Randomise 380 samples by covariates across four 96-well plates in R (OSAT pkg)

I need to randomise 380 samples (by age, sex and group [grp]) across four 96 well plates, with A01 reserved in each plate for a positive control.

I tried the r-pkg (OSAT) and the recommended script is below. The only piece that does not work is excluding well A01 from each of the four plates.

library(OSAT)

samples <- read.table("~/file.csv", sep=";", header=T)

sample.list <- setup.sample(samples, optimal = c("grp", "sex", "age"))

excludedWells <- data.frame("plates"= 1:4, "rows" = "1", "columns"= "1", "wells" = "1")

container <- setup.container(IlluminaBeadChip96Plate, 4, batch = 'plates', exclude=excludedWells)

setup <- create.optimized.setup(fun ="optimal.shuffle", sample.list, container)

out <- map.to.MSA(setup, MSA4.plate)

The corresponding R help doc states:

"If for any reason we need to reserve certain wells for other usage, we can exclude them from the sample assignment process. For this one can create a data frame to mark these excluded wells. Any wells in the container can be identified by its location identified by three variable "plates", "chips", "wells". Therefore the data frame for the excluded wells should have these three columns. For example, if we will use the first well of the first chip on each plate to hold QC samples, these wells will not be available for sample placement. We have 6 plates in our example so the following will reserve the 6 wells from sample assignment:

excludedWells <- data.frame(plates=1:6, chips=rep(1,6), wells=rep(1,6))

Our program can let you exclude multiple wells at the same position of plate/chip. For example, the following data frame will exclude the first well on each chips regardless how many plates we have:

ex2 <- data.frame(wells=1)

"

I tried both of these and they do not work - as they simply specify ANY well (and not well #1-A01).