Mathematical Modeling of Optimal Drone Flight Trajectories for Enhanced Object Detection in Video Streams Using Kolmogorov–Arnold Networks

Issembayeva A. Kuznetsov O. Shaushenova A. Nurpeisova A. Shuitenov G. Ongarbayeva M.
June 2025 Multidisciplinary Digital Publishing Institute (MDPI)

Technologies
2025 #13 Issue 6

This study addresses the critical challenge of optimizing drone flight parameters for enhanced object detection in video streams. While most research focuses on improving detection algorithms, the relationship between flight parameters and detection performance remains poorly understood. We present a novel approach using Kolmogorov–Arnold Networks (KANs) to model complex, non-linear relationships between altitude, pitch angle, speed, and object detection performance. Our main contributions include the following: (1) the systematic analysis of flight parameters’ effects on detection performance using the AU-AIR dataset, (2) development of a KAN-based mathematical model achieving R² = 0.99, (3) identification of optimal flight parameters through multi-start optimization, and (4) creation of a flexible implementation framework adaptable to different UAV platforms. Sensitivity analysis confirms the solution’s robustness with only 7.3% performance degradation under ±10% parameter variations. This research bridges flight operations and detection algorithms, offering practical guidelines that enhance the detection capability by optimizing image acquisition rather than modifying detection algorithms.

AU-AIR dataset , computer vision , flight parameter optimization , Kolmogorov–Arnold networks , object detection in video streams , unmanned aerial vehicles

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Department of Information Systems, Faculty of Computer Systems and Professional Education, S. Seifullin Kazakh Agro Technical Research University, Astana, 010000, Kazakhstan
Department of Theoretical and Applied Sciences, eCampus University, Via Isimbardi 10, CO, Novedrate, 22060, Italy
Department of Intelligent Software Systems and Technologies, School of Computer Science and Artificial Intelligence, Karazin Kharkiv National University, 4 Svobody Sq., V.N, Kharkiv, 61022, Ukraine
Department of Information Systems and Technologies, Faculty of Applied Sciences, Esil University, Astana, 010000, Kazakhstan
Department of Information and Communication Technologies, Faculty of Natural Sciences, Sherkhan Murtaza International Taraz University, Taraz, 080000, Kazakhstan

Department of Information Systems
Department of Theoretical and Applied Sciences
Department of Intelligent Software Systems and Technologies
Department of Information Systems and Technologies
Department of Information and Communication Technologies

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