[RsR] A question about robust estimation of a mean from multiple instruments

I have a question about a robust location estimator when faced with the
following situation:

There are n instruments, and each instrument has a different measurement
standard error.

I can just treat the data x as i.i.d and our standard concepts of lmRob()
would do a lot.

But in truth, in this problem, we know more. We have a standard error
estimate of each instrument. We should be able to utilise this, e.g. when
we see a weird value from an untrusted instrument we should be more willing
to disregard it.

How would one go about this? I would greatly appreciate pointers. I am
happy to place sample 25-observation datasets here if it's fun.