Pokročilé metody pro zpracování a zjednodušení cloudu bodů

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F20%3A39917254" target="_blank" >RIV/00216275:25530/20:39917254 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/2076-3417/10/10/3340/pdf" target="_blank" >https://www.mdpi.com/2076-3417/10/10/3340/pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/app10103340" target="_blank" >10.3390/app10103340</a>

Result language

angličtina

Original language name

Pokročilé metody pro zpracování a zjednodušení cloudu bodů

Original language description

Nowadays, mobile robot exploration needs a rangefinder to obtain a large number of measurement points to achieve a detailed and precise description of a surrounding area and objects, which is called the point cloud. However, a single point cloud scan does not cover the whole area, so multiple point cloud scans must be acquired and compared together to find the right matching between them in a process called registration method. This method requires further processing and places high demands on memory consumption, especially for small embedded devices in mobile robots. This paper describes a novel method to reduce the burden of processing for multiple point cloud scans. We introduce our approach to preprocess an input point cloud in order to detect planar surfaces, simplify space description, fill gaps in point clouds, and get important space features. All of these processes are achieved by applying advanced image processing methods in combination with the quantization of physical space points. The results show the reliability of our approach to detect close parallel walls with suitable parameter settings. More importantly, planar surface detection shows a 99% decrease in necessary descriptive points almost in all cases. This proposed approach is verified on the real indoor point clouds.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20204 - Robotics and automatic control

Project

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Continuities

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Applied Science - Basel

ISSN

2076-3417

e-ISSN

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Volume of the periodical

10

Issue of the periodical within the volume

10

Country of publishing house

CH - SWITZERLAND

Number of pages

26

Pages from-to

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UT code for WoS article

000541440000001

EID of the result in the Scopus database

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