Convolutional Neural Networks for Autonomous UAV Navigation in GPS-Denied Environments

Ricardo Serras Santos, João P. Matos-Carvalho, Slavisa Tomic, Marko Beko, Carlos T. Calafate

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work addresses the challenge of autonomous Unmanned Aerial Vehicle (UAV) navigation in Global Positioning System (GPS)-denied environments by proposing a new approach that is an amalgamation of data-driven and model-based philosophies. The proposed method exploits datasets acquired from existing frameworks like the Generalized Trust Region Sub-problem (GTRS) and the Weighted Least Squares (WLS). These datasets are then used to feed the proposed Convolutional Neural Network (CNN) specially tailored to create models for UAV navigation. Afterwards, these models are used to make predictions of an optimal trajectory. The obtained numerical results reveal that the proposed CNN reveals improvements in accuracy and robustness to noise when compared to other Machine Learning approaches, while reducing the required training time.

Original languageEnglish
Title of host publicationTechnological Innovation for Human-Centric Systems - 15th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2024, Proceedings
EditorsLuis M. Camarinha-Matos, Filipa Ferrada
PublisherSpringer Science and Business Media Deutschland GmbH
Pages111-122
Number of pages12
ISBN (Print)9783031638503
DOIs
Publication statusPublished - 1 Jan 2024
Event15th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2024 - Caparica, Portugal
Duration: 3 Jul 20245 Jul 2024

Publication series

NameIFIP Advances in Information and Communication Technology
Volume716 IFIPAICT
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference15th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2024
Country/TerritoryPortugal
CityCaparica
Period3/07/245/07/24

Keywords

  • Convolutional Neural Network (CNN)
  • Generalized Trust Region Sub-Problem (GTRS)
  • Navigation
  • Unmanned Aerial Vehicle (UAV)
  • Weighted Least Squares (WLS)

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