# Cooperative UAVs Gas Monitoring using Distributed Consensus

## TL;DR

This paper presents distributed consensus-based algorithms for UAV swarms to efficiently detect and localize gas plumes in a limited area, comparing exploration strategies and ensuring quick convergence to the source.

## Contribution

It introduces three novel exploration algorithms and a distributed localization method for UAV swarms, validated through realistic simulations.

## Key findings

- Three exploration algorithms compared in simulation
- Distributed consensus enables quick source convergence
- Algorithms effectively localize gas plumes in dynamic environments

## Abstract

This paper addresses the problem of target detection and localisation in a limited area using multiple coordinated agents. The swarm of Unmanned Aerial Vehicles (UAVs) determines the position of the dispersion of stack effluents to a gas plume in a certain production area as fast as possible, that makes the problem challenging to model and solve, because of the time variability of the target. Three different exploration algorithms are designed and compared. Besides the exploration strategies, the paper reports a solution for quick convergence towards the actual stack position once detected by one member of the team. Both the navigation and localisation algorithms are fully distributed and based on the consensus theory. Simulations on realistic case studies are reported.