Adaptive Multi-Sensor Fusion for SLAM: A Scan Context-Driven Approach
TL;DR
This paper introduces SC-LVI-SAM, a multi-sensor fusion SLAM algorithm using scan context to improve positioning accuracy in complex scenes by addressing feature point loss and motion issues.
Adaptive Multi-Sensor Fusion for SLAM: A Scan Context-Driven Approach
Yijing Zhang; Jia Liu; Runxi Cao; Yunxi Zhang
https://doi.org/10.1109/ACCESS.2024.3523129
Volume 13
This paper proposes a novel multi-sensor fusion SLAM algorithm, named SC-LVI-SAM, based on scanning context, to address the issues of decreased positioning accuracy caused by missing feature points and prolonged motion in complex large-scale scenes in multi-sensor fusion SLAM algorithms. Firstly, the scanning context method is used to preprocess LIDAR point cloud data, generating a descriptor of t...