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1. Toward Human-Level Intelligencein Autonomous Cars Prof. Sebastian Thrun
Director, SAIL
Stanford University
2. Progress in AI: 1956 – 2006 Human-Level Chess
Human-Level Dialogue
Human-Level Perception
3. 2004: Barstow, CA, to Primm, NV
4. 2004 Grand Challenge
5. Grand Challenge 2004: 106 Teams
6. Grand Challenge 2005: 195 Teams
7. Stanford’s Robot Stanley
8. Laser-Based Terrain Acquisition
9. Range Sensor Interpretation
10. Obstacle Detection
11. Laser Perception of the Beer Bottle Pass
12. Continual Planning and Control
13. Finding Drivable Surface in Video
14. Vision: Continual Adaptation
15. Adaptive Vision in Mojave Desert
16. 2005 Semi-Finalists: 43 Teams
17. AI Put to a Test: The “NQE”
18. National Qualification Event (Sept 05)
19. National Qualification Event
20. Adaptive Vision During “NQE”
21. 2005 Finalists: 23 Teams
22. The Grand Challenge Race
23. DARPA “Urban Challenge:” Nov 3, 2007 Carry out missions in urban environments
Obey all CA traffic laws
Accommodate road blockages etc
24. Why Hard?
25. Progress in AI: 1956 – 2006 Human-Level Chess
Human-Level Dialogue
Human-Level Perception
26. A Big Surprise? Perception ? Computation
In particular, computers won’t perceive better just because they are faster
Stanley’s software: runs on 2 laptops
Need: better computer algorithms!
27. Some Wild Technology Predictions In 20 years: I will trust my autonomous car more than I trust myself
In 50 years: Cars won’t have human controls any longer
In 50 years: Very little progress on human-level perception. Instead, we will “engineer away” most of the perception problems.
28. STAIR: Stanford AI Robot Project