This article presents FAST-LIO2: a fast, robust, and versatile LiDAR-inertial odometry framework. Overall, FAST-LIO2 is computationally efficient (e.g., up to 100 Hz odometry and mapping in large outdoor environments), robust (e.g., reliable pose estimation in cluttered indoor environments with rotation up to 1000 deg/s), versatile (i.e., applicable to both multiline spinning and solid-state LiDARs, unmanned aerial vehicle (UAV) and handheld platforms, and Intel- and ARM-based processors), while...
This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.
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| Category | 🤖 Artificial Intelligence |
| Published | Jan 31, 2022 |
| Journal | IEEE Transactions on Robotics |
| Authors | Wei Xu, Yixi Cai, Dongjiao He, Jiarong Lin, Fu Zhang |
| DOI | 10.1109/tro.2022.3141876 |
| Citations | 1,445 |
| Source | OpenAlex |