Effective sensing regions and connectivity of agents undergoing periodic relative motions

Daniel T. Swain, Ming Cao, Naomi Ehrich Leonard

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

1 Scopus citations

Abstract

Time-varying graphs are widely used to model communication and sensing in multi-agent systems such as mobile sensor networks and dynamic animal groups. Connectivity is often determined by the presence of neighbors in a sensing region defined by relative position and/or bearing. We present a method for calculating the effective sensing region that defines the connectivity between agents undergoing periodic relative motions. This method replaces time-varying calculations with time-invariant calculations which greatly simplifies studies of connectivity and convergence of consensus algorithms. We apply the technique to the case of agents moving in a common fixed direction with sinusoidal speed oscillations and fixed relative phases. For agents moving in a straight line, we show analytically how to select dynamics for fast convergence of consensus. Further numerical results suggest graph-level connectivity may be achieved with a sensing radius lower than that predicted by percolation theory for agents with fixed relative positions.

Original languageEnglish (US)
Title of host publicationProceedings of the 47th IEEE Conference on Decision and Control, CDC 2008
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3089-3094
Number of pages6
ISBN (Print)9781424431243
DOIs
StatePublished - 2008
Externally publishedYes
Event47th IEEE Conference on Decision and Control, CDC 2008 - Cancun, Mexico
Duration: Dec 9 2008Dec 11 2008

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other47th IEEE Conference on Decision and Control, CDC 2008
Country/TerritoryMexico
CityCancun
Period12/9/0812/11/08

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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