Errors-In-Variables in R

In reference to [1], how would you solve the following regression
problem:

Given observations (X_i,Y_i) with known respective error distributions
(e_X_i,e_Y_i) (say, 0-mean Gaussian with known STD), find the parameters
a and b which maximize the Likelihood of

Y = a*X + b

Taking the example further, how many of the very simplified assumptions
from the above example can be lifted or eased and R still has a method
for finding an errors-in-variables fit?