Multi-UAV routing for persistent intelligence surveillance & reconnaissance missions

TLDR

The study addresses a Persistent Intelligence, Surveillance and Reconnaissance routing problem that requires collecting data from specified task locations and delivering it to a control station. The UAV team aims to minimize the maximum delivery time of all task data to the control station while meeting each task’s revisit period constraint. The routing is formulated as a mixed‑integer linear program solved by a branch‑and‑cut algorithm, and heuristics are proposed to obtain faster suboptimal solutions. Experiments on multiple instances show that the algorithms achieve near‑optimal costs with reduced computation times compared to the exact solution.

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 suboptimal 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.