WPT-enabled Multi-UAV Path Planning for Disaster Management Deep Q-Network

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

Abstract

Unmanned aerial vehicles (UAVs) have been more prevalent over the past several years with the intent to be widely deployed in many industries, including agriculture, cinematography, healthcare, delivery, and disaster management missions due to their ability to provide real-time situational awareness. However, various limitations such as the battery capacity, the charging method, and the flying range make it difficult for most applications to carry out routine tasks in vast areas. In this paper, a deep reinforcement learning (DRL) method for multi-UAV path planning that considers a cooperative action amongst UAVs in which they share the next destination to avoid visiting the same location at the same time. The Deep Q-Network algorithm (DQN) enables UAVs to autonomously plan their fastest path and ensure the continuity of the mission by deciding when to schedule a visit to a charging station or a data collection point. An objective function with a tailored reward is designed to maintain the stability of the model and ensure the quick convergence of the model. Lastly, the proposed strategy has been demonstrated by the experiments on different scenarios and showed its effectiveness in ensuring the continuity of the mission with a fastest path possible.

Original languageEnglish
Title of host publication2023 International Wireless Communications and Mobile Computing, IWCMC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1672-1678
Number of pages7
ISBN (Electronic)9798350333398
DOIs
Publication statusPublished - 2023
Event19th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2023 - Hybrid, Marrakesh, Morocco
Duration: Jun 19 2023Jun 23 2023

Publication series

Name2023 International Wireless Communications and Mobile Computing, IWCMC 2023

Conference

Conference19th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2023
Country/TerritoryMorocco
CityHybrid, Marrakesh
Period6/19/236/23/23

Keywords

  • aerial data collection
  • deep reinforcement learning
  • smart health.
  • unmanned aerial vehicles
  • wireless power transfer
  • wireless sensor networks

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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