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