Decentralised multi-platform search for a hazardous source in a turbulent flow

Branko Ristic, Christopher Gilliam, William Moran, Jennifer L. Palmer

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

The paper presents a cognitive strategy that enables an interconnected group of autonomous vehicles (moving robots) to search and localise a source of hazardous emissions (gas, biochemical particles) in a coordinated manner. Dispersion of the emitted substance is assumed to be affected by turbulence, resulting in the absence of concentration gradients. The key feature of the proposed search strategy is that it can be applied in a completely decentralised manner as long as the communication network of autonomous vehicles forms a connected graph. By decentralised operation we mean that each moving robot performs computations (i.e. source estimation and robot motion control) locally. Coordination is achieved by exchanging the data with the neighbours only, in a manner which does not require global knowledge of the communication network topology.

Original languageEnglish
Pages (from-to)13-23
Number of pages11
JournalInformation Fusion
Volume58
DOIs
Publication statusPublished - Jun 2020

Bibliographical note

Funding Information:
This research is supported in part by the Defence Science and Technology Group through its Strategic Research Initiative on Trusted Autonomous Systems. Appendix A

Publisher Copyright:
© 2019 Elsevier B.V.

Keywords

  • Autonomous search
  • Decentralised multi-sensor fusion
  • Infotaxi
  • Sensor control
  • Sequential Monte Carlo estimation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems
  • Hardware and Architecture

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