Questions

1. Regarding SLAM, what sensor is most commonly used to create the data that SLAM needs to make a map?
2. Why does SLAM work better with wheel odometer data available?
3. In the Floor Finder algorithm, what does the Gaussian blur function do to improve the results?
4. The final step in the Floor Finder is to trace upward from the robot position to the first red pixel. In what other way can this step be accomplished (referring to Figure 7.3)?
5. Why did we cut the image in half horizontally before doing our neural network processing?
6. What advantages does using the neural network approach provide that a technique such as SLAM does not?
7. If we used just a random driving function instead of the neural network, what new program or function would we have to add to the robot to achieve the same results?
8. How did we end up avoiding the stairs in the approach presented in the chapter? Do you feel this is adequate? Would you suggest any other means for accomplishing...