SOURCE-LINKED INTELLIGENCE
Parameter Sensitivity Analysis for Aerial LiDAR-Inertial Odometries in low-altitude flights
LiDAR-based SLAM (Simultaneous Localization and Mapping) and LIO (LiDAR-inertial odometry) algorithms are often used for precise navigation of unmanned aerial vehicles, especially during interactions with the aerial robot's environment. However, the performance of these algorithms is greatly dependent on the scenario, LiDAR, and robot motion characteristics, often requiring an intensive tuning process to achieve the desired performance. To aid these tuning efforts, this paper analyzes the influence on performance of the parameters of an EKF-based LIO algorithm (FAST-LIO2) and the LIO module of
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-11T13:31:48.000Z
First collected: 2026-09-20T18:22:04.777Z. This is not the publication date.