Multiple UAVs cooperative path planning based on dynamic bayesian network

Wenqiang Guo, Xiaoguang Gao, Qinkun Xiao

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

8 Scopus citations

Abstract

For the sake of higher level of autonomy, based on Dynamic Bayesian networks (DBNs), a novel awareness frame is proposed for achieving cooperative control of multiple unmanned aerial vehicles (UAVs) in dynamic environment. With learning and inference algorithms for DBNs, the awareness in dynamic environment could be accomplished using parameters' change in relative DBN's transition networks based on derived fusion signal sequences. A cooperative path optimization algorithm against pop-up threats is provided for multiple UAVs under this awareness frame, which exploits knowledge about the given problem, together with a simple but efficient form of coordination variable among independent UAVs. Learning and inference for this awareness DBN are also discussed. Simulation results demonstrating the feasibility of this approach are presented.

Original languageEnglish
Title of host publicationChinese Control and Decision Conference, 2008, CCDC 2008
Pages2401-2405
Number of pages5
DOIs
StatePublished - 2008
EventChinese Control and Decision Conference 2008, CCDC 2008 - Yantai, Shandong, China
Duration: 2 Jul 20084 Jul 2008

Publication series

NameChinese Control and Decision Conference, 2008, CCDC 2008

Conference

ConferenceChinese Control and Decision Conference 2008, CCDC 2008
Country/TerritoryChina
CityYantai, Shandong
Period2/07/084/07/08

Keywords

  • Cooperative path planning
  • Dynamic bayesian networks
  • Dynamic environment
  • Unmanned aerial vehicles (UAVs)

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