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

• Published in: IEEE robotics and automation letters Vol. 6; no. 3; pp. 5167 - 5174
• Main Authors: Li, Kailai, Li, Meng, Hanebeck, Uwe D.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Datasets; Feature extraction; Laser radar; Lidar; localization; Mapping; Optimization; Real-time systems; Robot sensing systems; Runtime; Sensor fusion; Solid state; Source code; Three-dimensional displays
• ISSN: 2377-3766; 2377-3766
• DOI: 10.1109/LRA.2021.3070251

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 .