未知环境中移动机器人导航控制理论与方法（英文版）

Chapter 1 Overview
1．1 Introduction
1．2 A brief survey of mobile robot navigation theories and technologies in unknown environments
1．2．1 Architecture
1．2．2 Mapping and localization
1．2．3 Path planning
1．2．4 Motion control
1．2．5 Fault diagnosis and fault tolerance control
1．3 Research progress of machine learning theories and approaches in mobile robot navigation
1．4 Summary
References
Chapter 2 Architecture of Mobile Robot System in Unknown Environments
2．1 Introduction
2．2 The Architecture of Mobile Robot
2．2．1 Hierarchical Architecture
2．2．2 Reactive Architecture
2．2．3 Deliberative/Reactive Architecture
2．3 Examples of Mobile Robot System Architecture
2．3．1 Moving mechanism and sensor mechanism
2．3．2 Software architecture of control system
2．3．3 Hardware of control system
References
Chapter 3 Dynamic Models and Control of Mobile Robots under Unknown Environments
3．1 Introduction
3．2 Dynamic Models of Wheeled Mobile Robots
3．2．1 Several Typical Mechanisms of Wheeled Mobile Robots
3．2．2 Dynamic Model of Wheeled Mobile Robots with Nonholonomic Constraints
3．3 Stabilization and Tracking Control for Wheeled Mobile Robots
3．3．1 Stabilization and Tracking Controller Design for Wheeled Mobile Robots
3．3．2 Research on Stabilization and Tracking Control
3．4 Robust Unified Controller Design for Wheeled Mobile Robots
3．4．1 Robust Unified Control Law Design without Satisfying Nonholonomic Constraints
3．4．2 Robust Unified Controller for Wheeled Mobile Robots Moving on Uncertain Surfaces
3．5 Examples for Stabilization and Tracking Control Design
3．5．1 Tracking Control Law Design based on Backstepping
3．5．2 Trajectory Generation Method based on Differential Flatness for a Wheeled Mobile Robot
3．5．3 WMR Trajectory-Tracking Control with Actuator Saturation and Disturbances
References
Chapter 4 Mobile Robot Localization and Mapping
4．1 Dead Reckoning Localization
4．1．1 Locomotion Architecture And Proprioceptive Sensors
4．1．2 Design Of Dead Reckoning System
4．1．3 Simulation And Experiment
4．2 Mobile Robot Map Building
4．2．1 Map Building Based on Laser Radar
4．2．2 Map Matching Based on Maximum Likelihood Estimation
4．2．3 Self-localization Based on Feature Mapping
4．2．4 Experiment
4．3 Simultaneous Localization and Mapping
4．3．1 System State
4．3．2 EKF Algorithm with Local Maps
4．3．3 Simulation
4．4 Data Association Approach for Mobile Robot SLAM
4．4．1 Data Association Problem in SLAM
4．4．2 Hybrid Data Association Approach
4．4．3 Experimental Results
4．5 Mobile Robot SLAM in Dynamic Environment
4．5．1 Real-time Detection of Dynamic Obstacle By Laser Radar
4．5．2 Uniform Target Model
4．5．3 SLAMiDE System
4．5．4 Experimental Results
References
Chapter 5 Obstacle detection of mobile robot in unknown environments
5．1 Introduction
5．2 Detection method of obstacles
5．2．1 Laser ranging radar
5．2．2 Visual Method
5．3 Obstacle detection method based on laser ranging radar
5．3．1 Filtering of ranging data
5．3．2 3D Coordinate Transformation based on ranging data of laser radar
5．3．3 Obstacle detection in unstructured environments
5．4 Rapid obstacles detection by adaptive segmentation and stereo vision
References
Chapter 6 Navigational strategy for mobile robot under the unknown environment
6．1 Introduction
6．2 Path Planning
6．2．1 Case-based learning method
6．2．2 Planning method based on the model of the environment
6．2．3 Behavior-based path planning
6．2．4 New trends
6．3 Approximate VORONOI diagram based path planning
6．3．1 Space representation of mobile robots operating environment
6．3．2 Introduction of VORONOI diagram
6．3．3 Approximate VORONOI Boundary Network （AVBN） modeling method
6．3．4 Global planning based on AVBN model and GAS
6．3．5 The simulation and experiment
6．4 Reflective Local Planning Strategy
6．4．1 7-layer reflective avoidance model
6．4．2 The motion control of trajectory
6．4．3 Disturbance strategy
6．4．4 Reactive navigation experiments
6．5 local planning strategy for mobile robot
6．5．1 The Overview of Local Planning
6．5．2 Disturbance rule based on simulated annealing design
6．5．3 Local Planning Program Design
6．5．4 Local planning simulation
6．6 Composite Navigation Strategies and Its Implements
6．6．1 Composite navigation Tactics
6．6．2 The realization of composite navigation
6．7 Intelligent methods of path planning
6．7．1 Mobile robot's emergence navigation with EC for repeated tasks in unknown environments
6．7．2 Mobile robot path planning based on ant colony algorithm
6．8 Navigation strategy based on feature points
6．8．1 Feature Extraction
6．8．2 Navigation behaviors based on feature points
6．8．3 Design and Implementation of the Navigation Strategy
References
Chapter 7 Fault Diagnosis for Wheeled Mobile Robots under Unknown Environments
7．1 Introduction
7．2 Fuzzy adaptive particle filter algorithm for mobile robot fault diagnosis
7．2．1 Particle Filter Based Fault Diagnosis
7．2．2 Kinematics Models and Fault Models
7．2．3 Domain Constraints and Representation
7．2．4 Fuzzy Adaptive Particle Filter
7．2．5 Experiment Analysis
7．3 Soft fault compensation of mobile robots
7．3．1 Models and Soft Fault Detection
7．3．2 Adaptive particle filter for fault compensation
7．3．3 Experiments and Results Analysis
7．4 Fault diagnosis for mobile robots with incomplete models
7．4．1 Unknown Fault Detection for Dynamic Systems Based on Particle Filters
7．4．2 Particle Filter for Fault Diagnosis of Incomplete Systems
7．4．3 Fault Diagnosis of Mobile Robots with Incomplete Models
7．5 Fault diagnosis for laser range finder of mobile robots
7．5．1 Fault diagnosis for laser range find
7．5．2 Robust Perception Model for Laser Range Finder
7．5．3 Experiments and Analysis
References
Chapter 8 Prospect of mobile robot navigation control research in unknown environments
8．1 Future research areas
8．1．1 Environment perception technology
8．1．2 Multi-sensor information fusion technology
8．1．3 Research on self-learning of behavior
8．2 Final words
References
Index