What is the best method to bin intraday volume figures from a stock price timeseries using XTS / ZOO etc in R?

Question

For instance, let's say you have ~10 years of daily 1 min data for the volume of instrument x as follows (in xts format) from 9:30am to 4:30pm :

    Date.Time               Volume        
    2001-01-01 09:30:00     1200
    2001-01-01 09:31:00     1110
    2001-01-01 09:32:00     1303

All the way through to:

    2010-12-20 16:28:00     3200
    2010-12-20 16:29:00     4210
    2010-12-20 16:30:00     8303

I would like to:

• Get the average volume at each minute for the entire series (ie average volume over all 10 years at 9:30, 9:31, 9:32...16:28, 16:29, 16:30)

How should I best go about:

• Aggregating the data into one minute buckets
• Getting the average of those buckets
• Reconstituting those "average" buckets back to a single xts/zoo time series?

I've had a good poke around with aggregate, sapply, period.apply functions etc, but just cannot seem to "bin" the data correctly.

It's easy enough to solve this with a loop, but very slow. I'd prefer to avoid a programmatic solution and use a function that takes advantage of C++ architecture (ie xts based solution)

Can anyone offer some advice / a solution?

Thanks so much in advance.