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Generalized ICP

1. Intro

Combine ICP and point-to-plane ICP into a single probabilistic framework

  • More robust to incorrect correspondence
  • Easier to tune the maximum match distance

2. How it works

Align two point sets in 3D space

  • by minimizing the distance
  • Extends ICP by allowing more general types of correspondaences

3. Standard ICP

image-20230531230520928

4. Point-to-Plane

Update the T calculation process (Line 11)
$$
T \leftarrow \underset{T}{\operatorname{argmin}}\left{\sum_i w_i\left|\eta_i \cdot\left(T \cdot b_i-m_i\right)\right|^2\right}
$$
Taking the surface normal information

5. GICP

Also improved the Line 11

Attaching a probabilistic model

  • Correspondence: computed with Euclidean distance
  • Use of KD-tree and speed up

6. NDT?

NDT represents the entire point cloud as a collection of Gaussian distributions.

  1. divide the 3D space containing the point cloud into a grid of cells
  2. Each cell that contains at least one point is then represented by a Gaussian distribution
  3. iteratively revises the transformation (translation and rotation) to minimize the difference between the two point clouds.