LIRO-SLAM: A Tightly-Coupled LiDAR-Inertial Slam System for Robust UAV Navigation and Mapping in UHV Substations and Converter Stations

Autonomous inspection of substations using Unmanned Aerial Vehicles (UAVs) enhances safety, efficiency, and reliability in power grid maintenance. However, the complex electromagnetic environments and structural characteristics of substations pose significant challenges to UAV localization and mapping. To address these challenges, we present LIRO-SLAM, a tightly-coupled LiDAR-Inertial SLAM system specifically designed for reliable UAV navigation and mapping in substation environments. The core innovation of LIRO-SLAM lies in the deep integration of LiDAR odometry and IMU pre-integration within a graph optimization framework, effectively leveraging the complementary advantages of both sensors to achieve superior robustness and accuracy. Key techniques such as keyframe selection, motion constraint, and IMU bias correction are incorporated to mitigate the impact of IMU noise and drift. Extensive experiments demonstrate that LIRO-SLAM significantly outperforms state-of-the-art SLAM algorithms in terms of accuracy, robustness, and real-time performance. Field tests in real substation environments validate the practicality of our system, where high-precision 3D point cloud maps are constructed for equipment modeling and defect detection. LIROSLAM makes substantial contributions to autonomous substation inspection by enabling reliable UAV localization and mapping in complex environments.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1109/cbase64041.2024.10824643
Primary Topic
Robotics and Sensor-Based Localization
Type
article
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article

LIRO-SLAM: A Tightly-Coupled LiDAR-Inertial Slam System for Robust UAV Navigation and Mapping in UHV Substations and Converter Stations

Teng Fang, Yubo Gao, Biao Zou, Ning Wang et al.
Robotics and Sensor-Based Localization
article

LIRO-SLAM: A Tightly-Coupled LiDAR-Inertial Slam System for Robust UAV Navigation and Mapping in UHV Substations and Converter Stations

Teng Fang, Yubo Gao, Biao Zou, Ning Wang, Xiaokang Zhu, Weiqi Ren
article en

Abstract

Autonomous inspection of substations using Unmanned Aerial Vehicles (UAVs) enhances safety, efficiency, and reliability in power grid maintenance. However, the complex electromagnetic environments and structural characteristics of substations pose significant challenges to UAV localization and mapping. To address these challenges, we present LIRO-SLAM, a tightly-coupled LiDAR-Inertial SLAM system specifically designed for reliable UAV navigation and mapping in substation environments. The core innovation of LIRO-SLAM lies in the deep integration of LiDAR odometry and IMU pre-integration within a graph optimization framework, effectively leveraging the complementary advantages of both sensors to achieve superior robustness and accuracy. Key techniques such as keyframe selection, motion constraint, and IMU bias correction are incorporated to mitigate the impact of IMU noise and drift. Extensive experiments demonstrate that LIRO-SLAM significantly outperforms state-of-the-art SLAM algorithms in terms of accuracy, robustness, and real-time performance. Field tests in real substation environments validate the practicality of our system, where high-precision 3D point cloud maps are constructed for equipment modeling and defect detection. LIROSLAM makes substantial contributions to autonomous substation inspection by enabling reliable UAV localization and mapping in complex environments.

Affordable and clean energy
Openalex Percentile: Top 57%
Robotics and Sensor-Based Localization
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