy of 0.1883m, and gets 83% and 62% improvements on the accuracy of the INS (1.0994m) and the existing extended Kalman filter tracking algorithm (0.5m), respectively.

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Gemstone Team Vision