  We consider a team of heterogeneous robots which are deployed within a common
workspace to gather different types of data. The robots have different roles
due to different capabilities: some gather data from the workspace (source
robots) and others receive data from source robots and upload them to a data
center (relay robots). The data-gathering tasks are specified locally to each
source robot as high-level Linear Temporal Logic (LTL) formulas, that capture
the different types of data that need to be gathered at different regions of
interest. All robots have a limited buffer to store the data. Thus the data
gathered by source robots should be transferred to relay robots before their
buffers overflow, respecting at the same time limited communication range for
all robots. The main contribution of this work is a distributed motion
coordination and intermittent communication scheme that guarantees the
satisfaction of all local tasks, while obeying the above constraints. The robot
motion and inter-robot communication are closely coupled and coordinated during
run time by scheduling intermittent meeting events to facilitate the local plan
execution. We present both numerical simulations and experimental studies to
demonstrate the advantages of the proposed method over existing approaches that
predominantly require all-time network connectivity.
