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

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50 Chapter 4. Control are implemented for this case, and the PWM creation is implemented simply as follows. The PWM which controls the servo position is implemented with the first timer at with the motor. The period of PWM in first timer, to control the motor, is divided by a constant in order to achieve a smaller PWM period, which is around 2ms for the servo. The rest of the idea is the same. The PWM is generated with the help of the output compare mode. The servo position is initialized at the same time with the motors, then the position is controlled calling the Position Camera(); function that can take SERVO TOP, SERVO MID, SERVO BOTTOM as the different positions for the camera servo. Indeed this camera positions are used during the vision inspection to reach the target and calculate the motor contribution according the distance of the target object. 3 unique camera head position are implemented using the visual feedback from the ST software, to find the best configuration in terms of depth of field and field of view. If the target is more far than 750 mm the camera position is set to SERVO TOP, which can see the environment from 750 mm to robot up to 4-5 meters. If the target is closer than 750 mm to robot, the camera head position is lowered to SERVO MID, in order to provide a vision from robot boundary to 750 mm. The last position is implemented for testing reasons, and also provides a ready configuration to set the camera head in any position.
Chapter 5 Vision The vision system is focused on the implementation of the camera for object detection and calculating the position of this object according to the robot. To do so, the relation between different coordinate systems, which are image planecoordinate system, robot coordinatesystem, andreal world coordinate system, should be defined. In order to go to the target, it is necessary to know where the object is placed. Using the blob search algorithm, we acquire the position of the object in the pixel coordinates. We need a mapping between those three coordinates to command the movement. There are several approaches to determine the object position according to the robot, as mentioned in Chapter 2. Among those, we will use the one for the calibrated cameras. The rest of Chapter describes camera calibration, the script that calculates the transformation, color definition, and the script to define the color. 5.1 Camera Calibration The initial step for the algorithm is to find the camera calibration. The Camera Calibration Toolbox [2] is used to calculate the camera calibration matrix that is necessary to find the projection between the world and image points represented by homogeneous vectors. Normally, the object is placed on the real world coordinate systems, and its position can be measured from the origin. In order to find the distance of the camera plane to the object, we need a transformation that maps the 3D points (for the object that is assumed to place in ground, the point is a 2D point in world coordinates, since height is 0 all the times) of the objects in the 3D world coordinates to
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POLITECNICO DI MILANO Corso di Laur
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To my family...
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Summary Aim of this project is the
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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 and 56: Chapter 4 Control The motion mechan
Page 57 and 58: 4.1. Wheel configuration 41 Figure
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: 4.3. PWM Control 49 mentioned previ
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
Page 107 and 108: B.1. Microprocessor Code 91 Set_Spe
Page 109 and 110: B.1. Microprocessor Code 93 TIM_DeI
Page 111 and 112: B.1. Microprocessor Code 95 /* Expo
Page 113 and 114: B.1. Microprocessor Code 97 RGBCube
Page 115 and 116: 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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