  We propose a high-level planner for a multirotor to chase a ground vehicle,
while simultaneously respecting various state and input constraints. Assuming a
minimal kinematic model for the ground vehicle, we use data collected online to
generate predictions for our planner within a model predictive control
framework. Our solution is demonstrated, both via simulations and experiments
on a stable quadcopter platform.
