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Real-time learning for THZ radar mapping and UAV control

  • University of Bologna
  • National Research Council of Italy

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

9 Scopus citations

Abstract

In this paper we consider a joint detection, mapping and navigation problem by an unmanned aerial vehicle (UAV) with real-time learning capabilities. We formulate this problem as a Markov decision process (MDP), where the UAV is equipped with a THz radar capable to electronically scan the environment with high accuracy and to infer its probabilistic occupancy map. The navigation task amounts to maximizing the desired mapping accuracy and coverage and to decide whether targets (e.g., people carrying radio devices) are present or not. With the numerical results, we analyze the robustness of the considered Q-learning algorithm, and we discuss practical applications.

Original languageEnglish
Title of host publicationICAS 2021 - 2021 IEEE International Conference on Autonomous Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728172897
DOIs
StatePublished - Aug 11 2021
Event2021 IEEE International Conference on Autonomous Systems, ICAS 2021 - Virtual, Montreal, Canada
Duration: Aug 11 2021Aug 13 2021

Publication series

NameICAS 2021 - 2021 IEEE International Conference on Autonomous Systems, Proceedings

Conference

Conference2021 IEEE International Conference on Autonomous Systems, ICAS 2021
Country/TerritoryCanada
CityVirtual, Montreal
Period08/11/2108/13/21

Keywords

  • Autonomous Navigation
  • Q-learning
  • Reinforcement Learning
  • Unmanned Aerial Vehicles

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