1. CHAPTER 14
ROBOTICS

2. Mobile Robots

3. Manipulator Robots

4. Sensors and Effectors

5. Motion as Search

6. Decomposition Methods

7. Approximate Decomposition

8. Skeletonization Methods

9. Probabilistic Roadmaps

10. Potential Field Methods
So far: implicit preference for short paths
Rational agent should balance distance with risk!
Idea: introduce cost for being close to an obstacle
Can do this with discrete methods (how?)
Usually most natural with continuous methods

11. Probabilistic Robotics in Context

12. Robot Environment Interaction

13. Robot Environment Interaction

14. Localization

15. Monte Carlo Localization

16. SLAM Simultaneous Localization and Mapping
Estimate a map of the world, as well as your position of it, at the same time!
It’s hard:
If robot had a map, localization would be easier (still hard)
If robot knew where it was, building a map would be easier (still hard)
Issues of scale, approximations, etc.

17. Course Summary

18. Course Summary

19. Course Summary

20. Course Summary