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Cooperative target searching and tracking via UCT with probability distribution model

  • Ruoxi Qin
  • , Tian Wang
  • , Haotian Jiang
  • , Qianhong Yan
  • , Weikang Wang
  • , Hichem Snoussi
  • Beihang University
  • Université de technologie de Troyes

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

Abstract

As Unmanned Aerial Vehicle's (UAV) battery life and stability develop, multiple UAVs are having more and more applications in the uninterrupted patrol and security. Thus UAV's searching, tracking and trajectory planning become important issues. This paper proposes an online distributed algorithm used in UAV's tracking and searching, with the consideration of UAV's practical need to recharge under limited power. We propose a Quantum Probability Model to describe the partially observable target positions, and we use Upper Confidence Tree (UCT) algorithm to find out the best searching and tracking route based on this model. We also introduce the Teammate Learning Model to handle the nonstationary problems in distributed reinforcement learning.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Digital Signal Processing, DSP 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages560-564
Number of pages5
ISBN (Electronic)9781509041657
DOIs
StatePublished - 2 Jul 2016
Event2016 IEEE International Conference on Digital Signal Processing, DSP 2016 - Beijing, China
Duration: 16 Oct 201618 Oct 2016

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume0

Conference

Conference2016 IEEE International Conference on Digital Signal Processing, DSP 2016
Country/TerritoryChina
CityBeijing
Period16/10/1618/10/16

Keywords

  • Quantum Probability Distribution
  • UAV Tracking
  • UCT Planning

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