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• Contents
  Chapter 1 Overview 1
  1.1 Introduction 1
  1.2 A brief survey of mobile robot navigation theories and technologies in unknown environments 2
  1.2.1 Architecture 7
  1.2.2 Mapping and localization 3
  1.2.3 Path planning 5
  1.2.4 Motion control 5
  1.2.5 Fault diagnosis and fault tolerance control 6
  1.3 Research progress of machine learning theories and approaches in mobile robot navigation 8
  1.4 Summary 10
  References 10
  Chapter 2 Architecture of Mobile Robot System in Unknown Environments 13
  2.1 Introduction 13
  2.2 The Architecture of Mobile Robot 13
  2.2.1 Hierarchical Architecture 13
  2.2.2 Reactive Architecture 14
  2.2.3Deliberative/Reactive Architecture 16
  2.3 Examples of Mobile Robot System Architecture 17
  2.3.1 Moving mechanism and sensor mechanism 19
  2.3.2 Software architecture of control system 24
  2.3.3 Hardware of control system 36
  References 41
  Chapter 3 Dynamic Models and Control of Mobile Robots under Unknown Environments 44
  3.1 Introduction 44
  3.2 Dynamic Models of Wheeled Mobile Robots 45
  3.2.1 Several Typical Mechanisms of Wheeled Mobile Robots 45
  3.2.2 Dynamic Model of Wheeled Mohile Robots with Nonholonomic Constraints 45
  3.3 Stabilization and Tracking Control for Wheeled Mobile Robots 47
  3.3.1 Stabilization and Tracking Controller Design for Wheeled Mobile Robots 48
  3.3.2 Research on Stabilization and Tracking Control 49
  3.4 Robust Unified Controller Design for Wheeled Mobile Robots 65
  3.4.1 Robust Unified Control I_aw Design without Satisfying Nonholonomic Constraints 65
  3.4.2 Robust Unified Controller for Wheeled Mobile Robots Moving on Uncertain Surfaces 88
  3.5 Examples for Stabilization and Tracking Control Design 106
  3.5.1 Tracking Control I_aw Design based on Backstepping 106
  3.5.2 Trajectory Generation Method hased on Differential Flatness for a Wheeled Mobile Robot 110
  3.5.3 WMR TrajectoryTracking Control with Actuator Saturation and Distur bances 117
  References 146
  Chapter 4 Mobile Robot Localization and Mapping 156
  4.1 Dead Reckoning Localization 156
  4.1.1 Locomotion Architecture And Proprioceptive Sensors 157
  4.1.2 Design Of Dead Reckoning System 159
  4.1.3 Simulation And Experiment 163
  4.2 Mobile Robot Map Building 165
  4.2.1 Map Building Based on I_aser Radar 165
  4.2.2Map Matching Based on Maximum I_ikelihood Estimation 169
  4.2.3Selflocalization Based on Feature Mapping 170
  4.2.4 Experiment 172
  4.3 Simultaneous Localization and Mapping 174
  4.3.1 System State175
  4.3.2 EKF Algorithm with l_ocal Maps 175
  4.3.3 Simulation 179
  4.4 Data Association Approach for Mobile Robot SLAM 181
  4.4.1 Data Association Problem in SLAM 182
  4.4.2 Hvhrid Data Association Approach 184
  4.4.3 Experimental Results 186
  4.5 Mobile Robot SLAM in Dynamic Environment 188
  4.5.1 Realtime Detection of Dynamic ()bstacle By Laser Rada r189
  4.5.2 Uniform Target Model 195
  4.5.3 SLAMiDE System 196
  4.5.4 Experimental Results 200
  References 202
  Chapter 5 0bstacle detection of mobile robot in unknown environments 206
  5.1 Introduction 206
  5.2 Detection method of obstacles 207
  5.2.1Laser ranging radar 207
  5.2.2Visual Method 210
  5.3 0bstacle detection method based on laser ranging radar 217
  5.3.1 Filtering of ranging data 218
  5.3.2 3D Coordinate Transformation based on ranging data of laser radar 224
  5.3.3 Obstacle detection in unstructured environments 227
  5.4 Rapid obstacles detection by adaptive segmentation and stereo vision 231
  References 237
  Chapter 6 Navigational strategy for mobile robot under the unknown environ ment 239
  6.1 Introduction 239
  6.2 Path Planning 240
  6.2.1 Casebased learning method 240
  6.2.2 Planning method based on the model of the environment 241
  6.2.3 Behaviorbased path planning 243
  6.2.4 New trends 244
  6.3 Approximate V()R()NOI diagram based path planning246
  6.3.1 Space representation of mobile robots operating environment 246
  6.3.2 Introduction of VORONOI diagram 251
  6.3.3 Approximate V()RON()I Boundary Network (AVBN) modeling method 253
  6.3.4 Global planning based on AVBN model and GAS 260
  6.3.5 The simulation and experiment 270
  6.4 Reflective Local Planning Strategy 271
  6.4.1 7-layer reflective avoidance model 272
  6.4.2 The motion control of trajectory 275
  6.4.3 Disturbance strategy 276
  6.4.4 Reactive navigation experiments 278
  6.5 local planning strategy for mobile robot 280
  6.5.1 The Overview of Local Planning 280
  6.5.2 Disturbance rule based on simulated annealing design 282
  6.5.3 Local Planning Program Design 288
  6.5.4 Local planning simulation 290
  6.6 Composite Navigation Strategies and Its Implements 292
  6.6.1 Composite navigation Tactics 292
  6.6.2 The realization of composite navigation 304
  6.7 Intelligent methods of path planning 311
  6.7.1 Mobile robot's emergence navigation with EC for repeated tasks in unknown environments 311
  6.7.2 Mohile robot path planning based on ant colony algorithm 318
  6.8 Navigation strategy based on feature points 330
  6.8.1Feature Extraction 331
  6.8.2Navigation behaviors based on feature points 334
  6.8.3Design and Implementation of the Navigation Strategy 335
  References 339
  Chapter 7 Fault Diagnosis for Wheeled Mobile Robots under Unknown Environments 345
  7.1 Introduction 345
  7.2 Fuzzy adaptive particle filter algorithm for mobile robot fault diagnosis 347
  7.2.1 Particle Filter Based Fault Diagnosis 347
  7.2.2 Kinematics Models and Fault Models 349
  7.2.3 Domain Constraints and Representation 350
  7.2.4 Fuzzy Adaptive Particle Filter 351
  7.2.5 Experiment Analysis 353
  7.3 Soft fault compensation of mobile robots 355
  7.3.1 Models and Soft Fault Detection 356
  7.3.2 Adaptive particle filter for fault compensation 359
  7.3.3 Experiments and Results Analysis 364
  7.4 Fault diagnosis for mobile robots with incomplete models 370
  7.4.1 Unknown Fault Detection for Dynamic Systems Based on Particle Filters 371
  7.4.2 Particle Filter for Fault Diagnosis of Incomplete Systems 376
  7.4.3 Fault Diagnosis of Mohile Robots with Incomplete Models 377
  7.5 Fault diagnosis for laser range finder of mobile robots 378
  7.5.1 Fault diagnosis for laser range find 378
  7.5.2 Robust Perception Model for Laser Range Finder 381
  7.5.3 Experiments and Analysis 384
  References 385
  Chapter 8 Prospect of mobile robot navigation control research in unknown environments 387
  8.1 Future research areas 388
  8.1.1 Environment perception technology 388
  8.1.2 Multisensor information fusion technology 391
  8.1.3 Research on selflearning of behavior 392
  8.2 Final words 393
  References 394
  Index 396