Abstract
LiDAR relocalization aims to estimate the global 6-DoF pose of a sensor in the environment. However, existing regression-based approaches often encounter limitations in dynamic or ambiguous scenarios, as they typically prioritize single-frame inference, leaving the potential of spatio-temporal consistency across scans not fully explored. In this paper, we propose a Temporal-aware Localization framework (TempLoc) designed to enhance the robustness of outdoor localization by effectively modeling sequential consistency. Specifically, a Global Coordinate Estimation module is first introduced to predict point-wise global coordinates and associated uncertainties for each LiDAR scan. A Prior Coordinate Generation module is then presented to estimate inter-frame point correspondences by the attention mechanism. Lastly, an Uncertainty-Guided Coordinate Fusion module is deployed to integrate both predictions of point correspondence in an end-to-end fashion, yielding a more temporally consistent and accurate global 6-DoF pose. Experimental results on the NCLT and Oxford RobotCar benchmarks show that our TempLoc outperforms state-of-the-art methods by a large margin, demonstrating the effectiveness of temporal-aware correspondence modeling in LiDAR relocalization.
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- Open access
- Green open access
Cite this article
APA 7
Zhu, M., Wang, Z., Guo, Y., Liu, C., Huang, Y., Li, W., Ao, S., & Wang, C. (2026). Temporal-Aware Fusion for Robust Outdoor LiDAR Localization. https://omanscience.com/en/articles/temporal-aware-fusion-for-robust-outdoor-lidar-localization
MLA 9
Zhu, Minghang, et al. "Temporal-Aware Fusion for Robust Outdoor LiDAR Localization." https://omanscience.com/en/articles/temporal-aware-fusion-for-robust-outdoor-lidar-localization.
Chicago (author–date)
Zhu, Minghang, Zhijing Wang, Yuxin Guo, Chen Liu, Yongshu Huang, Wen Li, Sheng Ao, and Cheng Wang. 2026. "Temporal-Aware Fusion for Robust Outdoor LiDAR Localization." https://omanscience.com/en/articles/temporal-aware-fusion-for-robust-outdoor-lidar-localization.
Harvard
Zhu, M., Wang, Z., Guo, Y., Liu, C., Huang, Y., Li, W., Ao, S. and Wang, C. (2026) 'Temporal-Aware Fusion for Robust Outdoor LiDAR Localization', Available at: https://omanscience.com/en/articles/temporal-aware-fusion-for-robust-outdoor-lidar-localization.
Vancouver
Zhu M, Wang Z, Guo Y, Liu C, Huang Y, Li W, et al. Temporal-Aware Fusion for Robust Outdoor LiDAR Localization. https://omanscience.com/en/articles/temporal-aware-fusion-for-robust-outdoor-lidar-localization
IEEE
M. Zhu, Z. Wang, Y. Guo, C. Liu, Y. Huang, W. Li, S. Ao, and C. Wang, "Temporal-Aware Fusion for Robust Outdoor LiDAR Localization," https://omanscience.com/en/articles/temporal-aware-fusion-for-robust-outdoor-lidar-localization.