Research on Mobile Robot Localization Algorithm with Improved ORB Extraction Matching

Aiming at the problem of inaccurate positioning accuracy of V-SLAM system caused by poor texture and blurred images generated by mobile robots during rapid movement and large angle rotation, an improved ORB feature extraction matching algorithm is proposed. Firstly, using the statistical form of information entropy to calculate the image features, image enhancement is used to highlight the feature information of poorly textured and blurred image blocks, improve the efficiency of feature point detection, and enhance the robustness of the system. In addition, to improve the accuracy of feature matching, the BEBLID descriptor is used instead of the BRIEF descriptor for feature description. Through experimental verification on the publicly available TUM data set, it was found that the improved algorithm has a higher matching accuracy than the ORB algorithm, and has a significant increase in algorithm time compared to the ORB algorithm. After trajectory calculation, the improved algorithm is more in line with the real trajectory in camera motion and has a good improvement in pose accuracy.