  UAVs are increasingly being employed to carry out surveillance, parcel
delivery, communication-support and other specific tasks. Their equipment and
mission plan are carefully selected to minimize the carried load an overall
resource consumption. Typically, several single task UAVs are dispatched to
perform different missions. In certain cases, (part of) the geographical area
of operation may be common to these single task missions (such as those
supporting post-disaster recovery) and it may be more efficient to have
multiple tasks carried out as part of a single UAV mission using common or even
additional specialized equipment.
  In this paper, we propose and investigate a joint planning of multitask
missions leveraging a fleet of UAVs equipped with a standard set of accessories
enabling heterogeneous tasks. To this end, an optimization problem is
formulated yielding the optimal joint planning and deriving the resulting
quality of the delivered tasks. In addition, a heuristic solution is developed
for large-scale environments to cope with the increased complexity of the
optimization framework. The developed joint planning of multitask missions is
applied to a specific post-disaster recovery scenario of a flooding in the San
Francisco area. The results show the effectiveness of the proposed solutions
and the potential savings in the number of UAVs needed to carry out all the
tasks with the required level of quality.
