vio之滤波篇

资料：
Bayesian Filtering: From Kalman Filters to Particle Filters, and Beyond

Optimal State Estimation -Kalman, H infinity, and Nonlinear ApproachesOptimal State Estimation -Kalman, H infinity, and Nonlinear Approaches

3D：
msckf： https://github.com/KumarRobotics/msckf_vio
            网页上有论文链接，整体思路和所有负号表示都与原版msckf保持一致
            https://github.com/chutsu/prototype  
            这个项目还一直在更新 
riekf：https://github.com/jgoppert/iekf_analysis
     paper: https://hal.archives-ouvertes.fr/hal-00494342/document
ukf:  https://github.com/mbrossar/ICRA2018
        https://hal.archives-ouvertes.fr/hal-01588669/document
       在李群上进行处理

R-EKF(right_ekf_3d), FEJ-EKF(f_ekf_3d) and T-EKF(ekf_3d): https://github.com/RomaTeng/EKF-SLAM-on-Manifold

ekfslam、1p-ransac-eks-monoslam：
      https://github.com/JzHuai0108/ekfmonoslam


 2D:
ocekf:   https://github.com/rpng/ocekf-slam

iekf、ukf、ocekf： https://github.com/mbrossar/iekf-slam

文献：
 Indirect Kalman Filter for 3D Attitude Estimation
 以些函数的实现在这里