  In addition to conventional ground rovers, the Mars 2020 mission will send a
helicopter to Mars. The copter's high-resolution data helps the rover to
identify small hazards such as steps and pointy rocks, as well as providing
rich textual information useful to predict perception performance. In this
paper, we consider a three-agent system composed of a Mars rover, copter, and
orbiter. The objective is to provide good localization to the rover by
selecting an optimal path that minimizes the localization uncertainty
accumulation during the rover's traverse. To achieve this goal, we quantify the
localizability as a goodness measure associated with the map, and conduct a
joint-space search over rover's path and copter's perceptual actions given
prior information from the orbiter. We jointly address where to map by the
copter and where to drive by the rover using the proposed iterative
copter-rover path planner. We conducted numerical simulations using the map of
Mars 2020 landing site to demonstrate the effectiveness of the proposed
planner.
