TSM: Topological Scene Map for Representation in Indoor Environment Understanding

In the field of robotics, it is crucial to obtain a comprehensive semantic understanding of a scene for many applications. Based on the behavioral topological map and scene graph, we propose to employ a semantic map named Topological Scene Map (TSM) for representation in indoor environment understan...

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Main Authors: Zhiyong Liao, Yu Zhang, Junren Luo, Weilin Yuan
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9216084/
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spelling doaj-b2986e07e00f4d7da675f7108e9704192021-03-30T04:35:53ZengIEEEIEEE Access2169-35362020-01-01818587018588410.1109/ACCESS.2020.30293249216084TSM: Topological Scene Map for Representation in Indoor Environment UnderstandingZhiyong Liao0https://orcid.org/0000-0002-4420-6698Yu Zhang1Junren Luo2https://orcid.org/0000-0003-2126-0365Weilin Yuan3College of Intelligence Science and Technology, National University of Defense Technology, Changsha, ChinaCollege of Intelligence Science and Technology, National University of Defense Technology, Changsha, ChinaCollege of Intelligence Science and Technology, National University of Defense Technology, Changsha, ChinaCollege of Intelligence Science and Technology, National University of Defense Technology, Changsha, ChinaIn the field of robotics, it is crucial to obtain a comprehensive semantic understanding of a scene for many applications. Based on the behavioral topological map and scene graph, we propose to employ a semantic map named Topological Scene Map (TSM) for representation in indoor environment understanding. The behavioral topological map we constructed expresses the spatial connection relations and semantically describes the navigation behavior between adjacent topological nodes. The scene graph promotes the TSM to record the objects that appear in the scene and the relations between objects. The addition of spatial and semantic relations makes the expression of the scene more specific, which improves the robot's abilities of scene understanding and human-robotic interaction. In this article, we design a method for topological map construction and apply a novel approach to generate a scene graph from RGB-D data. The semantic representation of the environment generated in the experiments verifies that the TSM construction framework models the scene efficiently and the TSM is conducive to the realization of human-robotic interaction.https://ieeexplore.ieee.org/document/9216084/Scene graph generationtopological map constructionsemantic map
collection DOAJ
language English
format Article
sources DOAJ
author Zhiyong Liao
Yu Zhang
Junren Luo
Weilin Yuan
spellingShingle Zhiyong Liao
Yu Zhang
Junren Luo
Weilin Yuan
TSM: Topological Scene Map for Representation in Indoor Environment Understanding
IEEE Access
Scene graph generation
topological map construction
semantic map
author_facet Zhiyong Liao
Yu Zhang
Junren Luo
Weilin Yuan
author_sort Zhiyong Liao
title TSM: Topological Scene Map for Representation in Indoor Environment Understanding
title_short TSM: Topological Scene Map for Representation in Indoor Environment Understanding
title_full TSM: Topological Scene Map for Representation in Indoor Environment Understanding
title_fullStr TSM: Topological Scene Map for Representation in Indoor Environment Understanding
title_full_unstemmed TSM: Topological Scene Map for Representation in Indoor Environment Understanding
title_sort tsm: topological scene map for representation in indoor environment understanding
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description In the field of robotics, it is crucial to obtain a comprehensive semantic understanding of a scene for many applications. Based on the behavioral topological map and scene graph, we propose to employ a semantic map named Topological Scene Map (TSM) for representation in indoor environment understanding. The behavioral topological map we constructed expresses the spatial connection relations and semantically describes the navigation behavior between adjacent topological nodes. The scene graph promotes the TSM to record the objects that appear in the scene and the relations between objects. The addition of spatial and semantic relations makes the expression of the scene more specific, which improves the robot's abilities of scene understanding and human-robotic interaction. In this article, we design a method for topological map construction and apply a novel approach to generate a scene graph from RGB-D data. The semantic representation of the environment generated in the experiments verifies that the TSM construction framework models the scene efficiently and the TSM is conducive to the realization of human-robotic interaction.
topic Scene graph generation
topological map construction
semantic map
url https://ieeexplore.ieee.org/document/9216084/
work_keys_str_mv AT zhiyongliao tsmtopologicalscenemapforrepresentationinindoorenvironmentunderstanding
AT yuzhang tsmtopologicalscenemapforrepresentationinindoorenvironmentunderstanding
AT junrenluo tsmtopologicalscenemapforrepresentationinindoorenvironmentunderstanding
AT weilinyuan tsmtopologicalscenemapforrepresentationinindoorenvironmentunderstanding
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