A Comparison of Modern General-Purpose Visual SLAM Approaches

Merzlyakov, A. S.; Macenski, Steve

doi:10.1109/iros51168.2021.9636615

Cited by 32 publications

(18 citation statements)

References 14 publications

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“…However, authors in [76] demonstrated significant errors results of ORB-SLAM3 online performance. In [77], the algorithm obtained a good performance, but failed to process all the sequences, and obtained inaccurate estimates in outdoor sequences.…”

Section: Orb-slam3 (2020)mentioning

confidence: 99%

A Comprehensive Survey of Visual SLAM Algorithms

et al. 2022

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Simultaneous localization and mapping (SLAM) techniques are widely researched, since they allow the simultaneous creation of a map and the sensors’ pose estimation in an unknown environment. Visual-based SLAM techniques play a significant role in this field, as they are based on a low-cost and small sensor system, which guarantees those advantages compared to other sensor-based SLAM techniques. The literature presents different approaches and methods to implement visual-based SLAM systems. Among this variety of publications, a beginner in this domain may find problems with identifying and analyzing the main algorithms and selecting the most appropriate one according to his or her project constraints. Therefore, we present the three main visual-based SLAM approaches (visual-only, visual-inertial, and RGB-D SLAM), providing a review of the main algorithms of each approach through diagrams and flowcharts, and highlighting the main advantages and disadvantages of each technique. Furthermore, we propose six criteria that ease the SLAM algorithm’s analysis and consider both the software and hardware levels. In addition, we present some major issues and future directions on visual-SLAM field, and provide a general overview of some of the existing benchmark datasets. This work aims to be the first step for those initiating a SLAM project to have a good perspective of SLAM techniques’ main elements and characteristics.

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Section: Orb-slam3 (2020)mentioning

confidence: 99%

A Comprehensive Survey of Visual SLAM Algorithms

et al. 2022

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“…There are various papers describing the solution to the SLAM problem, both for a single robot and for a swarm. For example, in the works [2][3][4], the single-agent algorithms that are popular at the time of these works are listed and compared. There are algorithms that were directly developed as multi-agent algorithms.…”

Section: Swarmmentioning

confidence: 99%

Scalable Algorithms for Simultaneous Mapping and Localization of Mobile Robot Swarms

Filatov¹,

Krinkin²

2023

Autonomous Mobile Mapping Robots

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The chapter is devoted to the development of scalable algorithms for multi-agent solution of the SLAM problem. These algorithms are applicable to robots with limited computational resources, having limited computational power and memory, small spatial size, and power from a portable battery. To simplify the description, only robots equipped with LIDAR are considered. The main focus is as follows: a scalable multi-agent SLAM algorithm based on Dempster-Shafer theory; an algorithm for filtering two-dimensional laser scans to free up computational resources; evaluation of the accuracy of the map and trajectory constructed by the multi-agent algorithm; performance evaluation on resource-limited computing devices.

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Section: Introductionmentioning

confidence: 99%

“…Besides, visual SLAM methods have now received a great attention. A comparison of modern general-purpose visual SLAMs can be found in Merzlyakov and Macenski (2021). Next, a strong navigation system can be seen in Macenski et al (2020), its previous and current versions are now popularly used both in the research and real applications.…”

Section: Introductionmentioning

confidence: 99%

An efficient approach for the elevator button manipulation using the visual-based self-driving mobile manipulator

Toan

Jeong²,

Jo³

2022

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Purpose Because mobile manipulators are unable to climb stairs, the elevator operation is a crucial capacity to help those kinds of robot systems work in modern multifloor buildings. Here, the elevator button manipulation is considered as an efficient approach to fulfill that requirement. Previously, some studies presented elevator button recognition algorithms while some others designed schemes for the button manipulation work. However, the mobile robot, the manipulator and the camera in their robot systems are asynchronous. Besides, the time-consuming calibration for the camera is inevitable, especially in changeable environments. This paper aims to present an alternative method for the elevator button manipulation to overcome mentioned shortcomings. Design/methodology/approach In this paper, the elevator button manipulation is conducted by using the visual-based self-driving mobile manipulator in which the autonomous mobile robot, the manipulator and the camera cooperate more efficiently. Namely, the mobile robot does not need to be located exactly in front of the elevator panel as the manipulator has the ability to adjust the initial frame of the camera based on the system kinematic synchronization. In addition, the proposed method does not require the real world coordinates of elevator buttons, but uniquely using their pixel positions. By doing this, not only is the projection from two-dimensional pixel coordinates to three-dimensional (3D) real world coordinates unnecessary, but also the calibration of the camera is not required. Findings The proposed method is experimentally verified by using a visual-based self-driving mobile manipulator. This robotic system is the integration of an autonomous mobile robot, a manipulator and a camera mounted on the end-effector of the manipulator. Research limitations/implications Because the surface of the elevator button panel is usually mirror-like, the elevator button detection is easily affected by the glare and the brightness of the environmental light condition. Practical implications This robot system can be used for the goods delivery or the patrol in modern multifloor buildings. Originality/value This paper includes three new features: simultaneously detecting and manipulating elevator buttons without the projection from pixel coordinates to 3D real world coordinates, a kinematic synchronization to help the robot system eliminate accumulated errors and a safe human-like elevator button manipulation.

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A Comparison of Modern General-Purpose Visual SLAM Approaches

Cited by 32 publications

References 14 publications

A Comprehensive Survey of Visual SLAM Algorithms

A Comprehensive Survey of Visual SLAM Algorithms

Scalable Algorithms for Simultaneous Mapping and Localization of Mobile Robot Swarms

An efficient approach for the elevator button manipulation using the visual-based self-driving mobile manipulator

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