基于改进ORB算法的移动机器人视觉SLAM方法研究

Research on visual SLAM method of mobile robot based on improved ORB algorithm

以移动机器人视觉导航为应用背景,针对传统ORB算法在视觉SLAM中存在特征点分布不均匀、重叠特征点较多的问题,提出一种改进ORB算法。首先,对每层图像的尺度空间金字塔进行网格划分,增加空间尺度信息;其次,在特征点检测时,采用改进FAST角点自适应阈值提取,设置感兴趣区域;然后,采用非极大值抑制的方法,抑制低阈值特征点的输出;最后,使用基于区域图像特征点分布的方差数值评价待检测图像中特征点的分布情况。实验结果表明,改进ORB算法特征点的分布较为均匀,输出特征点重叠数量较少,执行时间较短。

Taking mobile robot visual navigation as the application background,an improved ORB algorithm is proposed to solve the problems of feature points unevenly distributing and too many redundant features in visual SLAM.Firstly,the scale-space pyramid of each image is meshed to increase the scale information.Secondly,feature points are detected,using improved FAST corner points adaptive extraction and setting region of interest.Thirdly,non-maximum suppression method is used to suppress the output low threshold feature points.Finally,feature points variance values based on region image is used to evaluate of distribution feature points in images.Experiments verify that the improved ORB algorithm has more uniform distribution,fewer output overlapping feature points and shorter run time.