Visual odometry data fusion for indoor localization of an unmanned aerial vehicle

This research aims at design and development of an Unmanned Aerial Vehicle which is spatially aware in an indoor environment devoid of GPS and SLAM algorithms. The sensor readings used for the indoor localization were fused by using an onboard autopilot system called Pixhawk. The presented work aims at enhancing the performances and optimizing the existing state estimation codes to get better results, in an indoor environment.