An Adaptive Informative Path Planning Algorithm for Real-time Air Quality Monitoring Using UAVs

Omar Velasco, Joao Valente, Abeje Y. Mersha

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

Abstract

Environmental monitoring is a heavily data driven task where data sample efficiency is paramount due to the shear volumes of gathered data. In particular, air monitoring strongly depends on sensor location. Since the recent past, Unmanned Aerial Vehicles (UAVs) present themselves as a prospective solution for flexible and better air quality data gathering. In this paper, we present a novel adaptive Informative Path Planning (IPP) approach that enables UAVs navigate through a sample utility map based on adaptive Statistical Gas Distribution Models (GDM) for efficient surveying. The presented adaptive IPP approach maximises the amount of gathered information per mission within the system constraints in known and unknown environments with near optimal performance. The effectiveness of the algorithm is tested through extensive simulation. The results showed high quality sample collection, low computational costs and better model prediction metrics against other surveying strategies. Although framed in an air environmental monitoring context, the developed solution can be used for any generic IPP problem by adapting the sample utility map to the particular application.
Original languageEnglish
Title of host publication2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1121-1130
Number of pages10
ISBN (Electronic)9781728142777
DOIs
Publication statusPublished - Sep 2020
Event2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020 - Athens, Greece
Duration: 1 Sep 20204 Sep 2020

Publication series

Name2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020

Conference

Conference2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020
CountryGreece
CityAthens
Period1/09/204/09/20

Keywords

  • Autonomous Vehicle Navigation
  • Environmental Monitoring
  • Informative Path Planning
  • Motion and Path Planning

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