针对在动态环境下受运动物体影响而不能准确进行机器人运动估计的问题,提出一种基于ORB特征区域分割的视觉里程计算法。利用相邻区域特征点三维空间距离不变性,对提取的特征点进行区域分割,将图像中运动物体产生的特征点与静态背景的特征点分割开,去除动态物体特征点的影响,再进行相机的位姿估计,从而去除场景中动态物体的干扰。实验结果表明,基于ORB特征区域分割的视觉里程计算法能够实时地在动态和静态环境中进行相机的位姿估计,具有很高的稳健性和精度。

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 are segmented and the feature points generated by the moving objects in the image are separated from the feature points in the static background, and influences of dynamic object feature points are 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.