Stereo Visual Odometry Algorithm Combined with Optical Flow Tracking
Aiming at the problem that the real-time performance of the system becomes low due to the frequent calculation and matching descriptors of the feature-based visual odometry,a stereo visual odometry combined with optical flow tracking is proposed.Firstly,the initialization is performed to generate the initial key frames and map points,then in the tracking thread,the optical flow tracking feature points are used to obtain the matching relationship,calculate and optimize the camera pose.After meeting the condi-tions for the generating key frames,the current frame is taken as a key frame,the ORB feature points of the image are extracted,the descriptor matching is used to obtain the matching relationship with the feature points of the previous key frame,and triangulate to generate new map points.Finally,the new key frames and map points are optimized using the sliding window algorithm in the optimi-zation thread,and the redundant key frames and map points are eliminated.In the KITTI data,the experimental results show that the trajectory error of the proposed algorithm is at the same level as that of the ORB-SLAM3 algorithm in the trajectory err and stereo mode,and the real-time performance is greatly improved.The average time for tracking each frame image is reduced from 52 ms to 16 ms.In the case of ensuring high precision,the running speed is greatly improved,and it has a high practical value.
visual odometrysimultaneous localization and mappingfeature matchingreal-time performancetrajectory error
万方数据
维普
