A REVIEW ON AUGMENTED REALITY TRACKING METHODS FOR MAINTENANCE OF ROBOTS

Autor:	Kai Woon Goh, Ye Sheng Koh, Yik Shin Tey, Che Fai Yeong, Eileen Su Lee Ming, Mohd Shahrizal Sunar, Marvin Dares
Rok vydání:	2020
Předmět:	Scope (project management) Human–computer interaction Computer science Scale (chemistry) General Engineering Robot Augmented reality Tracking (education)
Zdroj:	Jurnal Teknologi. 83:37-43
ISSN:	2180-3722 0127-9696
Popis:	Augmented reality (AR) in maintenance is a broad subject with many nuances when it comes to their implementation. The applications of these systems range from maintenance of large-scale assets such as buildings to smaller scale assets such as robots. Applications of AR in maintenance typically serves as a visual guide to assist users in diagnosis or steps needed to be performed for maintenance. In this paper, the tracking methods utilized in AR-based maintenance for robots are qualitatively evaluated. The reviewed works in this paper are between the years of 2015 to 2020 to ensure that the AR tracking methods are relatively state of the art. It is found that applications of AR-based maintenance for robots are uncommon in the scope defined in this research especially in the industrial environment as most reviewed works are conducted in a laboratory setting. In addition to that, it is found that marker-based tracking methods are commonly utilized in these applications.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9151d7b40f805133d94bf778724d842a https://doi.org/10.11113/jurnalteknologi.v83.14907 Zobrazit plný text záznamu