ARTIFICIAL INTELLIGENCE IN DRONE NAVIGATION: APPROACHES, CHALLENGES AND PROSPECTS
DOI:
https://doi.org/10.34185/1991-7848.itmm.2025.01.107Keywords:
artificial intelligence, automation, computer vision, drone, Kalman filter, machine learning, neural network, PID controller.Abstract
The article reviews modern approaches to the use of artificial intelligence (AI) in the navigation of unmanned aerial vehicles (UAVs), such as machine learning and computer vision, neural networks, PID controllers, Kalman filter and other technologies used for autonomous control of drones. Additional attention is paid to an overview of the main elements of creating an intelligent autonomous drone navigation system, modern technologies used in this area, route optimization, data denoising, real-time decision-making and improving the perception of the environment by an intelligent system. Key challenges are also outlined, including loss of communication with the operator, changing environmental conditions and the complexity of tracking low-visibility moving targets.
References
FPV. techtarget.com. URL: https://www.techtarget.com/whatis/definition/FPV-drone-first-person-view-drone
Kalman filter. URL: https://www.kalmanfilter.net/default.aspx
PID controller. URL: https://dewesoft.com/blog/what-is-pid-controller
PIDNN. URL: https://molefrog.com/etc/pid-neural-network/#d-neuron
