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
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