[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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230 K. Daniec et al. B A Fig. 10. Control application and Prepar3D® screenshot – waypoints flight the airplane are a regular part of the simulation created by Lockheed Martin corporation, and also are in a position corresponding to reality. Presented algorithms were implemented in C# language using WPF graphics engine. The application allows to connect to a simulation environment Prepar3D® on the same computer, and via TCP/IP protocol. Control application allows to control in autonomous mode, and as well in the stabilization mode. An interesting option is to control object with a USB device in manual mode. There is an ability to create a route on the real map. Map module allows also to add take-off and landing commands. An important feature in this software is the ability to view charts and change all the parameters of the PI controllers, which is fully sufficient for testing and prototyping algorithms for autonomous flight in the simulation environment Prepar3D®. 7.2 Artificial Traffic in Prepar3D® Prepar3D® simulator includes artificial traffic on the highways. Vehicles moving along such roads may be, for example, detected by the detection algorithms implemented in the control application. To zoom in more precisely in possibilities, that Prepar3D® gives for the vision processing purpose, there was prepared a situation (fig. 11b) where the aerial object have to pass the previously prepared route. The plane have to take two waypoints at the height of 100 m above sea and with setpoint speed 50 km/h. Camera, that is configured under the flying object (fig. 11a) can be moved in three ways (yaw, pitch and roll) and it can be zoomed up to 20 times.
Prototyping the Autonomous Flight Algorithms Using the Prepar3D® Simulator 231 A B Fig. 11. Airplane flight above the highway: a) Prepar3D®, b) Control application 8 Conclusions The performed tests in the SIL simulation were ended successfully. The plane can fly autonomously in a virtual reality. Therefore it can be supposed that the regula- tors cascade can be successfully used in the real world and can be implemented in a hardware of a real unmanned aerial vehicle (UAV) [16]. The quality of the presented solution is promising and will be verified during test flights. It was proved that it is possible to prototype control algorithms in a virtual reality simulation software. Having a working flight algorithm the next step could be to an imple- mentation of vision based algorithms in virtual reality, that could analyze artificial traffic and could affect aircraft control algorithm in order to follow the selected object on the ground. Furthermore, it is also possible to begin work on algorithms responsible for avoiding obstacles such as tall buildings or other aircrafts. Acknowledgement. Article is co-financed by European Union within European Social Fund within SWIFT project POKL.08.02.01-24-005/10. References [1] Mueller Eric, R.: Hardware-in-the-loop Simulation Design for Evaluation of Un- Field, CA, 94035 manned Aerial Vehicle Control Systems. NASA Ames Research Center, Moffett [2] Gessing, R.: About Optimality of Discrete-Time LQ Observer Based Regulator, Si- UAV. School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, lesian University of Technical, Institute of Automation [3] Johnson, E.N., Mishra, S.: Flight simulation for the development of an experimental 30332-015
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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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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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