Russian Federation
Russian Federation
UDC 629.3.05
The article is devoted to the role of artificial intelligence (AI) technologies in controlling robotic units of cars and agricultural machinery. The key difference between intelligent systems based on machine learning and computer vision from traditional automation is considered. The article describes the main areas of AI application: from autonomous driving systems and active vehicle safety to fully autonomous tractors and robotic harvesting systems. The article also addresses current issues related to the implementation of this technology, including security, cyber defense, and ethics, and identifies the industry's development prospects.
artificial intelligence, robotic aggregates, autonomous driving, autonomous tractors, machine learning, computer vision, active safety systems, big data, lidar, precision agricultural machinery
1. Safonov, K. V. Iskusstvennyy intellekt i neyronnye seti v sistemah upravleniya transportnymi sredstvami. — M.: Tehnosfera, 2021. — 356 s.
2. Goodfellow, I., Bengio, Y., Courville, A. Deep Learning. — MIT Press, 2016. — 800 p. (Klassicheskaya kniga po osnovam glubokogo obucheniya).
3. Gupta, L., Tangavalam, P. Sistemy avtonomnogo vozhdeniya: komp'yuternoe zrenie i upravlenie robotami. — Dolgoprudnyy: Intellekt, 2022. — 412 s.
4. Zhayvoronok, D. A. Povyshenie kachestva obmena informaciey abonentov avtotransportnoy infrastruktury / D. A. Zhayvoronok, I. V. Terehina, F. A. Shakina // Perspektivy razvitiya, innovacii i informacionnye tehnologii na transporte : Materialy Mezhdunarodnoy molodezhnoy nauchno-prakticheskoy konferencii, Voronezh, 17–18 oktyabrya 2024 goda. – Voronezh: Voronezhskiy gosudarstvennyy lesotehnicheskiy universitet im. G.F. Morozova, 2024. – S. 145-150. – DOIhttps://doi.org/10.58168/DPIITT2024_145-150. – EDN CRNGCH.



