Decentralized Learning With Limited Communications for Multi-robot Coverage of Unknown Spatial Fields

Kensuke Nakamura, Maria Santos, Naomi Ehrich Leonard

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

1 Scopus citations

Abstract

This paper presents an algorithm for a team of mobile robots to simultaneously learn a spatial field over a domain and spatially distribute themselves to optimally cover it. Drawing from previous approaches that estimate the spatial field through a centralized Gaussian process, this work leverages the spatial structure of the coverage problem and presents a decentralized strategy where samples are aggregated locally by establishing communications through the boundaries of a Voronoi partition. We present an algorithm whereby each robot runs a local Gaussian process calculated from its own measurements and those provided by its Voronoi neighbors, which are incorporated into the individual robot's Gaussian process only if they provide sufficiently novel information. The performance of the algorithm is evaluated in simulation and compared with centralized approaches.

Original languageEnglish (US)
Title of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages9980-9986
Number of pages7
ISBN (Electronic)9781665479271
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022 - Kyoto, Japan
Duration: Oct 23 2022Oct 27 2022

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2022-October
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2022
Country/TerritoryJapan
CityKyoto
Period10/23/2210/27/22

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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