Vanilla ICP

Usage

You can construct a new instance of Vanilla ICP with icp::ICP::from_method("vanilla").

Description

The vanilla algorithm for ICP will match the point-cloud centers exactly and then iterate until an optimal rotation has been found.

1. Matching Step: match closest points.

   Sources:
   

   • https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4767965
   • https://arxiv.org/pdf/2206.06435.pdf
   • https://web.archive.org/web/20220615080318/https://www.cs.technion.ac.il/~cs236329/tutorials/ICP.pdf
   • https://en.wikipedia.org/wiki/Iterative_closest_point
   • https://courses.cs.duke.edu/spring07/cps296.2/scribe_notes/lecture24.pdf

2. Transformation Step: determine optimal transformation.

   The translation vector is determined by the displacement between the centroids of both point clouds. The rotation matrix is calculated via singular value decomposition.

   Sources:
   

   • https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4767965
   • https://courses.cs.duke.edu/spring07/cps296.2/scribe_notes/lecture24.pdf

Read ICP Sources for a list of all resources used in this project. This page was automatically generated from vanilla.cpp with icp_doc_builder.py.