Abstract The rapid advancement of drone technology has led to its widespread adoption in education and research, offering students hands-on experience in aerodynamics, robotics, and automation. This study aims to identify the most suitable quadcopter prototype for university research by analysing different drone types, hardware components, flight control software, and autonomous navigation solutions. The research employs a comparative approach, evaluating various technologies based on performance, cost, and educational relevance. Results indicate that multi-rotor drones, particularly quadcopters, provide the best balance between usability and research potential. A combination of brushless motors, Li-Po batteries, carbon fibre frames, and PX4 or ArduPilot software is recommended for an optimal learning platform. Furthermore, integrating GPS and computer vision enhances autonomy, allowing students to explore AI-driven navigation. These findings contribute to the development of an efficient and cost-effective drone prototype tailored for university-level experimentation and innovation.
Mamchur et al. (Sat,) studied this question.