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    • 摘要: 针对光束法对初始值依赖性大以及双目相机模型的特点,在ORB-SLAM2算法基础提出了一种三阶段局部双目光束法平差算法。在帧间位姿跟踪阶段,为降低累积误差对匀速模型下3D-2D匹配的影响,引入环形匹配机制进一步剔除误匹配,并将关键帧地图点与当前帧3D-2D投影匹配;在跟踪局部地图阶段插入关键帧时,增加双目相机基距参数优化环节;在局部地图优化阶段,将最近的两关键帧间的普通帧也作为局部帧进行优化。KITTI数据集实验表明,三阶段局部双目光束法平差与ORB-SLAM2相比,构造了更多精确的3D-2D匹配,增加了优化约束条件,提高了运动估计与优化精度。

       

      Abstract: In this paper, a three-stage local binocular BA (bundule adjustment) is proposed based on the ORB-SLAM2 algorithm, which is based on the large value of the initial value and the binocular camera model. In order to reduce the influence of cumulative error on 3D-2D matching in the uniform model, the ring matching mechanism is introduced to eliminate the mismatched again and match the key frame map point with the current frame 3D-2D projection. In the tracking part of the local map optimization phase, the normal frame between the two nearest key frames is also optimized as the local frame when the key phase is inserted into the key frame. KITTI data set experiments show that the three-stage local binocular beam method has more accurate 3D-2D matching compared with ORB-SLAM2, which improves the optimization constraint and improves the motion estimation and optimization precision.