I am not sure about other SLAM packages that would support multi-robot mapping, but i can confirm, that GMapping is not capable of doing this.
In fact i would guess that none of the particle filter based SLAM variations (like GMapping) is suitable for this use case. Since the map you actually see is only the estimate produced by the currently highest rated particle there would be some kind of combinatory explosion of the needed particle count if odometry-noise from two or more robots has to be estimated. And since the initial offset of the starting points of the robots is not known, even more particles with guesses of this offset would be needed for a global map to align properly if one robot visits an area the other robot has already mapped.
You may have a look at graph-based approaches that maybe incorporate visual features that are globally unique (e.g. SIFT, SURF). But i really have no idea if there is a algorithm like this implemented in ros already. I would really appreciate if you could keep us posted about your findings later on.