From 22dc81cbbb855ea4f122efd5add93e9933c99561 Mon Sep 17 00:00:00 2001 From: hnqiu Date: Tue, 7 Sep 2021 16:46:41 +1000 Subject: [PATCH] Fix: duplicate text & a typo in lieGroup.tex --- chapters/lieGroup.tex | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/chapters/lieGroup.tex b/chapters/lieGroup.tex index 9f81060..b98a635 100644 --- a/chapters/lieGroup.tex +++ b/chapters/lieGroup.tex @@ -387,8 +387,7 @@ \subsection{Derivative on $\mathrm{SO}(3)$} \mathop {\min }\limits_{\mathbf{T}} J(\mathbf{T} ) = \sum_{i=1}^{N} \left\| {\mathbf{z}_i - \mathbf{Tp}_i} \right\|^2_2. \end{equation} -Because of the noise, the real observed data is not absolutely the same as the one we computed from the observation model, so we can calculate the error of predicted observation with the real one: -To solve such an optimized problem (which is a least square problem), we need to calculate the derivative of $J$ by $\mathbf{T}$. We leave the least square problem to the next section. Here we just want to clarify that we normally have some functions that have rotations or transforms as their variables. We have to adjust those rotations or transforms to find a better/best estimation. But, as we mentioned before, since $\mathrm{SO}(3)$ and $\mathrm{SE}(3)$ do not have a well-defined addition (they are just groups), so the derivatives cannot be defined in their common form. If we treat the $\mathbf{R}$ or $\mathbf{T}$ as common matrices, we have to introduce the constraints into our optimization. +To solve such an optimization problem (which is a least square problem), we need to calculate the derivative of $J$ by $\mathbf{T}$. We leave the least square problem to the next section. Here we just want to clarify that we normally have some functions that have rotations or transforms as their variables. We have to adjust those rotations or transforms to find a better/best estimation. But, as we mentioned before, since $\mathrm{SO}(3)$ and $\mathrm{SE}(3)$ do not have a well-defined addition (they are just groups), so the derivatives cannot be defined in their common form. If we treat the $\mathbf{R}$ or $\mathbf{T}$ as common matrices, we have to introduce the constraints into our optimization. However, from the perspective of Lie algebra, since it consists of vectors, it has a good addition operation. Therefore, there are two ways to solve the problem of derivation using Lie algebra: