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Review
A Review of Simultaneous Localization and Mapping for the Robotic-Based Nondestructive Evaluation of Infrastructures
Sensors, v 25(3), 712
24 Jan 2025
PMID: 39943350
Featured in Collection : Research Supported by Drexel Libraries' OA Programs
Abstract
The maturity of simultaneous localization and mapping (SLAM) methods has now reached a significant level that motivates in-depth and problem-specific reviews. The focus of this study is to investigate the evolution of vision-based, LiDAR-based, and a combination of these methods and evaluate their performance in enclosed and GPS-denied (EGD) conditions for infrastructure inspection. This paper categorizes and analyzes the SLAM methods in detail, considering the sensor fusion type and chronological order. The paper analyzes the performance of eleven open-source SLAM solutions, containing two visual (VINS-Mono, ORB-SLAM 2), eight LiDAR-based (LIO-SAM, Fast-LIO 2, SC-Fast-LIO 2, LeGO-LOAM, SC-LeGO-LOAM A-LOAM, LINS, F-LOAM) and one combination of the LiDAR and vision-based method (LVI-SAM). The benchmarking section analyzes accuracy and computational resource consumption using our collected dataset and a test dataset. According to the results, LiDAR-based methods performed well under EGD conditions. Contrary to common presumptions, some vision-based methods demonstrate acceptable performance in EGD environments. Additionally, combining vision-based techniques with LiDAR-based methods demonstrates superior performance compared to either vision-based or LiDAR-based methods individually.
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Details
- Title
- A Review of Simultaneous Localization and Mapping for the Robotic-Based Nondestructive Evaluation of Infrastructures
- Creators
- Ali Ghadimzadeh Alamdari - Drexel UniversityFarzad Azizi Zade - Ferdowsi University of MashhadArvin Ebrahimkhanlou (Corresponding Author) - Drexel University, Mechanical Engineering and Mechanics
- Publication Details
- Sensors, v 25(3), 712
- Publisher
- MDPI
- Number of pages
- 68
- Grant note
- Carleone Faculty Award of the College of Engineering at Drexel University
This research has been supported by the Carleone Faculty Award of the College of Engineering at Drexel University.
- Resource Type
- Review
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering; Mechanical Engineering and Mechanics
- Web of Science ID
- WOS:001419645700001
- Scopus ID
- 2-s2.0-85217737146
- Other Identifier
- 991022019919704721
UN Sustainable Development Goals (SDGs)
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Chemistry, Analytical
- Engineering, Electrical & Electronic
- Instruments & Instrumentation