An Improved SLAM Algorithm for Substation Inspection Robots Based on 3D Lidar and Visual Information Fusion
Current substation inspection robots mainly use Lidar as a sensor for localization and map building. However, laser SLAM has the problem of localization error in scenes with similar and missing environmental structural features, and environmental maps built by laser SLAM provide more single-road inf...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/11/2797 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849330641409146880 |
|---|---|
| author | Yicen Liu Songhai Fan |
| author_facet | Yicen Liu Songhai Fan |
| author_sort | Yicen Liu |
| collection | DOAJ |
| description | Current substation inspection robots mainly use Lidar as a sensor for localization and map building. However, laser SLAM has the problem of localization error in scenes with similar and missing environmental structural features, and environmental maps built by laser SLAM provide more single-road information for inspection robot navigation, which is not conducive to the judgment of the road scene. For this reason, in this paper, 3D Lidar information and visual information are fused to create a SLAM algorithm applicable to substation inspection robots to solve the above laser SLAM localization error problem and improve the algorithm’s localization accuracy. First, in order to recover the scalability of monocular visual localization, the algorithm in this paper utilizes 3D Lidar information and visual information to calculate the true position of image feature points in space. Second, the laser position and visual position are utilized with interpolation to correct the point cloud distortion caused by the motion of the Lidar. Then, a position-adaptive selection algorithm is designed to use visual position instead of laser inter-frame position in some special regions to improve the robustness of the algorithm. Finally, a color laser point cloud map of the substation is constructed to provide more road environment information for the navigation of the inspection robot. The experimental results show that the localization accuracy and map-building effect of the VO-Lidar SLAM algorithm designed in this paper are better than the current laser SLAM algorithm and verify the applicability of the color laser point cloud map constructed by this algorithm in substation environments. |
| format | Article |
| id | doaj-art-3229dc552f604bacbc1c7b87f6c8354c |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-3229dc552f604bacbc1c7b87f6c8354c2025-08-20T03:46:50ZengMDPI AGEnergies1996-10732025-05-011811279710.3390/en18112797An Improved SLAM Algorithm for Substation Inspection Robots Based on 3D Lidar and Visual Information FusionYicen Liu0Songhai Fan1State Grid Sichuan Electric Power Company, Chengdu 610094, ChinaState Grid Sichuan Electric Power Company, Chengdu 610094, ChinaCurrent substation inspection robots mainly use Lidar as a sensor for localization and map building. However, laser SLAM has the problem of localization error in scenes with similar and missing environmental structural features, and environmental maps built by laser SLAM provide more single-road information for inspection robot navigation, which is not conducive to the judgment of the road scene. For this reason, in this paper, 3D Lidar information and visual information are fused to create a SLAM algorithm applicable to substation inspection robots to solve the above laser SLAM localization error problem and improve the algorithm’s localization accuracy. First, in order to recover the scalability of monocular visual localization, the algorithm in this paper utilizes 3D Lidar information and visual information to calculate the true position of image feature points in space. Second, the laser position and visual position are utilized with interpolation to correct the point cloud distortion caused by the motion of the Lidar. Then, a position-adaptive selection algorithm is designed to use visual position instead of laser inter-frame position in some special regions to improve the robustness of the algorithm. Finally, a color laser point cloud map of the substation is constructed to provide more road environment information for the navigation of the inspection robot. The experimental results show that the localization accuracy and map-building effect of the VO-Lidar SLAM algorithm designed in this paper are better than the current laser SLAM algorithm and verify the applicability of the color laser point cloud map constructed by this algorithm in substation environments.https://www.mdpi.com/1996-1073/18/11/2797substation inspection robotsimultaneous localization and map construction3D Lidarcolor laser point cloud map |
| spellingShingle | Yicen Liu Songhai Fan An Improved SLAM Algorithm for Substation Inspection Robots Based on 3D Lidar and Visual Information Fusion Energies substation inspection robot simultaneous localization and map construction 3D Lidar color laser point cloud map |
| title | An Improved SLAM Algorithm for Substation Inspection Robots Based on 3D Lidar and Visual Information Fusion |
| title_full | An Improved SLAM Algorithm for Substation Inspection Robots Based on 3D Lidar and Visual Information Fusion |
| title_fullStr | An Improved SLAM Algorithm for Substation Inspection Robots Based on 3D Lidar and Visual Information Fusion |
| title_full_unstemmed | An Improved SLAM Algorithm for Substation Inspection Robots Based on 3D Lidar and Visual Information Fusion |
| title_short | An Improved SLAM Algorithm for Substation Inspection Robots Based on 3D Lidar and Visual Information Fusion |
| title_sort | improved slam algorithm for substation inspection robots based on 3d lidar and visual information fusion |
| topic | substation inspection robot simultaneous localization and map construction 3D Lidar color laser point cloud map |
| url | https://www.mdpi.com/1996-1073/18/11/2797 |
| work_keys_str_mv | AT yicenliu animprovedslamalgorithmforsubstationinspectionrobotsbasedon3dlidarandvisualinformationfusion AT songhaifan animprovedslamalgorithmforsubstationinspectionrobotsbasedon3dlidarandvisualinformationfusion AT yicenliu improvedslamalgorithmforsubstationinspectionrobotsbasedon3dlidarandvisualinformationfusion AT songhaifan improvedslamalgorithmforsubstationinspectionrobotsbasedon3dlidarandvisualinformationfusion |