[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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150 A. Babiarz, R. Bieda, and K. Jaskot Fig. 6. Design of robots top marker It was designed with three goals in mind: • It has to be significantly wider in one dimension, in order to improve precision of estimating the main axis of inertia • It should be more thick on one end than on the other, to make possible choosing the direction of main inertia axis, according to the algorithm described in the next section • It has to be small enough, to prevent two or more color markers coming from different robots from being recognized as one object, when being very close to each other. Estimating the angle of main axis of inertia is done in few steps. First, moments of inertia are calculated: (21) (22) (23) Then the elements of tensor of inertia are found: (24) (25) (26)
Vision System for Group of Mobile Robots 151 Finally, central moments of inertia can be calculated: 1 2 1 2 4 (27) 1 2 1 2 4 (28) Angles of both axes of inertia are calculated from the following formulas: (29) (30) To calculate the value of arc tangent it is the best to use 2 function from standard math library, as it automatically deals with finding proper sign of result depending on the quadrant of coordinate system. For objects symmetrical with respect to both axes of inertia, the one described by angle is perpendicular to the axis of longest dimension of the object while the axis described by the angle is co-linear with the axis of longest dimension, so the vision algorithm uses the second axis of inertia in further calculations. 2.9 Direction of Main Axis of Inertia The algorithm relies on special design of the shape of color marker on top of each robot described earlier in this chapter. The idea of finding the direction of main axis of inertia is explained on Figure 7 and explained below. Steps taken by the algorithm in order to decide whether the directed angle describing direction of main axis of inertia is equal to or can be described as follows: Fig. 7. Idea of finding the direction of orientation axis
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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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Probabilistic Approach to Planning
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206 Practical Applications of Class
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208 M. Mellado and K. Skrzypczyk an
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210 M. Mellado and K. Skrzypczyk a
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216 M. Mellado and K. Skrzypczyk 6
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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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250 K. Daniec et al. Fig. 2. Applic
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252 K. Daniec et al. by the ability
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254 K. Daniec et al. The idea of us
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Selection of Individual Gait Featur
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274 A. Nawrat et al. alia weather c
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276 A. Nawrat et al. have an embedd
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278 A. Nawrat et al. particular cha
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280 A. Nawrat et al. • 1-phase el
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282 A. Nawrat et al. The phase cond
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284 A. Nawrat et al. Table 1. Compa
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286 A. Nawrat et al. P3 P3 P3 71101
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288 A. Nawrat et al. S, VA 4,510 4,
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290 A. Nawrat et al. Comparison dif
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Technology Development of Military
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312 A. Czornik, A. Nawrat, and M. N
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328 M. Koźlak, A. Kurzeja, and A.
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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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