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Multi-Sensor Fusion SLAM Method for Underground Power Pipe Gallery

Jianfei Que, Enhui Zheng, Zehai Zou

Year
2023
Citations
3
Access
Open access

Abstract

Abstract The satellite signal in the underground power pipe gallery is missing and the light is dim, so simultaneous localization and mapping (SLAM) is facing many challenges. Aiming at this special scene, a new SLAM method based on multi-sensor fusion is proposed by using a new type of area array laser radar and a monocular camera to build a 3D scanner. The geometric structure of the global map is obtained by fusing the pre-integrated IMU data and the lidar data. The texture and color information of the global map are supplemented by visual information rendering. A data connection bridge is built between the equipment and the local server in the form of remote networking to achieve data synchronization. The experimental results of an underground power pipe gallery in Zhejiang Province show that the method significantly improves the accuracy of 3D reconstruction in complex environments, and provides a useful reference for the development of localization and mapping of underground inspection robots.

Keywords

Simultaneous localization and mappingComputer visionArtificial intelligenceComputer scienceInertial measurement unitLidarRendering (computer graphics)Laser scanningRobotRemote sensing

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