Optimization of Visual Odometry Algorithm Based on ORB Feature

Robot movement cannot be accurately estimated because of the impact of moving objects in a dynamic environment. Therefore, this study proposes a visual odometry algorithm based on ORB (Oriented FAST and Rotated BRIEF) feature regional segmentation. Further, using the distance invariance of the feature points in the adjacent regions in a three-dimensional space, the extracted feature points arc segmented and the feature points generated by the moving objects in the image arc separated from the feature points in the static background, and influences of dynamic object feature points arc removed. Subsequently, the position of the camera can be estimated, thereby removing the interference caused by the dynamic objects in a scene. The experimental results show that the visual odometry algorithm based on ORB feature regional segmentation can perform real-time pose estimation in both dynamic and static environments with good robustness and high precision.