  In this paper, we consider the automated planning of optimal paths for a
robotic team satisfying a high level mission specification. Each robot in the
team is modeled as a weighted transition system where the weights have
associated deviation values that capture the non-determinism in the traveling
times of the robot during its deployment. The mission is given as a Linear
Temporal Logic (LTL) formula over a set of propositions satisfied at the
regions of the environment. Additionally, we have an optimizing proposition
capturing some particular task that must be repeatedly completed by the team.
The goal is to minimize the maximum time between successive satisfying
instances of the optimizing proposition while guaranteeing that the mission is
satisfied even under non-deterministic traveling times. Our method relies on
the communication capabilities of the robots to guarantee correctness and
maintain performance during deployment. After computing a set of optimal
satisfying paths for the members of the team, we also compute a set of
synchronization sequences for each robot to ensure that the LTL formula is
never violated during deployment. We implement and experimentally evaluate our
method considering a persistent monitoring task in a road network environment.
