Obstacle Avoidance in UAVs: Using a Bug-Inspired Algorithm and Neural Network-Based RGB Camera Collision Prediction

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but.event.date23.04.2024cs
but.event.titleSTUDENT EEICT 2024cs
dc.contributor.authorRaichl, Petr
dc.contributor.authorMarcoň, Petr
dc.contributor.authorJanoušek, Jiří
dc.date.accessioned2024-07-09T07:38:41Z
dc.date.available2024-07-09T07:38:41Z
dc.date.issued2024cs
dc.description.abstractUnmanned Aerial Vehicles (UAVs) are increasingly deployed in complex environments for various applications, necessitating advanced obstacle avoidance capabilities to ensure safety and mission success. Inspired by the simplicity and effectiveness of biological navigation strategies, this study introduces a novel approach to UAV obstacle avoidance, leveraging the principles of the bug algorithm combined with the predictive power of neural networks. We propose a hybrid model that integrates a lightweight neural network to predict potential collisions in real-time. Our methodology employs a two-stage process: first, the neural network assesses the immediate risk of collision; second, the bug algorithm-inspired decision-making process determines the UAV’s maneuvering actions to navigate without crashing to obstacles. The approach was tested both in simulation and real outdoor experiments.en
dc.formattextcs
dc.format.extent327-331cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings I of the 30st Conference STUDENT EEICT 2024: General papers. s. 327-331. ISBN 978-80-214-6231-1cs
dc.identifier.isbn978-80-214-6231-1
dc.identifier.issn2788-1334
dc.identifier.urihttps://hdl.handle.net/11012/249261
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings I of the 30st Conference STUDENT EEICT 2024: General papersen
dc.relation.urihttps://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2024_sbornik_1.pdfcs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectUAVen
dc.subjectObstacle avoidanceen
dc.subjectCollision predictionen
dc.subjectArtificial intelligenceen
dc.subjectNeural Networksen
dc.titleObstacle Avoidance in UAVs: Using a Bug-Inspired Algorithm and Neural Network-Based RGB Camera Collision Predictionen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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