Towards High-Performance Solid-State-LiDAR-Inertial Odometry and Mapping

TL;DR

This paper introduces a real-time, high-accuracy LiDAR-inertial odometry and mapping system that works with both solid-state and mechanical LiDARs, including a novel feature extraction method for the Livox Horizon.

Contribution

It presents a novel tightly-coupled LiDAR-inertial odometry framework with a new feature extraction method tailored for solid-state LiDARs, achieving superior accuracy and real-time performance.

Findings

Outperforms state-of-the-art systems on public datasets.

Successfully handles irregular scan patterns of solid-state LiDARs.

Achieves real-time operation with high accuracy.

Abstract

We present a novel tightly-coupled LiDAR-inertial odometry and mapping scheme for both solid-state and mechanical LiDARs. As frontend, a feature-based lightweight LiDAR odometry provides fast motion estimates for adaptive keyframe selection. As backend, a hierarchical keyframe-based sliding window optimization is performed through marginalization for directly fusing IMU and LiDAR measurements. For the Livox Horizon, a newly released solid-state LiDAR, a novel feature extraction method is proposed to handle its irregular scan pattern during preprocessing. LiLi-OM (Livox LiDAR-inertial odometry and mapping) is real-time capable and achieves superior accuracy over state-of-the-art systems for both LiDAR types on public data sets of mechanical LiDARs and in experiments using the Livox Horizon. Source code and recorded experimental data sets are available at https://github.com/KIT-ISAS/lili-om.