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.
@article{arxiv.2112.12907,
title = {3D Point Cloud Reconstruction and SLAM as an Input},
author = {Ziyu Li and Fangyang Ye and Xinran Guan},
journal= {arXiv preprint arXiv:2112.12907},
year = {2021}
}