Optimizing the flight path for a scouting Uncrewed Aerial Vehicle

TL;DR

This paper presents an optimization-based method for planning the flight path of a UAV in post-disaster environments, aiming to maximize area coverage and data quality while minimizing uncertainty.

Contribution

It introduces a novel approach to optimize UAV flight paths considering sensor coverage and environmental uncertainty in unstructured, post-disaster scenarios.

Findings

Effective path planning improves reconnaissance efficiency.

Optimized paths increase data coverage and reduce uncertainty.

Method adapts to complex, unstructured environments.

Abstract

Post-disaster situations pose unique navigation challenges. One of those challenges is the unstructured nature of the environment, which makes it hard to layout paths for rescue vehicles. We propose the use of Uncrewed Aerial Vehicle (UAV) in such scenario to perform reconnaissance across the environment. To accomplish this, we propose an optimization-based approach to plan a path for the UAV at optimal height where the sensors of the UAV can cover the most area and collect data with minimum uncertainty.