Innovative Simulation Systems (eBook)

Preface 7
Acknowledgment 9
Contents 10
Part I Vision-Based Information for InnovativeSimulation Systems 13
1 Minimizing the Image Resolution in Order to Increase the Computing Speed Without Losing the Separation of the Recognised Patterns 15
Abstract 15
1 Introduction 16
2 Formulating the Problem of the Resolution Change for Grey Scale Images 16
3 Examining the Influence of the Image Resolution on the Moment Invariants Values for Grey Scale Images 20
4 Example 25
5 Conclusions 28
References 29
2 The Method of Guaranteeing the Separation Between the Recognised Object and Background 31
Abstract 31
1 Introduction 32
2 Formulating the Problem of Distinguishing an Object and Background 32
3 Invariant Functions Used for a Description of an Object and Background Features 35
4 The Method of Creating Features Vector Which Guarantees the Separation of an Object and Background 36
5 Examples 37
6 Conclusions 41
References 42
3 The Method of Developing the Invariant Functions Vector for Objects Recognition from a Given Objects Set 44
Abstract 44
1 Introduction 44
2 Formulating the Problem of the Recognition for Grey Scale Images 45
3 Creating Model Vectors of the Features and Assessing the Distance Between a Current Vector and Model Vector of the Features 50
4 Examples 54
5 Conclusions 56
References 56
4 Adjusting the Thresholds to the Recognised Pattern in Order to Improve the Separation Between the Recognised Patterns 58
Abstract 58
1 Introduction 59
2 Formulating the Problem of Thresholding for Grey Scale Images 60
3 Examining the Influence of the Thresholding Method on the Usefulness of the Moment Invariants for Pattern Recognition 61
4 Example 63
5 Conclusions 75
References 76
5 The Concept of an Active Thermal Camouflage for Friend-Foe Identification System 78
Abstract 78
1 Introduction 78
2 Existing Solutions 79
3 System Architecture 81
4 Experimental Verification of Concept of Friend or Foe Recognition System 82
5 Tests 84
6 Conclusions 85
References 86
6 Augmented Reality in UAVs Applications 88
Abstract 88
1 Introduction 88
2 Literature Review 89
3 Perspective Controls Implementation 90
4 Project Results 93
5 Conclusions 95
Acknowledgment 95
References 96
7 Real Time Dense Motion Estimation Using FPGA Based Omnidirectional Video Acquisition Device 98
Abstract 98
1 Introduction 98
2 Field Programmable Gate Array (FPGA) 100
3 Dense Optical Flow 102
3.1 Selection of Hardware Implemented Methods 103
3.2 Lucas-Kanade Method 104
4 Implementation 107
4.1 Computer Program---Method Comparison 107
4.2 Configuration of FPGA 107
5 Test Results---Predefined Sequences 108
5.1 Test Sequences 108
5.2 Error Measurement 109
5.3 Test Results 110
5.4 Summary 110
6 Test Results---Generated Video Stream 112
7 Test Results---Real-Time Dense Motion Estimation in Video Stream Captured by a Camera 114
8 Summary 116
References 117
8 GPU-Based Parameters Estimation for Anisotropic Diffusion 120
Abstract 120
1 Introduction 120
2 Algorithm 121
3 Implementation 122
4 Tests 122
5 Summary 126
Acknowledgment 127
References 127
9 An Evaluation of SETh---The Method for Long-Term Feature Tracking 129
Abstract 129
1 Introduction 129
2 Literature Review 130
3 SETh 131
4 Tests 137
5 Conclusions 195
Acknowledgments 195
References 196
10 The System for Augmented Reality Motion Measurements Visualization 199
Abstract 199
1 Introduction 199
2 Review of Medical Solutions 200
3 Proposed Solution 201
4 User Interface 206
5 Summary 208
References 209
11 Real-Time Multiple Laser Points Tracking 211
Abstract 211
1 Introduction 211
2 Laser Tracking 212
3 Test-Based Parameters Selection 214
4 Empirical Results 219
Acknowledgement 222
References 222
Part II Design, Construction and Analysisfor Purpose of Innovative Systems 224
12 Numerical and Experimental Analysis of a Truck Frame 226
Abstract 226
1 Introduction 226
2 Characteristics of the Frame 227
3 Definition of Loads 231
4 Analysis of Results 232
5 Modification Suggestions 233
6 Experimental Tests 234
7 Conclusions 239
References 239
13 Designing and Implementing Elements of a Vehicle Model in the VBS2 Virtual Simulation Environment 241
Abstract 241
1 Introduction 241
2 Creating the Basic Shape of the Vehicle 242
3 Creating Active Selections 252
4 Creating Technical Layers 253
4.1 Layer 5.000 254
4.2 Shadow Volume Layer 255
4.3 Geometry Layer 255
4.4 View---Cargo Layer 255
4.5 Fire Geometry Layer 256
4.6 Land Contact Layer 256
4.7 Hit-Points Layer 258
4.8 Memory Layer 258
5 References to the Crew and Landing Sites 260
6 Animations 261
7 Config.cpp File 263
8 Conclusion 264
References 265
14 Semi-active Suspension System for 2S1 Tracked Platform in Drive Comfort Improvement Application 266
Abstract 266
1 Introduction 266
2 Passive and Semi-active Suspension in the Tracked Vehicle Model 268
2.1 Passive Suspension Models---Basic Model 268
2.2 Passive Suspension Models---Modified Model 270
2.3 Sky-Hook Strategy Adopted to the Tracked Vehicle Suspension 272
2.4 Semi-active Suspension Models 273
2.5 ADAMS-Matlab Co-simulation Conditions 275
3 Simulation in the Yuma Proving Ground Conditions 275
4 Simulation Results Analysis 276
4.1 Time Domain Analysis---Modified Model 276
4.2 Time Domain Analysis---Basic Model 278
4.3 Frequency Domain Analysis---Modified Model 279
4.4 Frequency Domain Analysis---Basic Model 280
5 Conclusions 281
References 282
15 Experimental Mobile Robot---Hardware 283
Abstract 283
1 Introduction 283
2 Electronics 284
2.1 MCU 285
2.2 Sufficiently Large Random Access Memory 285
2.3 PWM 286
2.4 Communication Channels 286
2.5 ADC Channel 287
2.5.1 Schematic 287
2.5.2 External Oscillator 287
2.6 Wireless Communication 288
2.7 Motor Driver 289
2.7.1 Encoders 291
2.8 Power Supply 291
2.9 RS232 and USB Communication 292
3 Conclusions 293
References 294
16 Conception of a Diagnostic System for Evaluating a Technique Correctness and Effectiveness of Running 296
Abstract 296
1 Introduction 296
2 Correct Running Form 297
3 System Conception 298
3.1 Stationary Part 300
3.1.1 Vision System 300
3.1.2 Inertial System 301
3.2 Mobile Part 303
4 Conclusion 303
References 304
Part III Design and Evaluation of ControlAlgorithms 305
17 Experimental Mobile Robot---Software 307
Abstract 307
1 Introduction 307
2 Software 308
2.1 MCU Tasks 308
2.2 Design Overview 309
2.3 Scheduler 310
2.3.1 The Solution 311
2.3.2 Implementation 313
2.4 Device Drivers 313
2.5 Command Processor 314
2.6 Controllers 315
3 Developer Console 316
4 Conclusions 319
References 319
18 Application of Genetic Algorithms for Identification of Simulated Systems 321
Abstract 321
1 Introduction 321
2 Genetic Algorithms for Identification 322
3 Two-Step Genetic Algorithm 323
3.1 The Population 324
3.2 System Model for Fitness Calculations 327
3.3 Introducing Genetic Operators 329
3.4 Initial Population for S2 334
4 Verification Method of TSGA Verification by Simulation 336
5 Conclusion 337
References 337
19 Quadrotor Dynamics and Control for Precise Handling 339
Abstract 339
1 Introduction 339
2 Quadrotor Simulation Model 341
3 Quadrotor Flight Control System 347
4 Conclusions 354
Acknowledgment 354
References 354
20 The Application of the Modified BLT Method for the Synthesis of UAV's Control System 356
Abstract 356
1 Introduction 356
2 The Linear Multivariable Model for the UAV 357
3 An Example of the Control System Operation 360
4 Conclusions 363
References 363
21 The Modified BLT Method for Multivariable Control Systems 366
Abstract 366
1 Introduction 366
2 The Description and Proposed Modification of the BLT Method 367
2.1 The Algorithm of the Multivariable Controller Synthesis with the Use of the BLT Method 368
2.2 The Proposed Modification of the BLT Method 369
3 The Example of the Control System Synthesis 369
4 Conclusions 373
References 374
22 Analysis of Human Arm Nonlinear and Linear Mathematical Models 375
Abstract 375
1 Introduction 375
2 The Synthesis of a Mathematical Model of the Human Arm 376
2.1 Kinematics 376
2.2 Dynamics 379
2.3 Nonlinear Model of Arm 381
2.4 Linear Model of the Arm 382
3 1link-1DoF Arm Model 384
3.1 Kinematics 384
3.2 Dynamics 386
3.3 Nonlinear Model of Arm 386
3.4 Linear Model of Arm 387
4 1link-2DoF Arm Model 387
4.1 Kinematics 387
4.2 Dynamics 389
4.3 Nonlinear Model of Arm 390
4.4 Linear Model of Arm 390
5 Results of the Simulation 391
References 399
23 Naive Kalman Filtering for 3D Object Orientation 400
Abstract 400
1 Introduction 400
2 Reference System 401
3 Naive Kalman Filtering 402
4 Exemplary Experiments 406
5 Conclusion and Future Work 410
Acknowledgements 410
References 410
24 Non-GPS Navigation System for Criminalistic Investigation on Mobile Robot 412
Abstract 412
1 Introduction 412
2 Visual Odometry 413
2.1 Related Work 414
2.2 Algorithm Outline 415
2.3 Pose Graph 416
3 Experimental Evaluation 417
3.1 KITTI Benchmark 417
3.2 WUT Indoor Test 419
4 Conclusions and Future Work 421
References 421
25 Path Planning Algorithms for Autonomous Mobile Platform 423
Abstract 423
1 Introduction 423
2 Algorithms 424
2.1 GPS-Based 425
2.2 Encoder-Based 425
2.3 Combination of GPS and Odometry 428
2.4 Magnetic Azimuth 430
2.5 Waypoint Finding Method 433
3 Tests 433
3.1 Test no. 1---The Far Point 433
3.1.1 GPS-Based 434
3.1.2 Encoder-Based 435
3.1.3 Combined 435
3.2 Test no. 2---The Circuit Test 437
3.2.1 GPS-Based 437
3.2.2 Encoder-Based 437
3.2.3 Combined 438
3.3 Test no. 3---The Slalom Test 439
3.3.1 GPS-Based 439
3.3.2 Encoder-Based 440
3.3.3 Combined 440
3.4 Comparison of the Results 441
4 Conclusions 442
References 443