A Survey of LiDAR-Based 3D SLAM in Indoor Degraded Scenarios

This review paper investigates LiDAR odometry technologies adapted for indoor environments. Localization challenges arise primarily from reduced environmental constraints, particularly in confined spaces like narrow corridors or tunnels where homogeneous conditions make it challenging to discern the robot's position from LiDAR data. The paper provides a comprehensive analysis of algorithms and methodologies aimed at enhancing the robustness and precision of LiDAR odometry in these complex scenarios. It also explores the synergistic combination of LiDAR with other sensors, such as cameras and Inertial Measurement Units (IMUs), to refine the SLAM process. Moreover, the paper highlights recent progress in data processing techniques, with a specific emphasis on LiDAR intensity processing, which is crucial for accurate indoor navigation. In conclusion, the paper identifies current limitations and outlines a path for future research, emphasizing the need for the development of adaptive, intelligent systems that can reliably operate across various indoor environments.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/icftic64248.2024.10912938
Citations
1
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
1.30
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article

A Survey of LiDAR-Based 3D SLAM in Indoor Degraded Scenarios

Bin Wu, Yongle Zou, Xianrong Wan, Peipei Meng
1 citations
Robotics and Sensor-Based Localization
1.30
article

A Survey of LiDAR-Based 3D SLAM in Indoor Degraded Scenarios

Bin Wu, Yongle Zou, Xianrong Wan, Peipei Meng
article en
1 citations

Abstract

This review paper investigates LiDAR odometry technologies adapted for indoor environments. Localization challenges arise primarily from reduced environmental constraints, particularly in confined spaces like narrow corridors or tunnels where homogeneous conditions make it challenging to discern the robot's position from LiDAR data. The paper provides a comprehensive analysis of algorithms and methodologies aimed at enhancing the robustness and precision of LiDAR odometry in these complex scenarios. It also explores the synergistic combination of LiDAR with other sensors, such as cameras and Inertial Measurement Units (IMUs), to refine the SLAM process. Moreover, the paper highlights recent progress in data processing techniques, with a specific emphasis on LiDAR intensity processing, which is crucial for accurate indoor navigation. In conclusion, the paper identifies current limitations and outlines a path for future research, emphasizing the need for the development of adaptive, intelligent systems that can reliably operate across various indoor environments.

Wuhan University of Technology (CN)
Climate action
Openalex Percentile: Top 10%
Robotics and Sensor-Based Localization
1.30
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