Mobile Robotics, 2nd Edition

Table of contents

1. Cover
2. Introduction
3. 1 Three-dimensional Modeling
   1. 1.1. Rotation matrices
   2. 1.2. Euler angles
   3. 1.3. Inertial unit
   4. 1.4. Dynamic modeling
   5. 1.5. Exercises
   6. 1.6. Corrections
4. 2 Feedback Linearization
   1. 2.1. Controlling an integrator chain
   2. 2.2. Introductory example
   3. 2.3. Principle of the method
   4. 2.4. Cart
   5. 2.5. Controlling a tricycle
   6. 2.6. Sailboat
   7. 2.7. Sliding mode
   8. 2.8. Kinematic model and dynamic model
   9. 2.9. Exercises
   10. 2.10. Corrections
5. 3 Model-free Control
   1. 3.1. Model-free control of a robot cart
   2. 3.2. Skate car
   3. 3.3. Sailboat
   4. 3.4. Exercises
   5. 3.5. Corrections
6. 4 Guidance
   1. 4.1. Guidance on a sphere
   2. 4.2. Path planning
   3. 4.3. Voronoi diagram
   4. 4.4. Artificial potential field method
   5. 4.5. Exercises
   6. 4.6. Corrections
7. 5 Instantaneous Localization
   1. 5.1. Sensors
   2. 5.2. Goniometric localization
   3. 5.3. Multilateration
   4. 5.4. Exercises
   5. 5.5. Corrections
8. 6 Identification
   1. 6.1. Quadratic functions
   2. 6.2. The least squares method
   3. 6.3. Exercises
   4. 6.4. Corrections
9. 7 Kalman Filter
   1. 7.1. Covariance matrices
   2. 7.2. Unbiased orthogonal estimator
   3. 7.3. Application to linear estimation
   4. 7.4. Kalman filter
   5. 7.5. Kalman–Bucy
   6. 7.6. Extended Kalman filter
   7. 7.7. Exercises
   8. 7.8. Corrections
10. 8 Bayes Filter
    1. 8.1. Introduction
    2. 8.2. Basic notions of probabilities
    3. 8.3. Bayes filter
    4. 8.4. Bayes smoother
    5. 8.5. Kalman smoother
    6. 8.6. Exercises
    7. 8.7. Corrections
11. References
12. Index
13. End User License Agreement