Reports a learning-based airflow-inertial odometry system that fuses thermal anemometer, IMU, ESC, and barometer data to estimate MAV speed and position, with 5.7 m drift over 203 s in a GPS and vision denied indoor flight.
Deep learning flight speed estimation using thermal anemometers
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Learning-based Airflow Inertial Odometry for MAVs using Thermal Anemometers in a GPS and vision denied environment
Reports a learning-based airflow-inertial odometry system that fuses thermal anemometer, IMU, ESC, and barometer data to estimate MAV speed and position, with 5.7 m drift over 203 s in a GPS and vision denied indoor flight.