## ← 11-37 Robot_Sensing_1

• 2 Followers
• 14 Lines

11-37 Robot_Sensing_1

### Get Embed Code x Embed video Use the following code to embed this video. See our usage guide for more details on embedding. Paste this in your document somewhere (closest to the closing body tag is preferable): ```<script type="text/javascript" src='https://amara.org/embedder-iframe'></script> ``` Paste this inside your HTML body, where you want to include the widget: ```<div class="amara-embed" data-url="http://www.youtube.com/watch?v=_DjfTytro6I" data-team="udacity"></div> ``` 4 Languages

Showing Revision 2 created 11/02/2015 by Udacity Robot.

1. Now, I should say if we got this, you don't find any immediate
2. significant about statistics and probability.
3. This is totally nontrivial, but it comes in very handy.
4. So, I'm going to practice this with you using a second example. In this case, you are a robot.
5. This robot lives in a world of exactly two places. There is a red place and a green place, R and G.
6. Now, I say initially, this robot has no clue where it is,
7. so the prior probability for either place, red or green, is 0.5.
8. It also has a sensor as it can see through its eyes, but his sensor seems to be somewhat unreliable.
9. So, the probability of seeing red at the red grid cell is 0.8,
10. and the probability of seeing green at the green cell is also 0.8.
11. Now, I suppose the robot sees red.
12. What are now the posterior probabilities that the robot is at the red cell given that it just saw red
13. and conversely what's the probability that it's at the green cell even though it saw red.
14. Now, you can apply Bayes Rule and figure that out.