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2018 | OriginalPaper | Chapter

Plane Object-Based High-Level Map Representation for SLAM

Authors : Pavel Gritsenko, Igor Gritsenko, Askar Seidakhmet, Bogdan Kwolek

Published in: Computer Vision and Graphics

Publisher: Springer International Publishing

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Abstract

High-level map representation providing object-based understanding of the environment is an important component for SLAM. We present a novel algorithm to build plane object-based map representation upon point cloud that is obtained in real–time from RGB-D sensors such as Kinect. On the basis of segmented planes in point cloud we construct a graph, where a node and edge represent a plane and its real intersection with other plane, respectively. After that, we extract all trihedral angles (corners) represented by 3rd order cycles in the graph. Afterwards, we execute systematic aggregation of trihedral angles into object such as trihedral angles of the same plane-based object have common edges. Finally, we classify objects using simple subgraph patterns and determine their physical sizes. Our experiments figured out that the proposed algorithm reliably extracts objects, determines their physical sizes and classifies them with a promising performance.

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Footnotes
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Metadata
Title
Plane Object-Based High-Level Map Representation for SLAM
Authors
Pavel Gritsenko
Igor Gritsenko
Askar Seidakhmet
Bogdan Kwolek
Copyright Year
2018
Book
Computer Vision and Graphics

Print ISBN: 978-3-030-00691-4

Electronic ISBN: 978-3-030-00692-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-00692-1_9

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