Collision-Aware UAV Trajectories for Data Collection via Reinforcement Learning

Xueyuan Wang, M. Cenk Gursoy, Tugba Erpek, Yalin E. Sagduyu

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

Abstract

Unmanned aerial vehicles (UAVs) are expected to be an integral part of wireless networks, and determining collision-free trajectories in multi-UAV non-cooperative scenarios is a challenging task. In this paper, we consider a path planning optimization problem to maximize the collected data from multiple Internet of Things (IoT) nodes under realistic constraints. The considered multi-UAV non-cooperative scenarios involve random number of other UAVs in addition to the typical UAV, and UAVs do not communicate with each other. We translate the problem into an Markov decision process (MDP). Dueling double deep Q-network (D3QN) is proposed to learn the decision making policy for the typical UAV, without any prior knowledge of the environment (e.g., channel propagation model and locations of the obstacles) and other UAVs (e.g., their missions, movements, and policies). Numerical results demonstrate that real-time navigation can be efficiently performed with high success rate, high data collection rate, and low collision rate.

Original languageEnglish (US)
Title of host publication2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728181042
DOIs
StatePublished - 2021
Event2021 IEEE Global Communications Conference, GLOBECOM 2021 - Madrid, Spain
Duration: Dec 7 2021Dec 11 2021

Publication series

Name2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings

Conference

Conference2021 IEEE Global Communications Conference, GLOBECOM 2021
Country/TerritorySpain
CityMadrid
Period12/7/2112/11/21

Keywords

  • collision avoidance
  • Data collection
  • deep reinforcement learning
  • multi-UAV scenarios
  • path planning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Health Informatics

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