Attitude and Position Estimation in UAVs using Artificial Landmarks and MEMS Sensors in a Virtual Environment
This work discusses the development of a hybrid estimation algorithm based on computer vision and microelectromechanical system sensors. A mathematical enviroment was developed to simulate the dynamics of the quadrotor and its sensors, a 3D simulation software was also developed, simulating a on-board camera. The results obtained were compared to a TRIAD/MEMS attitude and position estimation technique. A fourty times increase in precision was shown, at the cost of five times additional computational processing time.