DA-IRRK: Data-Adaptive Iteratively Reweighted Robust Kernel-Based Approach for Back-End Optimization in Visual SLAM

DA-IRRK: Data-Adaptive Iteratively Reweighted Robust Kernel-Based Approach for Back-End Optimization in Visual SLAM

Back-end optimization is a key process to eliminate the cumulative error in Visual Simultaneous Localization and Mapping (VSLAM). Existing VSLAM frameworks often use kernel function-based back-end optimization methods. However, these methods typically rely on fixed kernel parameters based on the chi...

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Bibliographic Details
Main Authors: Zhimin Hu, Lan Cheng, Jiangxia Wei, Xinying Xu, Zhe Zhang, Gaowei Yan
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Sensors
Subjects:
visual SLAM
back-end optimization
median absolute deviation
data-adaptive
iteratively reweighted robust kernel
Online Access:https://www.mdpi.com/1424-8220/25/8/2529
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