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Lab 3

Lab 3. 2 students: missing info from submissions? (emailed) 95 +/- 13.6 Remember, -10 per day late! Overall, really good. Homework 2. No submissions from 2 students? Overall Average: 58 Stdev : 6.3 Averages on each problem: 9.7 8.3 7.6 9.8 9.1 5.8 9.6. Problem 1. Problem 2

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Lab 3

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  1. Lab 3 • 2 students: missing info from submissions? (emailed) • 95 +/- 13.6 • Remember, -10 per day late! • Overall, really good

  2. Homework 2 • No submissions from 2 students? • Overall Average: 58 • Stdev: 6.3 Averages on each problem: • 9.7 • 8.3 • 7.6 • 9.8 • 9.1 • 5.8 • 9.6

  3. Problem 1

  4. Problem 2 Sum these 4 prob. distributions to get -> answer (which we can double check to see it sums to 100%) 3*1 + 2*2 + 3*14 + 51 = 3+4+42+51 = 100

  5. P(d|2): 1 is 20%, 2 is 60%, 3 is 20% We read a distance of 2 from YB YB

  6. P(d|2): 1 is 20%, 2 is 60%, 3 is 20% We read a distance of 2 from YB YB

  7. P(d|2): 1 is 20%, 2 is 60%, 3 is 20% We read a distance of 2 from YB YB

  8. P(d|2): 1 is 20%, 2 is 60%, 3 is 20% We read a distance of 2 from YB YB

  9. P(d|2): 1 is 20%, 2 is 60%, 3 is 20% We read a distance of 2 from YB YB 10.2+8.4+.2+.4 = 19.2 -> mult by 5.208333

  10. Problem 3 P(d|2): 1 is 20%, 2 is 60%, 3 is 20% We read a distance of 2 from YB YB 10.2+8.4+.2+.4 = 19.2 -> mult by 5.208333

  11. Problem 4 • This method isn’t great. First, we’re not observing after every step. Second, info from this one beacon only covers part of the space. It’s also a little suspicious that there’s no probability for being greater than 3 squares away. • We should look for the beacon on every timestep. If we don’t see the beacon, that can also help us update our belief state. • We could also have more than one beacon. Or add an additional sensor (e.g., range finder). Or take multiple (independent?) readings from the beacon.

  12. Problem 5 • Enlarge all boundaries by the maximum size of the robot. In this case, it’s the diagonal. • Really, instead of square S and G, you should just have points (since that’s the point of using a configuration space).

  13. Problem 6 • First, start with the configuration space. • Then, draw lines between all pairs of corners/robot that are visible to each other. • Many people lost points for • Confusing a “visibility graph” with the parts of the environment the robot can see • Using the workspace, rather than the configuration space • Only drawing lines from the center of the robot start location to visible corners • Missing some of the corners in the graph

  14. 6: A, B, C, D, E, F, G 7: A, B, E, F, D, C, G Each node gets expanded once (and only once) Therefore, will only “visit” a node once, and will not get stuck in a cycle In Depth First, will visit D and F because D will be added back to the queue of nodes under consideration

  15. Test Tuesday • 75 min • 1 page of paper, 1 side • Handwritten or typed

  16. Learning to Control a Low-Cost Manipulator using Data-Efficient Reinforcement Learning. M. Deisenroth, C. Rasmussen, D. Fox • http://www.cs.washington.edu/ai/Mobile_Robotics/projects/robot-rl/ • EM/Math • Timing, losing connection • Eliminate drift (w/ wind) • What about a more uniform room? Scaling to larger maps? • Automatic scaling was cool.

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