Path Planning for Cooperative Routing of Air-Ground Vehicles

TL;DR

This paper introduces a cooperative routing framework for air-ground vehicles with communication constraints, using MILP and branch-and-cut algorithms to optimize paths for surveillance missions.

Contribution

It presents a novel MILP formulation and solution algorithm for joint path planning of air-ground teams under communication restrictions.

Findings

The approach effectively solves complex routing problems.

Computational experiments demonstrate the method's efficiency.

The framework improves mission coverage and communication reliability.

Abstract

We consider a cooperative vehicle routing problem for surveillance and reconnaissance missions with communication constraints between the vehicles. We propose a framework which involves a ground vehicle and an aerial vehicle; the vehicles travel cooperatively satisfying the communication limits, and visit a set of targets. We present a mixed integer linear programming (MILP) formulation and develop a branch-and-cut algorithm to solve the path planning problem for the ground and air vehicles. The effectiveness of the proposed approach is corroborated through extensive computational experiments on several randomly generated instances.