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author:

Fan, P. (Fan, P..) [1] | Zhai, C. (Zhai, C..) [2] | Zhang, H. (Zhang, H..) [3]

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Abstract:

The timely identification of external intruders is crucial to the protection of concerned regions or targets against malicious attacks. Multi-agent barrier coverage provides a powerful framework for the effective deployment of sensor networks to monitor baleful intruders. This paper aims to address the barrier coverage problem of robotic sensing networks by developing a multi-layer coverage formulation. Inspired by gas diffusion, a group of robotic sensors are scattered to expand the coverage territory from a gathering spot. With the assistance of a divide-and-conquer scheme, a distributed control algorithm is proposed to partition the defence barrier into multiple curve segments and integrate it with intruder monitoring. By adaptively scheduling robotic sensors among multi-layer networks, it contributes to maximizing the joint detection probability of sensing networks against external intruders. Moreover, theoretical analysis is conducted to acquire sufficient conditions for elevating the detection quality of a multi-layer sensing network. Finally, numerical simulations and robotic experiments are carried out to demonstrate the effectiveness of the proposed barrier coverage approach. © 2025 John Wiley & Sons Ltd.

Keyword:

adaptive scheduling strategy barrier coverage distributed control sensor network

Community:

  • [ 1 ] [Fan P.]School of Automation, China University of Geosciences, Wuhan, China
  • [ 2 ] [Fan P.]Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, China University of Geosciences, Wuhan, China
  • [ 3 ] [Fan P.]Engineering Research Center of Intelligent Technology for Geo-exploration, Ministry of Education, China University of Geosciences, Wuhan, China
  • [ 4 ] [Zhai C.]School of Automation, China University of Geosciences, Wuhan, China
  • [ 5 ] [Zhai C.]Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, China University of Geosciences, Wuhan, China
  • [ 6 ] [Zhai C.]Engineering Research Center of Intelligent Technology for Geo-exploration, Ministry of Education, China University of Geosciences, Wuhan, China
  • [ 7 ] [Zhang H.]College of Computer and Data Science, Fuzhou University, Fuzhou, China

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International Journal of Robust and Nonlinear Control

ISSN: 1049-8923

Year: 2025

3 . 2 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 1

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