Version 1
: Received: 26 July 2024 / Approved: 29 July 2024 / Online: 29 July 2024 (09:56:43 CEST)
How to cite:
Shi, B.; Lin, W.; Ouyang, W.; Shen, C.; Sun, S.; Sun, Y.; Sun, L. BA-CLM: A Globally Consistent 3D LiDAR Mapping Based on BA Cost Factors. Preprints2024, 2024072274. https://doi.org/10.20944/preprints202407.2274.v1
Shi, B.; Lin, W.; Ouyang, W.; Shen, C.; Sun, S.; Sun, Y.; Sun, L. BA-CLM: A Globally Consistent 3D LiDAR Mapping Based on BA Cost Factors. Preprints 2024, 2024072274. https://doi.org/10.20944/preprints202407.2274.v1
Shi, B.; Lin, W.; Ouyang, W.; Shen, C.; Sun, S.; Sun, Y.; Sun, L. BA-CLM: A Globally Consistent 3D LiDAR Mapping Based on BA Cost Factors. Preprints2024, 2024072274. https://doi.org/10.20944/preprints202407.2274.v1
APA Style
Shi, B., Lin, W., Ouyang, W., Shen, C., Sun, S., Sun, Y., & Sun, L. (2024). BA-CLM: A Globally Consistent 3D LiDAR Mapping Based on BA Cost Factors. Preprints. https://doi.org/10.20944/preprints202407.2274.v1
Chicago/Turabian Style
Shi, B., Yan Sun and Lei Sun. 2024 "BA-CLM: A Globally Consistent 3D LiDAR Mapping Based on BA Cost Factors" Preprints. https://doi.org/10.20944/preprints202407.2274.v1
Abstract
Constructing a globally consistent high-precision map is essential for the application of mobile robots. Existing optimization-based mapping methods typically constrain robot states in pose space during the graph optimization process, without directly optimizing the structure of the scene, thereby causing the map to be inconsistent. To address the above issues, this paper presents a three-dimensional (3D) LiDAR mapping framework (i.e., BA-CLM) based on LiDAR bundle adjustment (LBA) cost factors. We propose a multivariate LBA cost factor, which is built from a multi-resolution voxel map, to uniformly constrain the robot poses within a submap. The framework proposed in this paper applies the LBA cost factors for both local and global map optimization. Experimental results on several public 3D LiDAR datasets and a self-collected 32-line LiDAR dataset demonstrated that the proposed method achieves accurate trajectory estimation and consistent mapping.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
