[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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304 T. Czapla and J. Wrona M240 machine gun, Javelin missiles, and a sensor platform (with an electro-optical/infrared sensor). Technical data of described vehicle are shown in Table 8. Fig. 10. Unmanned multi-purpose ground vehicles: a) Gladiator, b) MDARS, c) MULE (sources: Newton, 2011, Spawar Systems Center Pacific, Global Security) Fig. 11. Unmanned ground vehicles: a) GRUNT, b) Guardium (source: Frontline Robotics, G-NIUS Unmanned Ground Systems LTD) 3.9 GRUNT The GRUNT (GRoundUniTs) wheeled vehicle was developed by Frontline Robotics. The platform is based on Argo All-Terrain-Vehicle using commercial solutions of sensors and PC-104 industrial computer. The vehicle works in autonomous mode and has radio communication systems. The GRUNT is equipped with all-around imaging cameras, night-vision sensors, radar, and a continuous navigation system. Technical data are listed in Table 9.The vehicle is shown in Fig. 11a.
Technology Development of Military Applications of Unmanned Ground Vehicles 305 Table 8. Technical data of MULE vehicle Weight Length x Width x Height Engine power Max speed Endurance Gradient/side slope 40%/- Vertical step Trench Fording Mode of operation 3.10 Black Knight 2500 kg 4.34 x 2.24 x 2.56 m 32.1 km/h 16 h Tele-operated, autonomous Fig. 12. Black Knight and its sensors Table 9. Technical data of GRUNT vehicle Weight Length x Width x Height Engine power Max speed Endurance - Gradient/side slope 15°/- Vertical step Trench Fording Mode of operation 450 kg 2.79 x 1.52 x 1.91 m 30 km/h Tele-operated, autonomous
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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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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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20 A. Babiarz et al. patrol point i
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22 A. Babiarz et al. particular ang
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24 A. Babiarz et al. The sample cod
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Recognition and Location of Objects
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48 P. Demski et al. Fig. 1. Automat
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50 P. Demski et al. E-Grip firing m
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52 P. Demski et al. 4 Automatic Tar
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54 P. Demski et al. implementing su
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Object Tracking for Rapid Camera Mo
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Object Tracking in a Picture during
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94 Construction of Image Acquisitio
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96 G. Bieszczad et al. effectivenes
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98 G. Bieszczad et al. such a way t
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100 G. Bieszczad et al. Table 1. No
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102 G. Bieszczad et al. Fig. 7. Pri
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110 G. Bieszczad et al. has to make
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112 G. Bieszczad et al. MTF functio
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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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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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178 D. Bereska et al. The aim of th
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182 D. Bereska et al. Fig. 5. Schem
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184 D. Bereska et al. 4.1 Mechanica
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186 D. Bereska et al. 4.1.3 Open-Lo
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188 D. Bereska et al. Fig. 16. Comp
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Probabilistic Approach to Planning
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206 Practical Applications of Class
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Prototyping the Autonomous Flight A
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Feature Extraction and HMM-Based Cl
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248 K. Daniec et al. In this articl
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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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