ICP_algorithm

Iterative Closest Point algorithm for fine alignment of point clouds

Iterative Closest Point Algorithm

Comparison of a few Iterative closest point algorithms and their implementation.

• Introduction

• Prerequisites

• Installation

  • Manually

• Usage

• Note

• References

• License

Introduction

This file contains the implementaion of ICP algorithm which finds the fine alignment transformation matrix for two given input point cloud files along with a heuristic, which is a coarse transformation matrix.

Prerequisites

Make sure to have:

• CMake (installation guide)

Installation

Manually

• Create a build directory and move into it

sh$ mkdir build
sh$ cd build

• Generate the Makefile with CMake

sh$ build/cmake ..

• Generate the binary file runfile

sh$ build/make

• Run the compiled file

sh$ build/./runfile

Usage

Video showing the visualisation of ICP algorithm in action

Note

I'm adding some of the my personal notes and findings about this topic

• pcl has GeneralisedICP, NonLinearICP and ICP.
  • ICP algorithm transformation is estimated based on Singular Value Decomposition (SVD)
  • ICP_NL is an ICP variant that uses Levenberg-Marquardt optimization backend. The resultant transformation is optimized as a quaternion.
  • Generalised_ICP is based on this paper In this paper authors have combined the the Iterative Closest Point (’ICP’) and ‘point-to-plane ICP‘ algorithms into a single probabilistic framework.

References

• ICP algorithm of PCL(Documentation)
• formating reference of this readme.md referred from yassram

License

MIT License

Copyright (c) 2020 yassir RAMDANI

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