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PLVS: A SLAM System with Points, Lines, Volumetric Mapping, and 3D Incremental Segmentation

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arxiv 2309.10896 v2 pith:IB2H7EYZ submitted 2023-09-19 cs.CV cs.RO

classification cs.CVcs.RO
keywords plvslinemappingvolumetricsegmentationslamavailableerror
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This document presents PLVS: a real-time system that leverages sparse SLAM, volumetric mapping, and 3D unsupervised incremental segmentation. PLVS stands for Points, Lines, Volumetric mapping, and Segmentation. It supports RGB-D and Stereo cameras, which may be optionally equipped with IMUs. The SLAM module is keyframe-based, and extracts and tracks sparse points and line segments as features. Volumetric mapping runs in parallel with respect to the SLAM front-end and generates a 3D reconstruction of the explored environment by fusing point clouds backprojected from keyframes. Different volumetric mapping methods are supported and integrated in PLVS. We use a novel reprojection error to bundle-adjust line segments. This error exploits available depth information to stabilize the position estimates of line segment endpoints. An incremental and geometric-based segmentation method is implemented and integrated for RGB-D cameras in the PLVS framework. We present qualitative and quantitative evaluations of the PLVS framework on some publicly available datasets. The appendix details the adopted stereo line triangulation method and provides a derivation of the Jacobians we used for line error terms. The software is available as open-source.

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Cited by 1 Pith paper

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  1. Online Knowledge Integration for 3D Semantic Mapping: A Survey

    cs.RO 2024-11 conditional novelty 2.0 of 10

    The paper provides a structured overview of online knowledge integration techniques for 3D semantic mapping, focusing on semantic scene graphs and language models.

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