泡泡一分鐘：FMD Stereo SLAM: Fusing MVG and Direct Formulation Towards Accurate and Fast Stereo SLAM

FMD Stereo SLAM: Fusing MVG and Direct Formulation Towards Accurate and Fast Stereo SLAM

FMD Stereo SLAM：融合MVG和直接方法，實現準確，快速的雙目SLAM

Fulin Tang, Heping Li, Yihong Wu

We propose a novel stereo visual SLAM framework considering both accuracy and speed at the same time. The framework makes full use of the advantages of key-feature based multiple view geometry(MVG)and direct-based formulation. At the front-end, our system performs direct formulation and constant motion model to predict a robust initial pose, reprojects local map to find 3D-2D correspondence and finally refines pose by the reprojection error minimization. This frontend process makes our system faster. At the back-end, MVG is used to estimate 3D structure. When a new keyframe is inserted, new mappoints are generated by triangulating. In order to improve the accuracy of the proposed system, bad mappoints are removed and a global map is kept by bundle adjustment. Especially, the stereo constraint is performed to optimize the map. This back-end process makes our system more accurate. Experimental evaluation on EuRoC dataset shows that the proposed algorithm can run at more than 100 frames per second on a consumer computer while achieving highly competitive accuracy.

咱們提出了一種新穎的雙目視覺SLAM框架，同時兼顧了精度和速度。該框架充分利用了基於關鍵特徵的多視圖幾何（MVG）和基於直接方法的優點。在前端，咱們的系統執行直接公式和恆定運動模型來預測穩健的初始姿式，從新投影局部地圖以找到3D-2D對應，並經過重投影偏差最小化來最終肯定姿式。這個前端過程使咱們的系統更快。 在後端，MVG用於估計3D結構。 插入新關鍵幀時，經過三角測量生成新的地圖點。爲了提升所提出系統的準確性，刪除了壞的地圖點並經過束調整保持全局地圖。 特別地，執行立體約束以優化地圖。這種後端流程使咱們的系統更加準確。 對EuRoC數據集的實驗評估代表，所提出的算法能夠在消費者計算機上以每秒100幀以上的速度運行，同時實現高度競爭的準確性。