iG-LIO: an incremental GICP-based tightly-coupled LiDAR-inertial odometry

iG-LIO: an incremental GICP-based tightly-coupled LiDAR-inertial odometry

This work proposes an incremental Generalized Iterative Closest Point (GICP) based tightly-coupled LiDAR-inertial odometry (LIO), iG-LIO, which integrates the GICP constraints and inertial constraints into a unified estimation framework. iG-LIO uses a voxel-based surface covariance estimator to esti...

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Bibliographic Details
Main Authors: Chen, Zijie, Xu, Yong, Yuan, Shenghai, Xie, Lihua
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2025
Subjects:
Computer and Information Science
Sensor fusion
LiDAR-inertial odometry
Online Access:https://hdl.handle.net/10356/182645

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