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Using a Drone Swarm/Team for Safety, Security and Protection Against Unauthorized Drones
Saab AB, Sweden.
Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-5562-1424
Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
2024 (engelsk)Inngår i: Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH , 2024, s. 263-277Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

There is an increased need for protection against unauthorized entry of drones as there has been an increased number of reports of UAV’s entering restricted areas. In this paper we explore an approach of using a swarm/team of drones that are able to cooperate, to autonomously engage and disable one or more unauthorized drones entering a restricted area. In our approach, we have investigated technologies for distributed decision-making and task allocation in real-time, in a dynamic simulated environment and developed descriptive models for how such technologies may be exploited in a mission designed for a drone swarm. This includes the definition of discrete tasks, how they interact and how they are composed to form such a mission, as well as the realization and execution of these tasks using machine learning models combined with behaviour trees. To evaluate our approach, we use a simulated environment for mission execution where relevant KPI’s related to the design of the mission have been used to measure how efficient our approach is in deterring or incapacitating unauthorized drones. The evaluation has been performed using Monte-Carlo simulations on a batch of randomized scenarios and measures of effectiveness has been used to measure each scenario instance and later compiled into a final assessment for the main scenario as well as each ingoing task. The results show a mission success in 93% of the simulated scenarios. Of these 93%, 58% of the scenarios resulted in the threat being neutralized and in 35% of the scenarios the threat was driven away from the critical area. We believe that the application of such measurements aids to validate the applicability of this capability in a real-world scenario and in order to assert the relevance of these parameters, future validations in real-world operational scenarios are warranted.

sted, utgiver, år, opplag, sider
Springer Science and Business Media Deutschland GmbH , 2024. s. 263-277
Emneord [en]
Drone swarm, Drones, Protection, Safety, Security, Decision making, Intelligent systems, Monte Carlo methods, Petroleum reservoir evaluation, Decision task, Distributed decision making, Distributed-decision makings, Real- time, Security and protection, Simulated environment, Task allocation
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Identifikatorer
URN: urn:nbn:se:mdh:diva-65370DOI: 10.1007/978-3-031-39619-9_19Scopus ID: 2-s2.0-85181980978ISBN: 9783031396182 (tryckt)OAI: oai:DiVA.org:mdh-65370DiVA, id: diva2:1828604
Konferanse
7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, 13 June 2023 through 15 June 2023
Tilgjengelig fra: 2024-01-17 Laget: 2024-01-17 Sist oppdatert: 2024-01-17bibliografisk kontrollert

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