Research on local point cloud map restoration based on laser SLAM

Wei Hou; Xiaoquan Liu; Qianqian Dong

doi:10.1117/12.3006140

10 October 2023 Research on local point cloud map restoration based on laser SLAM

Wei Hou, Xiaoquan Liu, Qianqian Dong

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279946 (2023) https://doi.org/10.1117/12.3006140
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

At present, the traditional 3D point cloud map pose solving system suffers from distortion of the local pose points due to GNSS signal locking and IMU accumulation error, which further manifests as local deformation of the point cloud map. This paper proposes a 3D point cloud map restoration method based on the joint optimization of multiple constraints to address the above problems. The method consists of DCC constraint construction module and MCO joint optimization module, which quickly constructs constraint terms after receiving front-end laser odometer poses, loopback observations and GPS data. After the system graphically models the input original trajectory positional points, the MCO module is used to jointly optimize each constraint using the positional graph to solve for the optimal positional. Finally, the method is evaluated on the publicly available KITTI dataset to demonstrate the effectiveness of the method.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wei Hou, Xiaoquan Liu, and Qianqian Dong "Research on local point cloud map restoration based on laser SLAM", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279946 (10 October 2023); https://doi.org/10.1117/12.3006140

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KEYWORDS

Point clouds

Deformation

Matrices

Nonlinear optimization

3D modeling

Feature extraction

Satellite navigation systems

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