BA-LINS: A Frame-to-Frame Bundle Adjustment for LiDAR-Inertial Navigation
CoRR(2024)
摘要
Bundle Adjustment (BA) has been proven to improve the accuracy of the LiDAR
mapping. However, the BA method has not yet been properly employed in a
dead-reckoning navigation system. In this paper, we present a frame-to-frame
(F2F) BA for LiDAR-inertial navigation, named BA-LINS. Based on the direct F2F
point-cloud association, the same-plane points are associated among the LiDAR
keyframes. Hence, the F2F plane-point BA measurement can be constructed using
the same-plane points. The LiDAR BA and the inertial measurement unit
(IMU)-preintegration measurements are tightly integrated under the framework of
factor graph optimization. An effective adaptive covariance estimation
algorithm for LiDAR BA measurements is proposed to further improve the
accuracy. We conduct exhaustive real-world experiments on public and private
datasets to examine the proposed BA-LINS. The results demonstrate that BA-LINS
yields superior accuracy to state-of-the-art methods. Compared to the baseline
system FF-LINS, the absolute translation accuracy and state-estimation
efficiency of BA-LINS are improved by 29.5
respectively. Besides, the ablation experiment results exhibit that the
proposed adaptive covariance estimation algorithm can notably improve the
accuracy and robustness of BA-LINS.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要