I think there are a few approaches. I haven't looked at them all and not sure which is the best:
But this doesn't give me the same answers I get from Stata for some reason. I've never tried to work out why, I just don't use this package.
rms package: I find this a bit of a pain to work with but usually get good answers with some effort. And it is the most useful for me.
model = ols(a~b, x=TRUE)
You can code it from scratch (see this blog post). It looks like the most painful option, but remarkably easy and this option often works the best.
A simple / quick explanation is that Huber-White or Robust SE are derived from the data rather than from the model, and thus are robust to many model assumptions. But as always, a quick Google search will lay this out in excruciating detail if you're interested.