The integration of additional sensors, such as Inertial Measurement Units (IMUs) and visual-inertial odometry, can significantly enhance the distance estimation capabilities of UAVs operating in deep hazardous tunnels. IMUs provide critical data on the UAV's orientation, acceleration, and angular velocity, which can be used to complement the optical flow measurements. By fusing IMU data with optical flow information, the system can achieve more robust localization, especially in environments where visual features are sparse or illumination is poor.
Visual-inertial odometry combines data from both visual sensors and IMUs to estimate the UAV's position and orientation more accurately. This technique can help mitigate the limitations of optical flow, particularly in low-texture environments like tunnel walls. By leveraging the motion data from the IMU, the system can predict the UAV's trajectory even when optical flow measurements are unreliable. This predictive capability is crucial in maintaining accurate distance estimation, especially when the optical flow algorithm encounters failure modes due to poor lighting or lack of surface features.
Moreover, the use of these additional sensors can enhance the overall robustness of the distance measurement module. For instance, if the optical flow sensor fails to provide reliable data due to environmental conditions, the IMU can still provide valuable information about the UAV's movement, allowing for a fallback mechanism that ensures continuous operation. This sensor fusion approach not only improves accuracy but also increases the reliability of the UAV's navigation system in challenging tunnel environments.