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Recent Trends and Advances in SLAM with Multi-Robot Systems
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Recent Trends and Advances in SLAM with Multi-Robot Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 14232

Special Issue Editors

Prof. Dr. Heoncheol Lee

E-Mail Website
Guest Editor
Department of IT Convergence Engineering, School of Electronic Engineering, Kumoh National Institute of Technology, Gyeongbuk 39177, Republic of Korea
Interests: SLAM; autonomous navigation; multi-robot systems; deep learning for anomaly detection; FPGA-based algorithm acceleration
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Seunghwan Lee

E-Mail Website
Guest Editor
School of Electronic Engineering, Kumoh National Institute of Technology, Gyeongbuk 39177, Republic of Korea
Interests: multiagent systems; autonomous navigation; SLAM
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Algorithms and frameworks for simultaneous localization and mapping (SLAM) have received attention in recent years because they are fundamental components for implementing autonomous navigation in unmanned vehicles. Especially, SLAM with multi-robot systems (MRSs) (i.e., multi-robot SLAM or cooperative SLAM (C-SLAM)) has also recently received attention because these techniques have many advantages over single-robot systems such as time efficiency and cost reduction in large unknown environments.

This Special Issue aims to provide broad coverage of recent trends and advances in SLAM with MRSs. Both theoretical and practical works as well as review/survey papers in the area are welcome. The topics of interest for this Special Issue include but are not limited to:

  • Algorithms and implementation for multi-robot SLAM;
  • Algorithms and implementation for multi-robot path planning;
  • Algorithms and implementation for multi-robot navigation;
  • Algorithms and implementation for multiple map merging;
  • Algorithms and implementation for multi-robot cooperation;
  • Practical sensor fusion systems for inter-robot recognition;
  • Efficient inter-robot collision avoidance;
  • Efficient inter-robot communication.

Prof. Dr. Heoncheol Lee
Prof. Dr. Seunghwan Lee
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multi-robot systems
  • multi-robot SLAM
  • multi-robot path planning
  • multi-robot navigation
  • multiple map merging
  • multi-robot cooperation
  • inter-robot recognition
  • inter-robot collision avoidance
  • inter-robot communication

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Published Papers (4 papers)

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Research

16 pages, 8686 KiB  
Article
CNN-Based Fault Detection of Scan Matching for Accurate SLAM in Dynamic Environments
by Hyein Jeong and Heoncheol Lee
Sensors 2023, 23(6), 2940; https://doi.org/10.3390/s23062940 - 8 Mar 2023
Cited by 4 | Viewed by 2531
Abstract
This paper proposes a method for CNN-based fault detection of the scan-matching algorithm for accurate SLAM in dynamic environments. When there are dynamic objects in an environment, the environment that is detected by a LiDAR sensor changes. Thus, the scan matching of laser [...] Read more.
This paper proposes a method for CNN-based fault detection of the scan-matching algorithm for accurate SLAM in dynamic environments. When there are dynamic objects in an environment, the environment that is detected by a LiDAR sensor changes. Thus, the scan matching of laser scans is likely to fail. Therefore, a more robust scan-matching algorithm to overcome the faults of scan matching is needed for 2D SLAM. The proposed method first receives raw scan data in an unknown environment and executes ICP (Iterative Closest Points) scan matching of laser scans from a 2D LiDAR. Then, the matched scans are converted into images, which are fed into a CNN model for its training to detect the faults of scan matching. Finally, the trained model detects the faults when new scan data are provided. The training and evaluation are performed in various dynamic environments, taking real-world scenarios into account. Experimental results showed that the proposed method accurately detects the faults of scan matching in every experimental environment. Full article
(This article belongs to the Special Issue Recent Trends and Advances in SLAM with Multi-Robot Systems)
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26 pages, 7956 KiB  
Article
Research on Two-Round Self-Balancing Robot SLAM Based on the Gmapping Algorithm
by Jianwei Zhao, Jinyu Li and Jiaxin Zhou
Sensors 2023, 23(5), 2489; https://doi.org/10.3390/s23052489 - 23 Feb 2023
Cited by 10 | Viewed by 4003
Abstract
Aiming at the inconvenience of inspection and monitoring of coal mine pump room equipment in a narrow and complex environment, this paper proposes and designs a two-wheel self-balancing inspection robot based on laser SLAM. Using SolidWorks, the three-dimensional mechanical structure of the robot [...] Read more.
Aiming at the inconvenience of inspection and monitoring of coal mine pump room equipment in a narrow and complex environment, this paper proposes and designs a two-wheel self-balancing inspection robot based on laser SLAM. Using SolidWorks, the three-dimensional mechanical structure of the robot is designed, and the overall structure of the robot is analyzed by finite element statics. The kinematics model of the two-wheel self-balancing robot was established, and the multi-closed-loop PID controller was used to design the two-wheel self-balancing control algorithm of the robot. The 2D LiDAR-based Gmapping algorithm was used to locate the robot and construct the map. Through the self-balancing test and anti-jamming test, it is verified that the self-balancing algorithm designed in this paper has a certain anti-jamming ability and good robustness. By using Gazebo to build a simulation comparison experiment, it is verified that the selection of the particle number is of great significance for improving the map accuracy. The actual test results show that the constructed map has high accuracy. Full article
(This article belongs to the Special Issue Recent Trends and Advances in SLAM with Multi-Robot Systems)
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14 pages, 5699 KiB  
Article
Multi-Robot Task Scheduling with Ant Colony Optimization in Antarctic Environments
by Seokyoung Kim and Heoncheol Lee
Sensors 2023, 23(2), 751; https://doi.org/10.3390/s23020751 - 9 Jan 2023
Cited by 6 | Viewed by 2664
Abstract
This paper addresses the problem of multi-robot task scheduling in Antarctic environments. There are various algorithms for multi-robot task scheduling, but there is a risk in robot operation when applied in Antarctic environments. This paper proposes a practical multi-robot scheduling method using ant [...] Read more.
This paper addresses the problem of multi-robot task scheduling in Antarctic environments. There are various algorithms for multi-robot task scheduling, but there is a risk in robot operation when applied in Antarctic environments. This paper proposes a practical multi-robot scheduling method using ant colony optimization in Antarctic environments. The proposed method was tested in both simulated and real Antarctic environments, and it was analyzed and compared with other existing algorithms. The improved performance of the proposed method was verified by finding more efficiently scheduled multiple paths with lower costs than the other algorithms. Full article
(This article belongs to the Special Issue Recent Trends and Advances in SLAM with Multi-Robot Systems)
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14 pages, 1569 KiB  
Article
GPU-Accelerated PD-IPM for Real-Time Model Predictive Control in Integrated Missile Guidance and Control Systems
by Sanghyeon Lee, Heoncheol Lee, Yunyoung Kim, Jaehyun Kim and Wonseok Choi
Sensors 2022, 22(12), 4512; https://doi.org/10.3390/s22124512 - 14 Jun 2022
Cited by 14 | Viewed by 3159
Abstract
This paper addresses the problem of real-time model predictive control (MPC) in the integrated guidance and control (IGC) of missile systems. When the primal-dual interior point method (PD-IPM), which is a convex optimization method, is used as an optimization solution for the MPC, [...] Read more.
This paper addresses the problem of real-time model predictive control (MPC) in the integrated guidance and control (IGC) of missile systems. When the primal-dual interior point method (PD-IPM), which is a convex optimization method, is used as an optimization solution for the MPC, the real-time performance of PD-IPM degenerates due to the elevated computation time in checking the Karush–Kuhn–Tucker (KKT) conditions in PD-IPM. This paper proposes a graphics processing unit (GPU)-based method to parallelize and accelerate PD-IPM for real-time MPC. The real-time performance of the proposed method was tested and analyzed on a widely-used embedded system. The comparison results with the conventional PD-IPM and other methods showed that the proposed method improved the real-time performance by reducing the computation time significantly. Full article
(This article belongs to the Special Issue Recent Trends and Advances in SLAM with Multi-Robot Systems)
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