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2018 | OriginalPaper | Buchkapitel

Plane Object-Based High-Level Map Representation for SLAM

verfasst von : Pavel Gritsenko, Igor Gritsenko, Askar Seidakhmet, Bogdan Kwolek

Erschienen in: Computer Vision and Graphics

Verlag: 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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Fußnoten
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Metadaten
Titel
Plane Object-Based High-Level Map Representation for SLAM
verfasst von
Pavel Gritsenko
Igor Gritsenko
Askar Seidakhmet
Bogdan Kwolek
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-030-00692-1_9