Scheduling of Emergency Tasks for Multiservice UAVs in Post-Disaster Scenarios

TL;DR

This paper presents an optimization framework for joint planning of multi-task UAV missions in post-disaster scenarios, demonstrating effective heuristics that enable rapid, resource-efficient responses in emergency situations.

Contribution

It introduces a novel optimization model for multi-task UAV mission planning and develops heuristics for large-scale, time-sensitive emergency applications.

Findings

Heuristic solutions achieve near-optimal performance.

Significant reduction in planning computational time.

Effective application to flood recovery scenario.

Abstract

Single-task UAVs are increasingly being employed to carry out surveillance, parcel delivery, communication support, and other specific tasks. When the geographical area of operation of single-task missions is common, e.g., in post-disaster recovery scenarios, it is more efficient to have multiple tasks carried out as part of a single UAV mission. In these scenarios, the UAVs' equipment and mission plan must be carefully selected to minimize the carried load and overall resource consumption. In this paper, we investigate the 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, two heuristic solutions are developed for large-scale environments to cope with the increased complexity of the optimization framework. The joint planning is applied to a specific scenario of a flood in the San Francisco area. Results show the effectiveness of the proposed heuristic solutions, which provide good performance and allow for drastic savings in the computational time required to plan the UAVs' trajectories with respect to the optimal approach, thus enabling prompt reaction to the emergency events.