Autonomous landing of a multicopter using computer vision

Takeoff, normal flight, and even specialized tasks such as taking pictures, are essentially solved problems in autonomous drone flight. This notably excludes landing, which typically requires a pilot because of its inherently risky nature. This project attempts to solve the problem of autonomous drone landing using computer vision and fiducial markers - and specifically does not use GPS as a primary means of navigation during landing. The system described in this thesis extends the functionality of the widely-used, open-source ArduPilot software which runs on many drones today, and which has only primitive functionality for autonomous landing. This system is implemented as a set of ROS modules which interact with ArduPilot for control. It is designed to be easily integrated into existing ArduPilot drone systems through the addition of a companion board and gimbal-mounted camera. Results are presented to evaluate the system's performance with regard to pose estimation and landing capabilities within Gazebo 9 simulator. Guidelines are provided for migration to a physical system as a gateway to future work