[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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228 K. Daniec et al. 7.1 Control Algorithm First test is the stabilization of the aircraft azimuth and it is shown in the fig. 8. Plot in the part A shows the aileron control, while the plot in part B represents the setpoint values of the angles: setpoint yaw ( ), setpoint roll ( ) and current values of angles: yaw () and roll (). Setpoint yaw variable was changed four times by the operator, while the other variables including ailerons control on the plot in part A were calculated by the PI controllers formula (1). The value of the current roll angle () is keeping up with its setpoint value ( ) in less than one second. The value of the airplane azimuth is changed at a constant speed, so the settling time depends on the error value. With an yaw error ( ) equal to 15° settling time is about 5 seconds and the control is without overregulation. It is worth noting that the maximum aileron control in this case does not exceed 20% of the control range. A B Fig. 8. Azimuth and roll stabilization plots
Prototyping the Autonomous Flight Algorithms Using the Prepar3D® Simulator 229 The next test is similar to previous, but it describes the stabilization of the air- plot B shows the setpointt value of the altitude (h ) and current value of altitude (h). In this case value of the setpoint height variable h was changed two times by steps by the operator. The settling time and the magnitude of the overregulation depends on the height error value. Overregulation reaches a higher value when the airplane is reducing altitude. Overregulation is much lower when airplane has to craft altitude above sea level (fig. 9). Plot A shows the elevator control and the increase its altitude. Reduction of the altitude of the aircraft with a value of 100 m takes about 20 seconds. A B Fig. 9. Height stabilization charts Waypoints flight, which is one of the commands described in section 6.2, was presented in the fig. 10. It shows an example of a flight along the sequence of two geographic coordinates. Presented figure has two elements, a visualization from the Prepar3D® simulation environment (fig. 10a), and the control application (fig. 10b). Map [14], that is included in the control application is a real representation of the object's position in the simulator. The buildings, which are located behind
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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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8 A. Babiarz et al. a) b) Fig. 5. T
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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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18 A. Babiarz et al. a) b) Fig. 11.
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Recognition and Location of Objects
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96 G. Bieszczad et al. effectivenes
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100 G. Bieszczad et al. Table 1. No
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114 G. Bieszczad et al. [11] Krupi
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116 D. Bereska et al. Presented in
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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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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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