Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques
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 unpred...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/9/2566 |
| _version_ | 1797569197466714112 |
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| author | Daniel H. Stolfi Matthias R. Brust Grégoire Danoy Pascal Bouvry |
| author_facet | Daniel H. Stolfi Matthias R. Brust Grégoire Danoy Pascal Bouvry |
| author_sort | Daniel H. Stolfi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T20:07:28Z |
| format | Article |
| id | doaj.art-6da07bfca6924b1fb928dd1d121165f9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T20:07:28Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-6da07bfca6924b1fb928dd1d121165f92023-11-19T23:10:34ZengMDPI AGSensors1424-82202020-04-01209256610.3390/s20092566Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary TechniquesDaniel H. Stolfi0Matthias R. Brust1Grégoire Danoy2Pascal Bouvry3SnT, University of Luxembourg, L-4364 Esch-sur-Alzette, LuxembourgSnT, University of Luxembourg, L-4364 Esch-sur-Alzette, LuxembourgSnT, University of Luxembourg, L-4364 Esch-sur-Alzette, LuxembourgSnT, University of Luxembourg, L-4364 Esch-sur-Alzette, LuxembourgIn 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.https://www.mdpi.com/1424-8220/20/9/2566swarm roboticsmobility modelinter-swarm collaborationunmanned aerial vehicleunmanned ground vehicleevolutionary algorithm |
| spellingShingle | Daniel H. Stolfi Matthias R. Brust Grégoire Danoy Pascal Bouvry Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques Sensors swarm robotics mobility model inter-swarm collaboration unmanned aerial vehicle unmanned ground vehicle evolutionary algorithm |
| title | Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques |
| title_full | Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques |
| title_fullStr | Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques |
| title_full_unstemmed | Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques |
| title_short | Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques |
| title_sort | emerging inter swarm collaboration for surveillance using pheromones and evolutionary techniques |
| topic | swarm robotics mobility model inter-swarm collaboration unmanned aerial vehicle unmanned ground vehicle evolutionary algorithm |
| url | https://www.mdpi.com/1424-8220/20/9/2566 |
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