Routing Unmanned Vehicles in GPS-Denied Environments

TL;DR

This paper introduces a new method combining cooperative localization and routing to enable unmanned vehicle navigation in GPS-denied environments, addressing a critical challenge in data gathering and monitoring tasks.

Contribution

It formulates a novel combinatorial optimization problem and develops algorithms for optimal routing and localization without GPS signals.

Findings

Algorithms effectively compute optimal paths in GPS-restricted environments.

Simulation results demonstrate the approach's effectiveness and performance.

The method enhances unmanned vehicle autonomy in GPS-denied scenarios.

Abstract

Most of the routing algorithms for unmanned vehicles, that arise in data gathering and monitoring applications in the literature, rely on the Global Positioning System (GPS) information for localization. However, disruption of GPS signals either intentionally or unintentionally could potentially render these algorithms not applicable. In this article, we present a novel method to address this difficulty by combining methods from cooperative localization and routing. In particular, the article formulates a fundamental combinatorial optimization problem to plan routes for an unmanned vehicle in a GPS-restricted environment while enabling localization for the vehicle. We also develop algorithms to compute optimal paths for the vehicle using the proposed formulation. Extensive simulation results are also presented to corroborate the effectiveness and performance of the proposed formulation and algorithms.