Sorry guys. This may be a basic question. I am doing a course on Robotics. I came across this equation for smoothing:
Here, u -> control action, delta -> pose, z -> sensor measurement, l -> landmark
My question is:
How can I interpret this probability and in general any probability written as:
P(A, B| C, D)?
Is this:
1.) P((A and B) given (C and D))
2.) P(A and (B given C) and D)
3.) P(((A and B) given C) and D)
and so on.
Are any of these representations equivalent?? Thanks in advance.
Follow up question:
According to the Bayesian Net, the sensor measurement depends on where the robot is and the map. Isn't it more intuitive the other way around? Shouldn't the sensor's measurement dictate where the robot is and how the map is?