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Issue: Số 90-09.2026
Section: Các bài báo
DOI: 10.70117/hdujs.3030-4628.90.09.2026.1152
Date Published: 27/09/2026
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Le, V. N., Nguyen, T. B. N., & Nguyen, T. H. (2026). ROBUST 2D LIDAR SCAN MATCHING USING COARSE-TO-FINE SEARCH STRATEGY AND ROBUST ERROR METRICS. Hong Duc University Journal of Science – Natural Sciences, Engineering and Technology, 90(09), 93-103. https://doi.org/10.70117/hdujs.3030-4628.90.09.2026.1152

ROBUST 2D LIDAR SCAN MATCHING USING COARSE-TO-FINE SEARCH STRATEGY AND ROBUST ERROR METRICS

Viet Nam Le, Thi Bich Nhat Nguyen1, Trung Hieu Nguyen1,
1 Hong Duc University

Main Article Content

Abstract

Simultaneous Localization and Mapping (SLAM) on resource-constrained hardware remains a significant challenge for low-cost service robots. This paper proposes an optimized Scan Matching method that integrates a Coarse-to-Fine (C2F) search strategy with a robust Trimmed objective function to address slow convergence and dynamic noise interference. Experiments with 2D Lidar sensors demonstrate that the proposed method (C2F-Trim-Robust) achieves superior stability with the lowest error standard deviation (178.6mm), significantly reducing the risk of local minima compared to traditional approaches like ICP or pure MSE. Notably, the hierarchical search strategy maintains a processing time of 3.73s, ensuring feasibility for deployment on low-end embedded processors.

Keywords

2D Lidar, Map Merging, Optimization, Coarse-to-Fine, Trimmed MSE.

Article Details

References

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