刘振彬,危双丰,庞帆,师现杰

• 1:北京建筑大学测绘与城市空间信息学院
• 2:建筑遗产精细重构与健康监测北京市重点实验室
• 3:自然资源部城市空间信息重点实验室

摘要(Abstract)：

针对目前纯视觉SLAM系统易受环境光照、纹理以及动态环境等场景的影响,其中单目SLAM系统还存在着初始化尺度模糊的问题,该文使用一种改进的非线性优化单目惯导SLAM方案,有效解决了单目SLAM系统中存在的尺度模糊问题。基于目前单目视觉和IMU融合性能最好的VINS-mono系统,改进初始化方案,增加了加速度bias偏差的初始化,使其能够适用于低成本的IMU传感器;借鉴ORB-SLAM方案,将基于ORB特征点法的前端应用于VINS-mono方案中,结合改进后的初始化方案,实现了较高精度的实时定位与稀疏地图重建。通过在EuRoc数据集中不同场景下的实验与分析,证明了改进后的VINS-mono方案相比之前的精度和鲁棒性都得到了提高。

关键词(KeyWords)： 非线性优化;IMU;单目相机;状态估计;SLAM

Abstract:

Keywords:

基金项目(Foundation): 北京建筑大学市属高校基本科研业务费专项资金资助项目(X18229);; 促进高校内涵发展定额项目(PG2019061,PG2019065)

作者(Author): 刘振彬,危双丰,庞帆,师现杰

DOI: 10.16251/j.cnki.1009-2307.2020.09.014

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