Sub nyquist sampling, required number of samples for time sparse grouped signals
Compressed sensing does not assume any distribution of non-zero elements in the input vector (signal), so it makes no difference if your non-zero elements are near each other or located uniformly on the sampling grid. The number of measurement, as theory states for all sparse signals, depends on how many non-zero elements you have (sparsity degree), what is your noise in input and what recovery quality your need (exact or approximation) and etc.
therefore,

Does it make sense to perform compressed sampling if the non zero samples are grouped in time?

Yes!
I suggest the following video lecture of Baranuik:
Video Lecture On CS