Cargando…

UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance

In this paper we present a surveillance system for early detection of escapers from a restricted area based on a new swarming mobility model called CROMM-MS (Chaotic Rössler Mobility Model for Multi-Swarms). CROMM-MS is designed for controlling the trajectories of heterogeneous multi-swarms of aeria...

Descripción completa

Detalles Bibliográficos
Autores principales: Stolfi, Daniel H., Brust, Matthias R., Danoy, Grégoire, Bouvry, Pascal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933201/
https://www.ncbi.nlm.nih.gov/pubmed/33681299
http://dx.doi.org/10.3389/frobt.2021.616950
_version_ 1783660558501806080
author Stolfi, Daniel H.
Brust, Matthias R.
Danoy, Grégoire
Bouvry, Pascal
author_facet Stolfi, Daniel H.
Brust, Matthias R.
Danoy, Grégoire
Bouvry, Pascal
author_sort Stolfi, Daniel H.
collection PubMed
description In this paper we present a surveillance system for early detection of escapers from a restricted area based on a new swarming mobility model called CROMM-MS (Chaotic Rössler Mobility Model for Multi-Swarms). CROMM-MS is designed for controlling the trajectories of heterogeneous multi-swarms of aerial, ground and marine unmanned vehicles with important features such as prioritising early detections and success rate. A new Competitive Coevolutionary Genetic Algorithm (CompCGA) is proposed to optimise the vehicles’ parameters and escapers’ evasion ability using a predator-prey approach. Our results show that CROMM-MS is not only viable for surveillance tasks but also that its results are competitive in regard to the state-of-the-art approaches.
format Online
Article
Text
id pubmed-7933201
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-79332012021-03-06 UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance Stolfi, Daniel H. Brust, Matthias R. Danoy, Grégoire Bouvry, Pascal Front Robot AI Robotics and AI In this paper we present a surveillance system for early detection of escapers from a restricted area based on a new swarming mobility model called CROMM-MS (Chaotic Rössler Mobility Model for Multi-Swarms). CROMM-MS is designed for controlling the trajectories of heterogeneous multi-swarms of aerial, ground and marine unmanned vehicles with important features such as prioritising early detections and success rate. A new Competitive Coevolutionary Genetic Algorithm (CompCGA) is proposed to optimise the vehicles’ parameters and escapers’ evasion ability using a predator-prey approach. Our results show that CROMM-MS is not only viable for surveillance tasks but also that its results are competitive in regard to the state-of-the-art approaches. Frontiers Media S.A. 2021-02-19 /pmc/articles/PMC7933201/ /pubmed/33681299 http://dx.doi.org/10.3389/frobt.2021.616950 Text en Copyright © 2021 Stolfi, Brust, Danoy and Bouvry. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Robotics and AI
Stolfi, Daniel H.
Brust, Matthias R.
Danoy, Grégoire
Bouvry, Pascal
UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance
title UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance
title_full UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance
title_fullStr UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance
title_full_unstemmed UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance
title_short UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance
title_sort uav-ugv-umv multi-swarms for cooperative surveillance
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933201/
https://www.ncbi.nlm.nih.gov/pubmed/33681299
http://dx.doi.org/10.3389/frobt.2021.616950
work_keys_str_mv AT stolfidanielh uavugvumvmultiswarmsforcooperativesurveillance
AT brustmatthiasr uavugvumvmultiswarmsforcooperativesurveillance
AT danoygregoire uavugvumvmultiswarmsforcooperativesurveillance
AT bouvrypascal uavugvumvmultiswarmsforcooperativesurveillance