I am starting in robotics, and reading about Markov Localization, I have one doubt, probably very stupid, but, well, I want to solve it.
Let's take the CMU Website example: https://www.cs.cmu.edu/afs/cs/project/jair/pub/volume11/fox99a-html/node3.html
Basically and very summarized:
- The robot does not know its location (uniform probability of being at any point), but knows there are 3 doors.
- It senses a door, and since that door could be any one out of the 3, the belief distribution spikes at those 3 doors.
- It moves to the right, and the belief distribution shifts to the right also, let's say "following the robot movement", and then the convolution is done when finding the 2nd door... This gets described in the next graphic, from the CMU:
But why does the belief distribution get shifted to the right, and not to the left, as the door is left behind?
Shouldn't the robot sense that there's no door between door 1 and 2 (starting from the left)?
Is there something about probability theory I've forgotten (I studied it like 14 years ago)?