Vision - based self - guided Quadcopter landing on moving platform during fault detection

Fault occurrence in the quadcopter is very common during operation in the air. This paper presents a real-time implementation to detect the fault and then the system is guaranteeing to safely land on the surface, even the moving landing platform. Primarily, PixHawk auto-pilot was used to verify in real-time, with platform detection and various environmental conditions. The method is ensuring the quadcopter operates in the landing area zone with the help of a GPS feature. Then the precise landing on the astable-landing platform is calibrated automatically using the vision-based learning feedback technique. The proposed objective is developed using reconfigurable Raspberry Pi-3 with a Pi camera. The full decision on an efficient landing algorithm is deployed into the quadcopter. The system is self-guided and automatically returns to home-based whenever the fault detects. The study is conducted with the situation of low battery operation and the trigger of auto-pilot helps to land the device safely before any mal-function. The system is featured with predetermined speed and altitude while navigating the home base, thus improves the detection process. Finally, the experiment study provided successful trials to track usable platform, landing on a restricted area, and disarm the motors autonomously