Geodetski list, Vol. 77 (100) No. 3, 2023.
Pregledni rad
SLAM and Geodesy
Antun Jakopec
orcid.org/0009-0007-9082-2823
; SLAM Geodezija d.o.o., Varaždin, Hrvatska
Loris Redovniković
; Geodetski fakultet Sveučilišta u Zagrebu, Zagreb, Hrvatska
Đuro Barković
orcid.org/0000-0003-3382-253X
; Geodetski fakultet Sveučilišta u Zagrebu, Zagreb, Hrvatska
Mladen Zrinjski
orcid.org/0000-0003-0834-6009
; Geodetski fakultet Sveučilišta u Zagrebu, Zagreb, Hrvatska
Sažetak
Simultaneous Localization and Mapping (SLAM) is a technique in robotics, mainly used in mobile robots. The fundamental task of SLAM is to interact with the environment through various sensors on a robot or other platform, while simultaneously determining the position and generating a cartographic representation, i.e., a model of the observed space. Since its initial introduction in 1986, SLAM has become a major topic in the world of robotics, and it is fair to say that not a day goes by without something being reported about it. Beyond robotics, experts from different fields also use SLAM, mainly for two different purposes, depending on what they are interested in, whether it is generating a model of the observed space or determining the position of robots and other platforms. Over time, various forms of SLAM have emerged, including Extended Kalman Filter SLAM, Particle Filter based SLAM, and Graph-Based SLAM. Several studies have shown that Graph-Based SLAM consistently produces better results. Successful implementations of SLAM depend on several factors, with the choice of appropriate sensors and the type of the environment being of paramount importance. The goal of this paper is to provide a brief insight into the definition of SLAM, its types, advantages and limitations, practical implementations, and to highlight the close connection between SLAM and geodesy.
Ključne riječi
SLAM; geodesy; Extended Kalman Filter; graph; sensors
Hrčak ID:
314129
URI
Datum izdavanja:
30.9.2023.
Posjeta: 211 *