An Online Learning Framework for UAV Target Search Missions in Non-Stationary Environments

Noor Khial*, Naram Mhaisen, Mohamed Mabrok, Amr Mohamed

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

The rapid evolution of Unmanned Aerial Vehicles (UAVs) has revolutionized target search operations in various fields, including military applications, search and rescue missions, and post-disaster management. In this paper, we propose the use of a multi-armed bandit algorithm for a UAV's search mission in an unknown and adversarial setting. The UAV's objective is to locate a mobile target formation, assuming that their mobility resembles an adversarial behavior. To achieve this, we formulate an optimization problem and leverage the Exp3 (exponential-weighted exploration and exploitation) algorithm to solve it. The targets are assumed to be moving under the assumption of an unknown and potentially non-stationary probability distribution. To enhance the learning process, we integrate environmental observations as contextual information, resulting in a variant called C-Exp3, which optimizes the search process. Finally, we evaluate the performance of C-Exp3 in UAV search missions, focusing on adversarial environments. The primary objective for the UAV is to converge towards an optimal policy as time t approaches the horizon T, reflecting the UAV's capacity to learn the formation's strategy.

Original languageEnglish
Title of host publicationProceedings of the 2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)
PublisherIEEE
Pages753-758
Number of pages6
ISBN (Electronic)979-8-3503-7162-8
ISBN (Print)979-8-3503-7163-5
DOIs
Publication statusPublished - 2024
Event2024 Annual IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2024 - Kingston, Canada
Duration: 6 Aug 20249 Aug 2024

Publication series

NameCanadian Conference on Electrical and Computer Engineering
ISSN (Print)0840-7789

Conference

Conference2024 Annual IEEE Canadian Conference on Electrical and Computer Engineering, CCECE 2024
Country/TerritoryCanada
CityKingston
Period6/08/249/08/24

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Multi-Armed Bandits
  • Online Learning
  • Search Mission
  • UAV

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