Learned Inertial Odometry for Autonomous Drone Racing

Inertial odometry is a cost-effective solution for quadrotor state estimation, but it suffers from drift. This study introduces a learning-based odometry algorithm for drone racing, combining inertial measurements with a model-based filter. Results show it outperforms other methods and has potential for agile quadrotor flight research.

Source: Davide Scaramuzza