A caterpillar plot is in essence nothing different than what is often called a forest plot in the meta-analytic literature, except that the estimates are ordered by their magnitude. You can find an example of how to draw such a plot with the metafor package here.
I am slowly chipping away at what will become version 2.0-0 at some point in the (near?) future. Things I've already added include
ranef.rma.mv() for extracting the BLUPs of the random effects for
rma.mv models (usable at this point, but still needs a bit more work; also need to add
regtest.default() so the user can now specify the outcomes and corresponding sampling variances directly to these functions,
residuals() now has a
type argument and can compute Pearson residuals, all functions that repeatedly refit models now have the option to show a progress bar, lots of smaller tweaks/improvements, some obligatory code cleanup, and minor updates in the documentation. There will also be the option to fit what are called 'location-scale models' – introducing this feature will require a bit more explanation though, so I will defer those details to a later addition to the website.
If you already want to check out some of these features, you can always install the development version of metafor directly from GitHub (see here for instructions).