- chapter 2: Bug algorithims
- requiring minimal mathematical background to implement and analyze.
- 2 basic motion primitives - moving in a straight line or following a boundary.
- chapter 3: Configuration spaces
- rigid bodies / rigid arms
- visualize paths through configuration space
- chapter 4: artificial potential functions
- virtual potential field in configuration space to make obstacles repulsive and a goal configuration attractive.
- chapter 5: roadmaps
- concise representations of the robot’s free space
- chapter 6: cell decomposition
- alternative representation of free space
- chapter 7: sampling-based algorithms
- trade completeness guarantees for reduction in complexity
- chapter 8: Kalman Filtering
- chapter 9: Bayesian estimation
- chapter 10: robot dynamics
- chapter 11: trajectory planning