# Multiservice UAVs for Emergency Tasks in Post-disaster Scenarios

## TL;DR

This paper introduces a joint planning approach for multi-task UAV missions in post-disaster scenarios, optimizing resource use and reducing UAV numbers through a formulated optimization problem and heuristic solutions.

## Contribution

It proposes a novel joint planning framework for multi-task UAV missions with heterogeneous equipment, improving efficiency in disaster recovery operations.

## Key findings

- Significant reduction in UAV numbers needed for tasks
- Effective application demonstrated in San Francisco flood scenario
- Optimization framework improves resource allocation and mission quality

## Abstract

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.