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arXiv · 2112.12907

3D Point Cloud Reconstruction and SLAM as an Input

Ziyu Li·Fangyang Ye·Xinran Guan
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Abstract

To handle the different types of surface reconstruction tasks, we have replicated as well as modified a few of reconstruction methods and have made comparisons between the traditional method and data-driven method for reconstruction the surface of an object with dense point cloud as input. On top of that, we proposed a system using tightly-coupled SLAM as an input to generate deskewed point cloud and odometry and a Truncated Signed Distance Function based Surface Reconstruction Library. To get higher accuracy, IMU(Inertial Measurement Unit) pre-integration and pose graph optimization are conduct in the SLAM part. With the help of the Robot Operating System, we could build a system containing those two parts, which can conduct a real-time outdoor surface reconstruction.

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Ziyu Li, Fangyang Ye, Xinran Guan. 2021-12-24. 3D Point Cloud Reconstruction and SLAM as an Input. https://arxiv.org/abs/2112.12907

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