000164052 001__ 164052 000164052 005__ 20251121161351.0 000164052 0247_ $$2doi$$a10.1109/LRA.2025.3623043 000164052 0248_ $$2sideral$$a146192 000164052 037__ $$aART-2025-146192 000164052 041__ $$aeng 000164052 100__ $$aLiu, Changxiang 000164052 245__ $$aSelective Point Sampling for LiDAR-Inertial Odometry 000164052 260__ $$c2025 000164052 5203_ $$aThe accuracy of LiDAR-Inertial Odometry (LIO) is highly sensitive to low-quality LiDAR measurements, which can substantially degrade state estimation. In this paper we propose Selective Point Sampling (SPS), a lightweight strategy that enhances LIO performance by discarding as outliers LiDAR measurements that are statistically inconsistent with their local map neighborhood. Consistency is quantified using the Kullback–Leibler (KL) divergence between each measurement’s distribution and the averaged distributions of its neighboring map points, and only measurements below a KL threshold are retained to form residuals for state updates. SPS is implemented as a modular plug-in compatible with existing EKF-based LIO frameworks, requiring minimal integration effort. Extensive experiments on public datasets—NCLT, M2DGR, Botanic Garden, and Newer College—and additional custom-collected sequences demonstrate consistent localization accuracy gains across multiple baselines with negligible computational overhead. 000164052 540__ $$9info:eu-repo/semantics/closedAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000164052 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000164052 700__ $$aYu, Hongshan 000164052 700__ $$aChen, Xieyuanli 000164052 700__ $$aLu, Huimin 000164052 700__ $$aWang, Jingchuan 000164052 700__ $$aHuang, Yi 000164052 700__ $$0(orcid)0000-0003-1368-1151$$aCivera, Javier$$uUniversidad de Zaragoza 000164052 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát. 000164052 773__ $$g10, 12 (2025), 12875-12882$$pIEEE Robot. autom. let.$$tIEEE Robotics and Automation Letters$$x2377-3766 000164052 8564_ $$s1861353$$uhttps://zaguan.unizar.es/record/164052/files/texto_completo.pdf$$yVersión publicada 000164052 8564_ $$s3621203$$uhttps://zaguan.unizar.es/record/164052/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000164052 909CO $$ooai:zaguan.unizar.es:164052$$particulos$$pdriver 000164052 951__ $$a2025-11-21-14:25:33 000164052 980__ $$aARTICLE