Robot Cognition and Navigation. An Experiment with Mobile Robots

Preface......Page 6
Acknowledgements......Page 7
Contents......Page 9
1.1 Introduction to the Model of Cognition......Page 14
1.1.1 Various States of Cognition......Page 16
1.1.2 Cycles of Cognition......Page 18
1.2.1 Human Visual System......Page 20
1.2.2 Vision for Mobile Robots......Page 21
1.3 Visual Recognition......Page 23
1.3.2 Feature-Based Model......Page 24
1.3.4 Structural Model......Page 25
1.4.1 Properties and Issues in Machine Learning......Page 26
1.4.2 Classification of Machine Learning......Page 28
1.5.1 Modeling Cognition Using ANN......Page 30
1.5.3 Genetic Algorithms in Robot Cognition......Page 32
1.6 Summary......Page 33
2.1 Introduction......Page 34
2.2.1 Data Structure for Map Building......Page 35
2.2.2 Explanation of the Algorithm......Page 39
2.2.3 An Illustration of Procedure......Page 40
2.2.4 An Illustration of Procedure......Page 42
2.2.5 Robot Simulation......Page 44
2.3 Execution of the Map Building Program......Page 46
2.4 Summary......Page 51
3.2 Representation of the Robot’s Environment......Page 52
3.2.1 GVD Using Cellular Automata......Page 53
3.3.1 Introduction to the Quadtree......Page 54
3.3.3 Generation of the Quadtree......Page 55
3.4 Neighbor-Finding Algorithms for the Quadtree......Page 60
3.5 The A* Algorithm for Selecting the Best Neighbor......Page 65
3.6 Execution of the Quadtree-Based Path Planner Program......Page 67
3.7 Summary......Page 71
4.1 Introduction......Page 72
4.2 Genetic Algorithms......Page 73
4.2.1 Encoding of a Chromosome......Page 74
4.2.3 Mutation......Page 75
4.2.5 Selection......Page 76
4.3.1 Formulation of Navigation......Page 77
4.4 Execution of the GA-Based Navigation Program......Page 80
4.5.1 Introduction to TAM......Page 81
4.5.2 Encoding and Decoding Process in a Temporal Memory......Page 83
4.5.3 An Example in a Semi-dynamic Environment......Page 84
4.5.4 Implications of Results......Page 87
4.6 Summary......Page 88
5.1 Introduction......Page 90
5.2 Robot Hardware and Software Resources......Page 91
5.3 ARIA......Page 92
5.3.1 ARIA Client–Server......Page 93
5.3.3 Opening the Connection......Page 97
5.3.4 ArRobot......Page 98
5.3.5 Range Devices......Page 100
5.3.6 Commands and Actions......Page 101
5.4 Socket Programming......Page 108
5.4.1 Socket Programming in ARIA......Page 109
5.5.1 Functions......Page 111
5.6 Small Vision System (SVS)......Page 113
5.6.1 SVS C++ Classes......Page 114
5.6.3 Stereo Image Class......Page 115
5.6.4 Acquisition Classes......Page 119
5.7 Multithreading......Page 125
5.9 Summary......Page 126
6.2 Flow Chart and Source Code for Robot Parameter Display......Page 128
6.3 Summary......Page 138
7.2 Flow Chart and Source Code for BotSpeak Program......Page 140
7.3 Summary......Page 149
8.2 Flow Chart and Source Code for Gripper Control Program......Page 150
8.3 Summary......Page 163
9.2 Flow Chart and Source Code for Sonar Reading Display on Client......Page 164
9.3 Summary......Page 174
10.2 Algorithm and Source Code for Wandering Within the Workspace......Page 176
10.3 Summary......Page 186
11.2 Algorithm and Source Code for Tele-operation......Page 188
11.3 Summary......Page 201
12.1 Introduction......Page 202
12.2 The ImageServer Program......Page 203
12.3 The MotionServer Program......Page 205
12.4 The Navigator Client Program......Page 208
12.5 Summary......Page 212
13.2 Necessity for 3D Reconstruction......Page 214
13.3 Building Perception......Page 215
13.3.2 Process of 3D Reconstruction......Page 216
13.4.1 Image Formation......Page 218
13.4.2 Perspective Projection in One Dimension......Page 219
13.4.3 Perspective Projection in 3D......Page 220
13.5 Global Representation......Page 224
13.6 Transformation to Global Coordinate System......Page 230
Xc......Page 233
14.2 Algorithm for Image Capture......Page 234
14.3 Summary......Page 238
15.2 Minimal Representation......Page 240
15.3 Recursive Kalman Filter......Page 242
15.4 Experiments and Estimation......Page 244
15.4.1 Reconstruction of 3D Points......Page 250
15.4.2 Reconstruction of a 3D Line......Page 255
15.4.3 Reconstruction of a 3D Plane......Page 259
15.5 Correspondence Problem in 3D Recovery......Page 262
15.6 Summary......Page 263
16.2 Flow Chart and Source Code for 3D Perception......Page 264
16.3 Summary......Page 275
17.2 Methods of Edge Detection......Page 276
17.3 Curve Tracking and Curve Fitting......Page 279
17.4 Program for Curve Detector......Page 283
17.5 Summary......Page 288
18.2 Algorithms and Source Code for Garbage Collection......Page 290
18.3 Summary......Page 294
References......Page 296
Index......Page 302