MQTPP - Towards Multiple Q-Table based Path Planning in UAV Environments

Michael R. Jones, Soufiene Djahel, Kristopher Welsh

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

6 Citations (Scopus)

Abstract

This paper introduces an original multi destination path planning approach for Unmanned Aerial Vehicles (UAVs) named MQTPP (Multi Q-Table Path Planning). MQTPP aims to reduce the computational burden of cyclical/continuous path planning through a Q-learning planning process whilst overcoming the fixed path origin problem. The preliminary performance evaluation results indicate that MQTPP performs well for longer paths, and allows for more efficient re-planning should mission objectives or environmental topography change.

Original languageEnglish
Title of host publication2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages457-460
Number of pages4
ISBN (Electronic)9781665431613
ISBN (Print)9781665431620
DOIs
Publication statusE-pub ahead of print - 10 Feb 2022
Externally publishedYes
Event2022 IEEE 19th Annual Consumer Communications & Networking Conference - Virtual, Las Vegas, United States
Duration: 8 Jan 202211 Jan 2022

Publication series

Name
PublisherIEEE
ISSN (Electronic)2331-9860

Conference

Conference2022 IEEE 19th Annual Consumer Communications & Networking Conference
Abbreviated titleCCNC
Country/TerritoryUnited States
City Las Vegas
Period8/01/2211/01/22

Keywords

  • UAVs
  • Path planning
  • Q-learning

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