Submitted version of the thesis - Airlab, the Artificial Intelligence ...

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40 Chapter 4. Control position both in Cartesian and polar coordinates. Normally, the position of the robot is represented by Cartesian coordinates which is a point in X-Y plane. By polar coordinates, the position is described by an angle, and a distance to the origin. Instead of representing robot position with a single coordinate, the hybrid approach is used as follows. The robot pose is defined as {XI,YI,α} where XI and YI are linear positions of the robot in the world. Let α denote the angle between the robot axis and the vector that connects the center of the robot and the target object. The transformation of the coordinates into polar coordinates with its origin at goal position: p = � ∆x 2 +∆y 2 and α = −θ+atan2(∆x,∆y) (4.1) Then the calculated angle α is passed as the parameter to the simulator in order to test the motor contributions calculated for the motion. Later, the behavior tested with simulator is implemented for microcontroller with Triskar function (in Appendix A.1), and the angle α calculated after acquiring the target, is passed to Triskar function, to calculate the motor contributions on-board, to reach the target. The inverse kinematics model is simple. It was considered that the representative coordinates of the robot were located in its center. Each wheel is placed in such orientation that its axis of rotation points towards the center of the robot and there is an angle of 120 ◦ between the wheels. The velocity vector generated by each wheel is represented on Figure 4.1 by an arrow and their direction relative to the Y coordinate (or robot front direction) are 30 ◦ , 150 ◦ and 270 ◦ respectively. Forthistypeofconfiguration, thetotal platformdisplacementisachieved by summing up all the three vectors contributions, given by: −→ FT = −→ F1 + −→ F2 + −→ F3 First of all, some definitions need to be considered. Figure 4.1 represents the diagram of the mobile robot platform with the three wheels. It was assumed that the front of the robot is in positive Y direction, and the positive side to counter clockwise. The three wheels coupled to the motors are mounted at angle position -60, +60 and +180 degrees, respectively. It is
4.1. Wheel configuration 41 Figure 4.1: The wheel position and robot orientation important to remember that the wheel driving direction is perpendicular to the motor axis (therefore 90 degrees more). The line of movement for each wheel (when driven by the motor and ignoring sliding forces) is represented in Figure 4.1 by solid, black arrows. The arrow indicates positive direction contribution. The total platform displacement is the sum of three vector components (one per motor) and is represented as a vector, applied to the platform body center. In order to find out the three independent motor contributions, the composition of the vectors represented by red arrows is projected on axes representing the line of movement of each wheel. The calculation of the independent motor contributions is made using the following formulas: ⎡ ⎤ V t1 ⎢ ⎥ ⎣V t2⎦ = MF ∗V V t3
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POLITECNICO DI MILANO Corso di Laur
Page 5: To my family...
Page 9: Summary Aim of this project is the
Page 13 and 14: Contents Sommario I Summary III Tha
Page 15 and 16: List of Figures 2.1 The standard wh
Page 17 and 18: Chapter 1 Introduction 1.1 Goals Th
Page 19 and 20: 1.4. Thesis Structure 3 tailed desc
Page 21 and 22: Chapter 2 State of the Art Advances
Page 23 and 24: 2.1. Locomotion 7 provides low resi
Page 25 and 26: 2.1. Locomotion 9 Figure 2.4: Diffe
Page 27 and 28: 2.1. Locomotion 11 Omnidirectional
Page 29 and 30: 2.2. Motion Models 13 2.2 Motion Mo
Page 31 and 32: 2.4. Games and Interaction 15 a 2.5
Page 33 and 34: 2.4. Games and Interaction 17 We in
Page 35 and 36: 2.4. Games and Interaction 19 lot o
Page 37 and 38: Chapter 3 Mechanical Construction W
Page 39 and 40: 3.2. Motors 23 The initial design o
Page 41 and 42: 3.2. Motors 25 Figure 3.3: The calc
Page 43 and 44: 3.3. Wheels 27 target surface, maxi
Page 45 and 46: 3.5. Bumpers 29 Figure 3.8: Three w
Page 47 and 48: 3.6. Batteries 31 itself also works
Page 49 and 50: 3.7. Hardware Architecture 33 In sh
Page 51 and 52: 3.7. Hardware Architecture 35 The s
Page 53 and 54: 3.7. Hardware Architecture 37 With
Page 55: Chapter 4 Control The motion mechan
Page 59 and 60: 4.2. Matlab Script 43 This is case
Page 61 and 62: 4.2. Matlab Script 45 Mixed Angular
Page 63 and 64: 4.3. PWM Control 47 acollision, suc
Page 65 and 66: 4.3. PWM Control 49 mentioned previ
Page 67 and 68: Chapter 5 Vision The vision system
Page 69 and 70: 5.1. Camera Calibration 53 the prin
Page 71 and 72: 5.1. Camera Calibration 55 Figure 5
Page 73 and 74: 5.1. Camera Calibration 57 Later, i
Page 75 and 76: 5.2. Color Definition 59 warmer (ye
Page 77 and 78: 5.2. Color Definition 61 Anotheraut
Page 79 and 80: 5.2. Color Definition 63 9000 8000
Page 81 and 82: 5.3. Tracking 65 any color values.
Page 83 and 84: Chapter 6 Game The robot will be us
Page 85 and 86: • Initialize sensors • Initiali
Page 87 and 88: If the camera is set to SERVO MID,
Page 89 and 90: Chapter 7 Conclusions and Future Wo
Page 91 and 92: ior, which will be useful in the re
Page 93 and 94: Bibliography [1] Battle bots-http:/
Page 95 and 96: BIBLIOGRAPHY 79 [25] Han et al. A n
Page 97 and 98: Appendix A Documentation of the pro
Page 99 and 100: Figure A.2: The flow diagram of the
Page 101 and 102: Appendix B Documentation of the pro
Page 103 and 104: B.1. Microprocessor Code 87 /* Conf
Page 105 and 106: B.1. Microprocessor Code 89 #ifdef
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B.1. Microprocessor Code 91 Set_Spe
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B.1. Microprocessor Code 93 TIM_DeI
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B.1. Microprocessor Code 95 /* Expo
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B.1. Microprocessor Code 97 RGBCube
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B.1. Microprocessor Code 99 /* Incl
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B.1. Microprocessor Code 101 #endif
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B.1. Microprocessor Code 103 } void
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B.1. Microprocessor Code 105 GPIO_I
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B.1. Microprocessor Code 107 /* Sta
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B.1. Microprocessor Code 109 } Inve
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B.1. Microprocessor Code 111 #inclu
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B.1. Microprocessor Code 113 /* * M
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B.1. Microprocessor Code 115 b[1] =
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B.1. Microprocessor Code 117 } * (B
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B.1. Microprocessor Code 119 #defin
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B.2. Color Histogram Calculator 121
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B.3. Object’s Position Calculator
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B.3. Object’s Position Calculator
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B.4. Motion Simulator 127 0 0 0 0 0
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B.4. Motion Simulator 129 if (plot
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B.4. Motion Simulator 131 fill (m a
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B.4. Motion Simulator 133 end text(
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Appendix C User Manual This documen
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C.1. Tool-chain Software 137 Figure
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C.2. Setting up the environment (Qt
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C.3. Main Software - Game software
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Appendix D Datasheet The pin mappin
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Figure D.2: The schematics for the
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