Please use this identifier to cite or link to this item:
Title: A novel map-merging technique for occupancy grid-based maps using multiple robots: a semantic approach
Authors: Durdu, Akif
Korkmaz, Mehmet
Keywords: Bilgisayar Bilimleri, Yapay Zeka
Bilgisayar Bilimleri, Sibernitik
Bilgisayar Bilimleri, Donanım ve Mimari
Bilgisayar Bilimleri, Bilgi Sistemleri
Bilgisayar Bilimleri, Yazılım Mühendisliği
Bilgisayar Bilimleri, Teori ve Metotlar
Mühendislik, Elektrik ve Elektronik
Issue Date: 2019
Abstract: Map merging is a noteworthy phenomenon for cases such as search and rescue and disaster areas in which the duration is quite significant when gathering information about an environment. It is obvious that the total mapping time decreases if the number of agents (robots) increases. However, the use of multiple agents leads to problems such as task allocation schemes and the fusing of local maps. Examining the present methods, it is generally observed that the common features of local maps have been found and the global map is formed by obtaining related transformation between local maps. However, such implementations may be risky when local maps have symmetrical areas. Hence, a novel and semantic approach has been developed to solve this problem. The developed method counts on the reliability level of feature points. If relevant feature points are trusted, local maps are merged according to the best point or points. The simulation results from a robot operating system and a real-time experiment support the proposed method’s efficiency, and mapping can be performed even for environments that have symmetrical similar parts and the task time can thus be reduced.
ISSN: 1300-0632
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

Files in This Item:
File SizeFormat 
5940f723-4b2c-4e31-acf8-2056fa3e4087.pdf10.32 MBAdobe PDFView/Open
Show full item record

CORE Recommender


checked on Feb 4, 2023


checked on Jan 30, 2023

Page view(s)

checked on Jan 30, 2023


checked on Jan 30, 2023

Google ScholarTM



Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.