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Register a new userIntegrated Navigation Using IMU/GPS/Vision
الملاحة التكاملیة باستخدام منصّة قیاس عطالیة ونظام ال GPS و الرؤية باستخدام الحاسب
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یهدف هذا البحث إلى دراسة و تصمیم نظام ملاحة تكاملي. یعتمد النظام الذي تم تصمیمه على دمج القیاسات من وحدة قیاسات عطالیة IMU ، و نظام تحدید الموقع العالمي ال GPS و نظام ملاحة باستخدام الرؤیة الحاسوبیةVisual Navigation اعتمدت إجرائیة التصمیم على حساب الحل الملاحي من كل نظام على حده، أي من الحساسات العطالیة و من كامیرات، ثم إجراء تكامل IMU/GPS/Visionلتحقیق استمراریة في تصحیح الحل الملاحي و أخطاء الحساسات العطالیة.
This research aims to study and design an integrated navigation system. The designed system depends on fusing data from IMU, GPS and Vision systems. The work pocedure depends on calculating the navigation solution from each system alone; i.e from the inertial sensors and from the cameras, then integrate them to maintain continuity in correcting the navigation solution and the inertial sensors errors.
References used
Paul D Groves. Principles of GNSS, inertial, and multisensor integrated navigation systems. Artech house, 2013
Priyanka Aggarwal, Zainab Syed, and Naser El-Sheimy. MEMSbased integrated navigation. Artech House, 2014
Esmat Bekir. Introduction to modern navigation systems. World Scientific, 2007
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This article reviews the structure of an integrated navigation system made up of unit inertial sensors manufactured by MEMS technology, a GPS Receiver unit, magnetic compasses manufactured by MEMS technology, and a high barometric sensor. The integra
ted system is built using an Extended Kalman Filter (EKF). This reviewing is performed with the use of a closed-loop system that has simple integration namely the Loosely Coupling Integration.
After conducting several air tests to collect real navigational data, antipersonnel navigational data has been used to do the integrated navigation system analysis with EKF environment in the software Matlab.
It has been noticed after the analysis that the complementary horizontal navigation system error does not exceed 50 m. With deliberate withholding of GPS data for different periods in order to test the performance of the integrated navigation system in case of withholding the GPS signal, we have found that the integrated navigation system achieves good accuracy, where the horizontal error does not exceed 200 m value when the withholding GPS data for 120 seconds. This can be considered as small and acceptable values compared with the horizontal error value for inertial navigation unit stim300 when operating independently of up to 8200 m.
Vision language navigation is the task that requires an agent to navigate through a 3D environment based on natural language instructions. One key challenge in this task is to ground instructions with the current visual information that the agent per
ceives. Most of the existing work employs soft attention over individual words to locate the instruction required for the next action. However, different words have different functions in a sentence (e.g., modifiers convey attributes, verbs convey actions). Syntax information like dependencies and phrase structures can aid the agent to locate important parts of the instruction. Hence, in this paper, we propose a navigation agent that utilizes syntax information derived from a dependency tree to enhance alignment between the instruction and the current visual scenes. Empirically, our agent outperforms the baseline model that does not use syntax information on the Room-to-Room dataset, especially in the unseen environment. Besides, our agent achieves the new state-of-the-art on Room-Across-Room dataset, which contains instructions in 3 languages (English, Hindi, and Telugu). We also show that our agent is better at aligning instructions with the current visual information via qualitative visualizations.
Camera calibration has always been an essential component of photogrammetric
measurement, especially in high-accuracy close-range applications. Although the rapid
growth in adoption of digital cameras in 3D measurement applications, there are many
situations where the geometry of the image network will not support robust recovery of
camera parameters via on-the-job calibration. For this reason, stand-alone camera
calibration has again emerged as an important issue in photogrammetry and computer
vision.
In this paper, we give a rapid overview of the approaches adopted for camera
calibration in photogrammetry and computer vision. Also, we compare the method of selfcalibration,
largely used in photogrammetry, with the tow-steps method applied in
computer vision for digital camera calibration.
The use of GPS readings has led to a real revolution in Geodesic sciences and their applications. Now, the possibility of replacing the conventional methods used in measuring elevations by using GPS technology which is a good method to get the 3D poi
nts providing that the GPS measures the helical elevations. In order to measure the Physically important elevations such as the ortho-metric elevation, there must be an accurate specimen that gives the Geoids of the helix ( Geoids separation ) .In some parts of the world ( as in the case of our study ), there are only universal Ganoids .Those ganoids are calculated as series to reach a certain defined degree.
The difference in the elevation ref. surfaces and the surface of the global geoids affects the optimized elevation of the GPS, but if we deal in this paper with the deviations in elevations, there will be no problem . The importance of this paper starts here , as we can get the possibility of taking the deviations in elevations by using The GPS tech that does not exceed /500m/ distance along with improving the results by using EGM2008 model. The results of the deviations in elevation taken by GPS, the Universal Geoids specimen /EGM 2008 / the direct engineering and triangular settlements, will be compared so that we reach some recommendations that increase accuracy in work and save time and efforts.
We deal with the navigation problem where the agent follows natural language instructions while observing the environment. Focusing on language understanding, we show the importance of spatial semantics in grounding navigation instructions into visua
l perceptions. We propose a neural agent that uses the elements of spatial configurations and investigate their influence on the navigation agent's reasoning ability. Moreover, we model the sequential execution order and align visual objects with spatial configurations in the instruction. Our neural agent improves strong baselines on the seen environments and shows competitive performance on the unseen environments. Additionally, the experimental results demonstrate that explicit modeling of spatial semantic elements in the instructions can improve the grounding and spatial reasoning of the model.
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