An Extension of the ICP Algorithm for Modeling Nonrigid Objects with Mobile Robots
Abstract
The iterative closest point (ICP) algorithm [2] is a popular method for modeling 3D objects from range data. The classical ICP algorithm rests on a rigid surface assumption. Building on recent work on nonrigid object models [5; 16; 9], this paper presents an ICP algorithm capable of modeling nonrigid objects, where individual scans may be subject to local deformations. We describe an integrated mathematical framework for simultaneously registering scans and recovering the surface configuration. To tackle the resulting high-dimensional optimization problems, we introduce a hierarchical method that first matches a coarse skeleton of scan points, then adapts local scan patches. The approach is implemented for a mobile robot capable of acquiring 3D models of objects.
Cite
Text
Hähnel et al. "An Extension of the ICP Algorithm for Modeling Nonrigid Objects with Mobile Robots." International Joint Conference on Artificial Intelligence, 2003.Markdown
[Hähnel et al. "An Extension of the ICP Algorithm for Modeling Nonrigid Objects with Mobile Robots." International Joint Conference on Artificial Intelligence, 2003.](https://mlanthology.org/ijcai/2003/hahnel2003ijcai-extension/)BibTeX
@inproceedings{hahnel2003ijcai-extension,
title = {{An Extension of the ICP Algorithm for Modeling Nonrigid Objects with Mobile Robots}},
author = {Hähnel, Dirk and Thrun, Sebastian and Burgard, Wolfram},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2003},
pages = {915-920},
url = {https://mlanthology.org/ijcai/2003/hahnel2003ijcai-extension/}
}