[Studies in Computational Intelligence 481] Artur Babiarz, Robert Bieda, Karol Jędrasiak, Aleksander Nawrat (auth.), Aleksander Nawrat, Zygmunt Kuś (eds.) - Vision Based Systemsfor UAV Applications (2013, Sprin

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226 K. Daniec et al. height. The next step is to achieve an initial height that is equal to 1 5 of the destination altitude. When this happens, there are activated height and heading control- and despite all the efforts, it is not perfect. The landing process is divided into two parts, the first concerns the approach to land and set the plane on of the glide path (fig. 6), while the second concerns the landing curve. To determine the coordinates of the approach for landing, important information is: where (relative to lers, which effects the stabilization of the take-off destination altitude. The autonomous landing algorithm proved to be quite difficult to implement, airport) is a plane. Fig. 6. Approach for landing Depending on the location aircraft, the algorithm determines from 6 (purple and green colors) to 9 (blue and red colors) coordinates. The first coordinate is not always at the beginning of the first arrow in the fig. 6. It can be located for exam- ple in the middle of this arrow. The method for determining whether a coordinate is reached, is to compare the absolute values of all three ENU coordinates, with predefined precision value (4). || || || , (4) where: confirm the position is reached, , , ENU coordinate components, redefined precision value in meters. When the airplane reaches the beginning of the glide path, algorithm starts to determine the landing curve. The function of the curve is described by the formula (5), but it is scaled to the left and right side of the -axis. Each part contains 10 coordinates, and the whole left side concerns only for the airport. Navigation during landing is fairly complicated, and therefore, when determining achieved position algorithm checks only the height of the airplane. Using the following ENU coordinates there is determined the pitch angle from the formula (6), and the orientation of the plane is set towards the end of the runway. When the height relative to the airport will be sufficiently low (i.e. the plane will be about 5 above the runway), the setpoint speed is reduced to the landing speed, and finally when airplane reaches this speed the engine is turned off.
Prototyping the Autonomous Flight Algorithms Using the Prepar3D® Simulator 227 1,2 (5) atan2 , (6) where: – maps the landing path in the East-North plane, – setpoint pitch angle, , , – ENU coordinates components. 6.2 Circling and Taking Waypoints Circling command is an additional option, which starts automatically, when the airplane is in the air, has already completed a flight along the waypoint path, and when the user doesn't manage to give any new commands in the specified time period. Executing this command, the algorithm is still changing the aircraft azi- air muth by some angle after passing a certain given distance . The whole movement is obviously on a preset height . Positions of the circular path are calculated from the ENU conversion and then they are converted to setpoints for the PI controllers. During the flight along the desired path, which consists of a sequence of points in LLA form algorithm uses the stabilization of the setpoint height and stabilization of the orientation, which are calculated from designated ENU coordinates. With this option ENU coordinates are calculated in real time, which is based only on current and destinationn GPS position. Arbitration method for achieve destination position is the same as for other commands formula (4). 7 Tests This paper presents four test of unmanned aircraft flights in simulation environment Prepar3D®. Thesee tests were performed on a single PC with running Microsoft Windows 7. This computer is running two applications: simulation environment Prepar3D® and control application which. These applications communicate with each other using a dedicated SimConnect library shared by Lockheed Martin (fig. 7). Fig. 7. Connection between Prepar3D® and control application The first two tests weree performed to show the results of the completed PI controllers tuning, and the UAV flight stabilization. Both the third and fourth test describes the pseudo autonomous flight which is based on a sequence of geo- graphic coordinates. The purpose of the last test is flight over the artificial traffic on the highway, which is the first step to create a tracking algorithms.
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Studies in Computational Intelligen
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Aleksander Nawrat · Zygmunt Kuś E
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“In God We Trust, All others we o
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VIII Preface valuable information i
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Contents Part I: Design of Object D
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Contents XIII Technology Developmen
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XVI List of Contributors Adam Czorn
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XVIII List of Contributors Henryk M
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XX List of Contributors Józef Wron
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2 Design of Object Detection, Recog
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4 A. Babiarz et al. 1 Introduction
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6 A. Babiarz et al. The description
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10 A. Babiarz et al. o o o “micvo
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12 A. Babiarz et al. a) b) Fig. 7.
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14 A. Babiarz et al. • The camera
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16 A. Babiarz et al. the camera ser
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18 A. Babiarz et al. a) b) Fig. 11.
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Recognition and Location of Objects
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Object Tracking for Rapid Camera Mo
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116 D. Bereska et al. Presented in
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118 D. Bereska et al. Fig. 2. Image
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120 D. Bereska et al. Fig. 4. Ortho
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Omnidirectional Video Acquisition D
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Part III Design of Vision Based Con
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Vision System for Group of Mobile R
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A Distributed Control Group of Mobi
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Technology Development of Military
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344 Conclusions Control algorithms
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[Studies in Computational Intelligence 481] Artur Babiarz, Robert Bieda, Karol Jędrasiak, Aleksander Nawrat (auth.), Aleksander Nawrat, Zygmunt Kuś (eds.) - Vision Based Systemsfor UAV Applications (2013, Sprin

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