Literature DB >> 33681299

UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance.

Daniel H Stolfi1, Matthias R Brust1, Grégoire Danoy1,2, Pascal Bouvry1,2.   

Abstract

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.
Copyright © 2021 Stolfi, Brust, Danoy and Bouvry.

Entities:  

Keywords:  UAV; UGV; UMV; competitive coevolutionary genetic algorithm; mobility model; parameter optimisation; surveillance system; swarm robotics

Year:  2021        PMID: 33681299      PMCID: PMC7933201          DOI: 10.3389/frobt.2021.616950

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


  2 in total

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Authors:  Yun Sun; Herman Fesenko; Vyacheslav Kharchenko; Luo Zhong; Ihor Kliushnikov; Oleg Illiashenko; Olga Morozova; Anatoliy Sachenko
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  2 in total

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