Multi-USV Adaptive Exploration Using Kernel Information and Residual Variance.

Gaussian process field validated freshwater analysis informative path planning multi-robot systems sampling hotspots

Journal

Frontiers in robotics and AI
ISSN: 2296-9144
Titre abrégé: Front Robot AI
Pays: Switzerland
ID NLM: 101749350

Informations de publication

Date de publication:
2021
Historique:
received: 13 06 2020
accepted: 25 03 2021
entrez: 14 6 2021
pubmed: 15 6 2021
medline: 15 6 2021
Statut: epublish

Résumé

Using a team of robots for estimating scalar environmental fields is an emerging approach. The aim of such an approach is to reduce the mission time for collecting informative data as compared to a single robot. However, increasing the number of robots requires coordination and efficient use of the mission time to provide a good approximation of the scalar field. We suggest an online multi-robot framework

Identifiants

pubmed: 34124169
doi: 10.3389/frobt.2021.572243
pmc: PMC8194496
doi:

Types de publication

Journal Article

Langues

eng

Pagination

572243

Informations de copyright

Copyright © 2021 Mishra, Koay, Chitre and Swarup.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Science. 2010 Oct 8;330(6001):201-4
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Sci Rep. 2015 Nov 27;5:17306
pubmed: 26610807
Genome Res. 1998 Mar;8(3):175-85
pubmed: 9521921
Genome Res. 1998 Mar;8(3):186-94
pubmed: 9521922

Auteurs

Rajat Mishra (R)

Acoustic Research Laboratory, Tropical Marine Science Institute, National University of Singapore, Singapore, Singapore.

Teong Beng Koay (TB)

Acoustic Research Laboratory, Tropical Marine Science Institute, National University of Singapore, Singapore, Singapore.
NUS Environmental Research Institute, National University of Singapore, Singapore, Singapore.

Mandar Chitre (M)

Acoustic Research Laboratory, Tropical Marine Science Institute, National University of Singapore, Singapore, Singapore.
Department of Electrical & Computer Engineering, Faculty of Engineering, National University of Singapore, Singapore, Singapore.

Sanjay Swarup (S)

NUS Environmental Research Institute, National University of Singapore, Singapore, Singapore.
Singapore Centre for Environmental Life Sciences Engineering, Singapore, Singapore.
Department of Biological Sciences, Faculty of Science, National University of Singapore, Singapore, Singapore.

Classifications MeSH