Authors: Jae Hyung Jung
Year: 2022
- Merge Gaussian Mixture (GM) on Lie Groups, Object SLAM with symmetric objects
- Gaussian Mixture can be used to model multiple hypothesis
- How to define GM on Lie Groups? Proposes to use the midway point technique
- We note
$X \in G$ an element in a Lie Group - Gaussian distribution on Lie Groups:
$X = \exp(-\xi^\wedge)\hat{X}$ with$\hat{X}$ the mean and$\xi \sim N(0,P)$ , we note it$X \sim N_G(\hat{X}, P)$ - GM on lie Group:
$\sum w_i N_G(\hat{X}_i, P_i)$ with$\sum w_i = 1$
Gaussian Mixture Merge:
- IV - A : Express a given Gaussian mixture distribution N_G(\hat{X}_i, P_i) but in the lie algebra of a common point
$\hat{X}_c$ - IV - B : Compute a midway point
$\hat{X}_f = (\hat{X}_2\hat{X}_1^{-1})^{w_2}\hat{X}_1$ , express and merge the two gaussian distribution$X_1$ and$X_2$ on the Lie Algebra of the midway point - V : Numerical experiments with
$SO(3)$
SLAM problem:
- promising example with SLAM with a symmetric object
- Impelement the Gaussian Mixture Invariant Extended Kalman Filter GM-IEKF