  We consider the problem of using an autonomous agent to persistently monitor
a collection of dynamic targets distributed in an environment. We generalize
existing work by allowing the agent's dynamics to vary throughout the
environment, leading to a hybrid dynamical system. This introduces an
additional layer of complexity towards the planning portion of the problem: we
must not only identify in which order to visit the points of interest, but also
in which order to traverse the regions. We design an offline high-level
sequence planner together with an online trajectory optimizer realizing the
computed visiting sequence. We provide numerical experiments to illustrate the
performance of our approach.
