In 1988, the concept of simultaneous localization and mapping (SLAM) was proposed. ORB-SLAM is a monocular real-time SLAM system based on features. It fundamentally continues the algorithmic structure of Parallel Tracking And Mapping (PTAM), improving the majority of its components, and so has a larger field of vision in terms of variance, with improved resilience and bundle adjustment (BA) efficiency. Artificial intelligence and machine learning have advanced significantly since the inception of SLMA. Furthermore, in the presence of extreme motion clutter, ORB-SLAM has significantly enhanced loop-back detection and relocation. As a result, it is evident that SLAM and ORB-SLAM approaches are highly worth investigating and expanding. This document presents a detailed chronological account of SLAM development and compares the features of several versions of ORB-SLAM enhancements. It compares two existing ORB-SLAM3 enhancement strategies in dynamic situations in particular. In addition, the article includes a perspective and predictions for the future and later stages.

Topics
Artificial intelligence, Machine learning
1.
Dai
,
Y.
,
Wu
,
J.
, &
Wang
,
D.
,
A Review of Common Techniques for Visual Simultaneous Localization and Mapping
.
J. Robot.
2023
,
1
–
21
(
2023
).
https://doi.org/10.1155/2023/8872822
Google Scholar
Crossref
Search ADS
 
2.
IEEE Robotics and Automation Conference
(
San Francisco
,
California
)
3.
S.
Borthwick
 and
H.
Durrant-Whyte
, “
Dynamic localisation of autonomous guided vehicles
,” in
Proceedings of the 1994 IEEE International Conference on MFI’94. Multisensor Fusion and Integration for Intelligent Systems
, pp.
92
–
97
,
IEEE, Las Vegas
,
NV, USA
, October
1994
.
https://doi.org/10.1109/MFI.1994.398452
Google Scholar
Crossref
Search ADS
 
4.
H.
Durrant-Whyte
,
I.
Bailey
, "
Simultaneous Localization and Mapping: Part I
,"
IEEE Transactions on Robotics and Automation
, vol.
15
, no.
2
, pp.
329
–
341
,
1999
.
Google Scholar
 
5.
Chen
,
K.
,
Chen
,
J.
,
Lu
,
H.
, &
Hu
,
S.
 (
2002
).
Real-Time Visual SLAM with Points and Line Segments
.
IEEE Transactions on Pattern Analysis and Machine Intelligence
,
24
(
8
),
1167
–
1179
.
Google Scholar
 
6.
J.
Chen
,
H.
Dissanayake
, "
Simultaneous Localization and Mapping using a Single Camera and Laser Range Finder
,"
International Journal of Robotics Research
, vol.
24
, no.
4
, pp.
307
–
319
,
2005
.
Google Scholar
Crossref
Search ADS
 
7.
P.
Davison
,
J.
Murray
, "
Monocular Visual Odometry
,"
International Journal of Computer Vision
, vol.
70
, no.
1
, pp.
99
–
118
,
2007
.
Google Scholar
 
8.
H.
Durrant-Whyte
,
I.
Bailey
, "
EKF-SLAM: A Practical Implementation
,"
IEEE Transactions on Robotics
, vol.
23
, no.
6
, pp.
1352
–
1367
,
2007
.
Google Scholar
 
9.
F.
Frostig
,
T.
Kanade
, "
Real-Time Visual Odometry
,"
International Journal of Computer Vision
, vol.
90
, no.
2
, pp.
139
–
154
,
2010
.
Google Scholar
 
10.
R.
Mur-Artal
,
J. D.
Tardós
, "
ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras
,"
IEEE Transactions on Robotics
, vol.
33
, no.
5
, pp.
1255
–
1262
,
2017
.
https://doi.org/10.1109/TRO.2017.2705103
Google Scholar
Crossref
Search ADS
 
11.
García-Fidalgo
,
J.
,
Martínez-Sánchez
,
A.
, &
Tardós
,
J. D.
 (
2020
).
ORB-SLAM3: An Accurate, Scalable, and Robust Monocular, Stereo and RGB-D SLAM System
.
IEEE Transactions on Robotics.
Google Scholar
 
12.
Y.
Wang
,
X.
Li
,
S.
Li
,
Y.
Li
,
Y.
Liu
, "
S-LAM: A Deep Learning-Based SLAM System
,"
IEEE Transactions on Robotics
, vol.
37
, no.
2
, pp.
191
–
206
,
2021
.
Google Scholar
 
13.
Theodorou
,
C.
,
Velisavljevic
,
V.
 &
Dyo
,
V.
Visual SLAM for Dynamic Environments Based on Object Detection and Optical Flow for Dynamic Object Removal
.
Sensors
22
,
7553
(
2022
).
https://doi.org/10.3390/s22197553
Google Scholar
Crossref
Search ADS
PubMed
 
14.
Li
,
J.
 et al.
The Method of Static Semantic Map Construction Based on Instance Segmentation and Dynamic Point Elimination
.
Electronics
10
,
1883
(
2021
).
https://doi.org/10.3390/electronics10161883
Google Scholar
Crossref
Search ADS
 
This content is only available via PDF.
©2023 Authors. Published by AIP Publishing.
2023
Author(s)
You do not currently have access to this content.