Skin‐Like Airflow Odometry for Micro Aerial Vehicles Based on Distributed Thermal Anemometers

Under restricted global positioning access, navigating micro aerial vehicles (MAVs) is particularly challenging. Therefore, the ability to autonomously estimate velocity and position based on onboard sensors becomes critical. While vision or radar‐based approaches face limitations for MAVs due to payload constraints, poor lighting, or featureless environments, bio‐inspired airflow sensing offers a promising alternative. Airflow interaction with MAVs provides continuous motion cues during flight, enabling airflow odometry—a feasible yet accuracy‐limited solution. This article presents a novel skin‐like airflow odometry system using distributed flexible thermal anemometers embedded in wingtips, allowing real‐time motion estimation where conventional methods fail. Computational fluid dynamics is first employed to analyze the feasibility and sensitivity without changing their aerodynamic profile. A transformer‐enhanced gated recurrent unit network then extracts high‐precision airflow velocity, while model‐based multisensor fusion reduces dead‐reckoning drift and is validated through experiments. To the authors’ knowledge, this demonstrates the first airflow odometry system with positional accuracy surpassing previous research for MAV applications.