基于点线特征的单目同步定位与建图初始化方法

Monocular Simultaneous Localization and Mapping Initialization Method Based on Point and Line Features

针对目前单目同步定位与建图(SLAM)初始化方法鲁棒性差、精度低的问题,提出了一种基于点线特征的单目SLAM初始化方法。首先,在两帧图像之间提取线特征,并进行特征匹配。然后,通过最大化投影线特征的重叠长度优化两帧图像之间的初始旋转和平移矩阵。最后,用滑动窗口增加初始化的图像帧数,利用多帧图像的信息和约束关系以及全局光束平差法优化初始地图和估计的相机关键帧位姿。在TUM和OpenLORIS数据集上的测试结果表明,相比传统初始化方法,本方法的鲁棒性更好、精度更高,能在具有挑战性的场景中快速完成高精度初始化。

Aiming at the problem of poor robustness and accuracy in the initialization of monocular visual simultaneous localization and mapping(SLAM),this paper proposes a robust initialization method based on point and line features.First,the line features are extracted and matched between two frames.Then,the initial rotation matrix and translation matrix between the two frames are optimized by maximizing the overlap length of the projected line features.Finally,a sliding window is used to increase the number of initial image frames,and the initial map and the estimated keyframe pose are optimized based on information and constraint of multi-frame images and the global bundle adjustment method.The test results on the TUM and OpenLORIS datasets show that compared with traditional initialization methods,the method is more robust and accurate,and can quickly complete high-precision initialization in challenging scenarios.