Mobile robot hardware and software is developing to the point where interesting applications for groups of such robots can be contemplated. We envision a set of mobots acting to map and perform surveillance or other task within an indoor environment (the Sense Net). A typical application of the Sense Net would be to detect survivors in buildings damaged by earthquake or other disaster, where human searchers would be put a risk. As a team, the Sense Net could reconnoiter a set of buildings faster, more reliably, and more comprehensibly than an individual mobot. The team, for example, could dynamically form subteams to perform task that cannot be done by individual robots, such as measuring the range to a distant object by forming a long baseline stereo sensor form a pari of mobots. In addition, the team could automatically reconfigure itself to handle contingencies such as disabled mobots. This paper is a report of our current progress in developing the Sense Net, after the first year of a two-year project. In our approach, each mobot has sufficient autonomy to perform several tasks, such as mapping unknown areas, navigating to specific positions, and detecting, tracking, characterizing, and classifying human and vehicular activity. We detail how some of these tasks are accomplished, and how the mobot group is tasked.