Image Processing on a Master of Multi-Quadcopter for Optimizing Area Boundary Monitoring System

Shifting regional boundary markers is a regional border issue that often occurs. One of the reasons this happens is because the regional boundary markers are in places that are difficult to reach. It is hoped that implementing image processing methods on drones can prevent this problem from occurring. This research aims to test the accuracy of drone movements and image processing performance to monitor waypoint conditions. This test was carried out by observing and comparing the coordinates of each follower drone with the master when the drone took a picture of the arUco marker at the waypoint. The research results show that the precision of drone movements is quite high. The drone can go to the precisely specified waypoint. The position difference between master and slave is very small. Image processing also runs well. The system can recognize the arUco ID and its location coordinates. Also, the system has high accuracy, marker shifts can be detected even if they only shift as far as 0.004 m.