What type of study is this?

This is a Quantitative Study study.

October 10, 2025

Automated Uav Control System Based on Artificial Intelligence Elements

Key Points

The system enhances UAV efficiency through the use of machine learning and neural networks for real-time tasks.
Key performance involves trajectory prediction and obstacle avoidance, utilizing reinforcement learning for self-improvement.
Implementation discussions include military applications and emergency monitoring, highlighting significant operational benefits.
The architecture includes essential sensor modules such as GPS, camera, and LiDAR with communication tools for telemetry.

Abstract

This paper presents the architecture of an automated UAV control system that includes an onboard computer with machine learning capabilities, sensor modules (GPS, camera, LiDAR, IMU), and communication tools for telemetry transmission. The system’s operation model is based on the use of neural networks for target detection, trajectory prediction, and obstacle avoidance. Particular attention is given to reinforcement learning algorithms, which allow the control system to independently improve its behavior based on action evaluation. The implementation potential of such systems in military applications, reconnaissance missions, and emergency monitoring is discussed. The integration of AI into control systems significantly enhances the efficiency of UAVs, reduces operator workload, and enables autonomous execution of complex tasks in real-time 1,2.

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Cite This Study

Gulenko et al. (Tue,) studied this question.

synapsesocial.com/papers/68e861a57ef2f04ca37e4638 https://doi.org/https://doi.org/10.34132/mspc2025.01.06.14

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