# Multi-UAV Routing for Persistent Intelligence Surveillance & Reconnaissance Missions

## TL;DR

This paper addresses a complex UAV routing problem for persistent surveillance, aiming to optimize data delivery times while respecting task revisit constraints, using mixed integer programming and heuristics for efficient solutions.

## Contribution

It formulates a novel PISR routing problem with revisit constraints and develops both exact and heuristic algorithms for effective path planning.

## Key findings

- Heuristic algorithms significantly reduce computation time.
- Optimal solutions outperform heuristics in cost but take longer to compute.
- The approach effectively balances data freshness and routing efficiency.

## Abstract

We consider a Persistent Intelligence, Surveillance and Reconnaissance (PISR) routing problem, which includes collecting data from a set of specified task locations and delivering that data to a control station. Each task is assigned a refresh rate based on its priority, where higher priority tasks require higher refresh rates. The UAV team's objective is to minimize the maximum of the delivery times of all the tasks' data to the control station, while simultaneously, satisfying each task's revisit period constraint. The centralized path planning problem for this PISR routing problem is formulated using mixed integer linear programming and solved using a branch-and-cut algorithm. Heuristics are presented to find sub-optimal feasible solutions that require much less computation time. The algorithms are tested on several instances and their performance is compared with respect to the optimal cost and computation time.