Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractDevelopment and validation of the GC method for the quantitative determination of semi-volatile solvents in the pharmaceutical substance bosentan    Next AbstractDetermination of acetyl gestagenic steroids in kidney fat by automated supercritical fluid extraction and liquid chromatography ion-trap mass spectrometry »

Sensors (Basel)


Title:Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques
Author(s):Stolfi DH; Brust MR; Danoy G; Bouvry P;
Address:"SnT, University of Luxembourg, L-4364 Esch-sur-Alzette, Luxembourg. FSTM/DCS, University of Luxembourg, L-4364 Esch-sur-Alzette, Luxembourg"
Journal Title:Sensors (Basel)
Year:2020
Volume:20200430
Issue:9
Page Number: -
DOI: 10.3390/s20092566
ISSN/ISBN:1424-8220 (Electronic) 1424-8220 (Linking)
Abstract:"In this article, we propose a new mobility model, called Attractor Based Inter-Swarm collaborationS (ABISS), for improving the surveillance of restricted areas performed by unmanned autonomous vehicles. This approach uses different types of vehicles which explore an area of interest following unpredictable trajectories based on chaotic solutions of dynamic systems. Collaborations between vehicles are meant to cover some regions of the area which are unreachable by members of one swarm, e.g., unmanned ground vehicles on water surface, by using members of another swarm, e.g., unmanned aerial vehicles. Experimental results demonstrate that collaboration is not only possible but also emerges as part of the configurations calculated by a specially designed and parameterised evolutionary algorithm. Experiments were conducted on 12 different case studies including 30 scenarios each, observing an improvement in the total covered area up to 11%, when comparing ABISS with a non-collaborative approach"
Keywords:Algorithms *Pheromones bio-inspiration evolutionary algorithm inter-swarm collaboration mobility model pheromones swarm robotics unmanned aerial vehicle unmanned ground vehicle;
Notes:"MedlineStolfi, Daniel H Brust, Matthias R Danoy, Gregoire Bouvry, Pascal eng N62909-18-1-2176/Office of Naval Research/ Switzerland 2020/05/06 Sensors (Basel). 2020 Apr 30; 20(9):2566. doi: 10.3390/s20092566"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 22-11-2024