The Autonomous Fixed-Wing Drone Version YTP16 (Yaw-Tracking-Path) and 17 Map Way Points to Support Unit Operations Tasks

Autonomous-based fixed-wing drones have become an important solution in a variety of applications, such as mapping, surveillance, and logistics, due to their energy efficiency and wider range. This study aims to design and test the performance of an autonomous fixed-wing drone that is able to follow 16 waypoints with high precision using the YTP16 (Yaw-Tracking-Path) algorithm and 17 map waypoints. The methods used include the design of the control system, the integration of GPS and IMU sensors, and field testing in 10 experiments. The YTP16 algorithm is designed to minimize path deviation by utilizing yaw, GPS, and waypoint data. The test results showed that the drone was able to follow a path with an average error tolerance of 1.3% (in the range of 1-2%) at all waypoints. The graph of the test results shows the consistency of the drone's performance in following the programmed path. Environmental factors such as wind and GPS interference affect accuracy slightly, but remain within acceptable tolerance limits. This study proves that the YTP16 system is effective in improving the accuracy of autonomous navigation on fixed-wing drones. These findings make a significant contribution to the development of drone technology for applications that require high precision, such as area mapping and surveillance missions. In the future, research can be developed by adding obstacle avoidance features and algorithm optimization for more complex environmental conditions.