Unified Representation of Geometric Primitives for Graph-SLAM Optimization Using Decomposed Quadrics

• URL: http://arxiv.org/abs/2108.08957v1
• Date: Fri, 20 Aug 2021 01:06:51 GMT
• Title: Unified Representation of Geometric Primitives for Graph-SLAM Optimization Using Decomposed Quadrics
• Authors: Weikun Zhen, Huai Yu, Yaoyu Hu, Sebastian Scherer
• Abstract summary: This work is focused on the parameterization problem of high-level geometric primitives. We first present a unified representation of those geometric primitives using emphquadrics which yields a consistent and concise formulation. In simulation experiments, it is shown that the decomposed formulation has better efficiency and robustness to observation noises than baseline parameterizations.
• Score: 12.096145632383418
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In Simultaneous Localization And Mapping (SLAM) problems, high-level landmarks have the potential to build compact and informative maps compared to traditional point-based landmarks. This work is focused on the parameterization problem of high-level geometric primitives that are most frequently used, including points, lines, planes, ellipsoids, cylinders, and cones. We first present a unified representation of those geometric primitives using \emph{quadrics} which yields a consistent and concise formulation. Then we further study a decomposed model of quadrics that discloses the symmetric and degenerated nature of quadrics. Based on the decomposition, we develop physically meaningful quadrics factors in the settings of the graph-SLAM problem. Finally, in simulation experiments, it is shown that the decomposed formulation has better efficiency and robustness to observation noises than baseline parameterizations. And in real-world experiments, the proposed back-end framework is demonstrated to be capable of building compact and regularized maps.

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