Intelligent Visual Odometry: Leveraging SURF Descriptors for Autonomous UAV Navigation

Accurate velocity estimation to autonomous navigation for Unmanned Aerial Vehicles (UAVs). This study presents a monocular visual odometry pipeline that leverages the Speeded-Up Robust Features (SURF) algorithm to provide a robust and computationally efficient solution for this task. The proposed framework operates the (SURF) method under the assumption of constant-altitude flight over planar terrain. The combined approach demonstrates superior performance in real-world computer vision applications where both feature matching accuracy and computational efficiency are paramount.experimental results demonstrate that our SURF-based approach delivers consistent and reliable velocity measurements, achieving an optimal balance between computational efficiency and estimation accuracy, making it highly suitable for real-time UAV applications.