Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones

Dariusz Marek; Jakub Szyguła; Piotr Biernacki; Marcin Paszkuta; Adam Domański; Marcin Fojcik; Marta Szczygieł; Konrad Wojciechowski

doi:10.1145/3737899.3768522

Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones

Dariusz Marek
, Jakub Szyguła
, Piotr Biernacki
, Marcin Paszkuta
, Adam Domański
, Marcin Fojcik
, Marta Szczygieł
, Konrad Wojciechowski

Institute of Theoretical and Applied Informatics of the Polish Academy of Sciences
Western Norway University of Applied Sciences
Polish-Japanese Academy of Information Technology
Academy of Silesia

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

1 Cytowanie z bazy Scopus

Abstrakt

This paper presents a simplified mechanism for collision avoidance in drone swarms flying in dynamic environments. The algorithm is based on sharing information between drones about their positions and planned movements, and uses repulsion vectors to adjust flight paths and avoid obstacles. In this work, we introduce a way to automatically adjust one of the key parameters of the algorithm using a simple artificial neuron. This makes the system more flexible and better adapted to changing conditions, while still keeping it easy to implement and suitable for use in small, low-cost drones. The solution works without central control and supports safe, coordinated flight.

Język oryginału	angielski
Tytuł publikacji goszczącej	FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility
Wydawca	Association for Computing Machinery, Inc
Strony	44-51
Liczba stron	8
ISBN (elektroniczny)	9798400719769
Identyfikatory DOI	https://doi.org/10.1145/3737899.3768522
Status publikacji	Opublikowano - 2 gru 2025
Wydarzenie	2025 Federated Learning and Edge AI for Privacy and Mobility, FLEdge-AI 2025 - Hong Kong, Chiny Czas trwania: 4 lis 2025 → 8 lis 2025

Seria publikacji

Nazwa	FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility

Konferencja

Konferencja	2025 Federated Learning and Edge AI for Privacy and Mobility, FLEdge-AI 2025
Kraj/Terytorium	Chiny
Miejscowość	Hong Kong
Okres	4/11/25 → 8/11/25

Cele SDG ONZ

Ten wynik przyczynia się do realizacji następujących celów zrównoważonego rozwoju

Cel 3 Dobre zdrowie i dobre samopoczucie

Obszary tematyczne ASJC Scopus

Sztuczna inteligencja
Zastosowania informatyki
Inżynieria elektryczna i elektroniczna
Anestezjologia i medycyna bólu

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10.1145/3737899.3768522

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Cytowanie

Marek, D., Szyguła, J., Biernacki, P., Paszkuta, M., Domański, A., Fojcik, M., Szczygieł, M., & Wojciechowski, K. (2025). Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones. W FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility (str. 44-51). (FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility). Association for Computing Machinery, Inc. https://doi.org/10.1145/3737899.3768522

Marek, Dariusz ; Szyguła, Jakub ; Biernacki, Piotr i in. / Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones. FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility. Association for Computing Machinery, Inc, 2025. str. 44-51 (FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility).

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title = "Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones",

abstract = "This paper presents a simplified mechanism for collision avoidance in drone swarms flying in dynamic environments. The algorithm is based on sharing information between drones about their positions and planned movements, and uses repulsion vectors to adjust flight paths and avoid obstacles. In this work, we introduce a way to automatically adjust one of the key parameters of the algorithm using a simple artificial neuron. This makes the system more flexible and better adapted to changing conditions, while still keeping it easy to implement and suitable for use in small, low-cost drones. The solution works without central control and supports safe, coordinated flight.",

keywords = "collision avoidance, neural networks, distributed systems, Federated Learnings, UAVs, positioning accuracy, software-in-the-loop (SITL), Swarm of Drones",

author = "Dariusz Marek and Jakub Szygu{\l}a and Piotr Biernacki and Marcin Paszkuta and Adam Doma{\'n}ski and Marcin Fojcik and Marta Szczygie{\l} and Konrad Wojciechowski",

note = "Publisher Copyright: {\textcopyright} 2025 Copyright held by the owner/author(s).; 2025 Federated Learning and Edge AI for Privacy and Mobility, FLEdge-AI 2025 ; Conference date: 04-11-2025 Through 08-11-2025",

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doi = "10.1145/3737899.3768522",

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Marek, D , Szyguła, J , Biernacki, P , Paszkuta, M , Domański, A, Fojcik, M, Szczygieł, M & Wojciechowski, K 2025, Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones. w FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility. FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility, Association for Computing Machinery, Inc, str. 44-51, 2025 Federated Learning and Edge AI for Privacy and Mobility, FLEdge-AI 2025, Hong Kong, Chiny, 4/11/25. https://doi.org/10.1145/3737899.3768522

Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones. / Marek, Dariusz ; Szyguła, Jakub ; Biernacki, Piotr i in.
FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility. Association for Computing Machinery, Inc, 2025. str. 44-51 (FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

TY - GEN

T1 - Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones

AU - Marek, Dariusz

AU - Szyguła, Jakub

AU - Biernacki, Piotr

AU - Paszkuta, Marcin

AU - Domański, Adam

AU - Fojcik, Marcin

AU - Szczygieł, Marta

AU - Wojciechowski, Konrad

PY - 2025/12/2

Y1 - 2025/12/2

N2 - This paper presents a simplified mechanism for collision avoidance in drone swarms flying in dynamic environments. The algorithm is based on sharing information between drones about their positions and planned movements, and uses repulsion vectors to adjust flight paths and avoid obstacles. In this work, we introduce a way to automatically adjust one of the key parameters of the algorithm using a simple artificial neuron. This makes the system more flexible and better adapted to changing conditions, while still keeping it easy to implement and suitable for use in small, low-cost drones. The solution works without central control and supports safe, coordinated flight.

AB - This paper presents a simplified mechanism for collision avoidance in drone swarms flying in dynamic environments. The algorithm is based on sharing information between drones about their positions and planned movements, and uses repulsion vectors to adjust flight paths and avoid obstacles. In this work, we introduce a way to automatically adjust one of the key parameters of the algorithm using a simple artificial neuron. This makes the system more flexible and better adapted to changing conditions, while still keeping it easy to implement and suitable for use in small, low-cost drones. The solution works without central control and supports safe, coordinated flight.

KW - collision avoidance

KW - neural networks, distributed systems, Federated Learnings, UAVs, positioning accuracy

KW - software-in-the-loop (SITL)

KW - Swarm of Drones

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DO - 10.1145/3737899.3768522

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T3 - FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility

SP - 44

EP - 51

BT - FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility

PB - Association for Computing Machinery, Inc

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Y2 - 4 November 2025 through 8 November 2025

ER -

Marek D , Szyguła J , Biernacki P , Paszkuta M , Domański A, Fojcik M i in. Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones. W FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility. Association for Computing Machinery, Inc. 2025. str. 44-51. (FLEdge-AI 2025 - Proceedings of the 2025 Federated Learning and Edge AI for Privacy and Mobility). doi: 10.1145/3737899.3768522

Neural Tuning of Parameters in a Collision Avoidance Mechanism for Swarms of Drones

Abstrakt

Seria publikacji

Konferencja

Cele SDG ONZ

Obszary tematyczne ASJC Scopus

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