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.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.