基于李群的视觉/惯性组合导航算法

Visual/inertial integrated navigation algorithm on Lie groups

为了进一步研究高性能导航,提出基于李群的视觉惯性组合导航算法:利用单目相机对全局地图上一定数量的3维固定路标进行跟踪观测,并采用多速率融合方法解决视觉惯导工作频率不一致问题;构建视觉惯性紧耦合模型,然后采用基于李群的无迹卡尔曼滤波方法和不变扩展卡尔曼滤波方法对观测信息与惯导数据进行融合并相互比较。通过数值仿真将2种滤波结果与采用传统无迹卡尔曼滤波算法的滤波结果进行对比,结果表明2种滤波方法都可以有效抑制系统误差,提升导航精度。

In order to further study on the efficient navigation,the paper proposed visual/inertial integrated navigation algorithm based on Lie groups:the monocular camera was used to track and observe a certain number of 3 D fixed landmarks on the global map,and the multi-rate fusion method was used to solve the inconsistency of the visual and inertial working frequency;the visual and inertia tight coupling model was constructed,then two filtering methods of unscented Kalman filtering method on Lie groups and invariant extended Kalman filtering method were used to fuse and compare between the observed information with the INS data.Finally,the numerical simulation was used to compare the two different kinds of filtering results with those using the traditional unscented Kalman filtering algorithm,and result showed that the two methods could both effectively suppress system errors and improve the navigation accuracy.