Development and testing of an event-based visual-inertial odometry algorithm

This thesis presents the development and evaluation of an event-based visual-inertial odometry algorithm. The system processes data from an event camera and an inertial measurement unit (IMU), combining them through sensor fusion. The fusion of visual and inertial information enables accurate motion estimation. The algorithm was tested in various dynamic scenarios to assess its performance and robustness.