FAST-LIO2: Fast Direct LiDAR-Inertial Odometry
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Abstract
This article presents FAST-LIO2: a fast, robust, and versatile LiDAR-inertial odometry framework. Building on a highly efficient tightly coupled iterated Kalman filter, FAST-LIO2 has two key novelties that allow fast, robust, and accurate LiDAR navigation (and mapping). The first one is directly registering raw points to the map (and subsequently update the map, i.e., mapping) without extracting features. This enables the exploitation of subtle features in the environment and, hence, increases the accuracy. The elimination of a hand-engineered feature extraction module also makes it naturally adaptable to emerging LiDARs of different scanning patterns; the second main novelty is maintaining a map by an…
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5Topics & keywords
Topics
Keywords
- Odometry
- Lidar
- Tree (set theory)
- Computer science
- Artificial intelligence
- Benchmark (surveying)
- Upsampling
- Algorithm
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