Rejestracja chmur punktów: komponenty systemu

pol Article in Polish DOI: 10.14313/PAR_223/19

send Tomasz Kornuta *, Marta Jolanta Łępicka ** * IBM Research - Almaden, 650 Harry Rd, San Jose, CA 95120, Stany Zjednoczone ** Politechnika Warszawska, Instytut Automatyki i Informatyki Stosowanej

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Streszczenie

Dwuczęściowy artykuł dotyczy problemu rejestracji obrazów RGB-D. W robotyce problem ten znany jest pod pojęciem V-SLAM (ang. Visual Simultaneous Localization and Mapping). W poniższej, pierwszej części artykułu omówiono pokrótce główne komponenty typowego systemu rejestracji, a następnie zawężono uwagę do algorytmu ICP (ang. Iterative Closest Point), służącego do wzajemnej rejestracji chmur punktów. W drugiej części artykułu uwagę skupiono na asocjacji chmur punktów, różnego rodzaju atrybutach punktów, które mogą być wykorzystane podczas znajdowania  dopasowań oraz szeregu metryk operujących na tych atrybutach. Pokrótce omówiono zastosowaną metodykę badań, zaprezentowano eksperymenty mające na celu porównanie wybranych odmian algorytmu ICP oraz omówiono otrzymane wyniki.

Słowa kluczowe

chmura punktów, ICP, obraz RGB-D, rejestracja, V-SLAM, wzajemne łączenie

Registration of RGB-D Images: Components of the System

Abstract

The two-part article focuses on the problem of registration of RGB-D images, a problem that in the robotics domain is known as Visual Simultaneous Localization and Mapping, or V-SLAM in short. The following, first part of the article presents a bird’s eye view on the main components of V-SLAM systems and focuses on the ICP (Iterative Closest Point), an algorithm for a pairwise registration of point clouds. In the second part we present different types of attributes of points that can be used during the association step along with different metrics that operate on those attributes and that can be employed during the registration. We also describe the methodology used in the conducted experiments and discuss the results of comparison of selected flavours of ICP.

Keywords

ICP, pairwise registration, point cloud, RGB-D image, V-SLAM

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