Development of Deep Stall Landing System for Fixed-Wing Aircraft using Image Processing

Abstract

Currently, Unmanned Aerial Vehicle (UAV) plays a huge role, especially fixed-wing UAVs that can be used for various missions such as wide area survey work. It can also carry heavy loads over a long distance. And use less power. However, this type of UAV requires a relatively large runway or landing area. If the landing is used as a net landing, it will need a lot of space to install a net anyway. On the other hand, if using a multirotor UAV or Hybrid model (tilt-wing) that uses less space for take-off and landing. Nevertheless, there will be a limit on speed. If the wind is strong, it will not be able to fly and unable to carry enough load. Therefore, the organizers have foreseen the problem and fix the take-off and landing of fixed-wing UAV by using hand launch method for take-off while landing will use deep stall landing (GPS + Camera) that uses GPS to determine the radius zone 25 meters from the target to land in the start deep stall, in which this landing method will nose up until the angle of attack (AOA) is enough rates to cause the fixed-wing to lose lifting force and land at the specified point using camera to detect landing targets and adjusting the control surface on the fixed-wing elevator to land as close as possible to the specified point. It must be able to land closer to the target than using GPS or the pilot only. The results revealed that GPS landings had an average radius between the landing point and the target being 15.59 m. Pilot landings had an average radius between the landing point and the target being 14.71 m and GPS + Camera landing had an average the radius between the landing point and the target being 7.22 m. If the landing distance is calculated only the longitudinal axis, so GPS landing distance was 13.1 m. Pilot landing was 8.7 m and the GPS + Camera landing was 5.37 m. Furthermore, deep stall landing (GPS + Camera) can land closer than using GPS and pilot only.