Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments

Weiyue Zhang; Xianyu Qi; Yufei Zhao; Wei Wang; Xiangdong Yang

doi:10.1145/3562007.3562012

Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments

Weiyue Zhang
, Xianyu Qi^*
, Yufei Zhao
, Wei Wang
, Xiangdong Yang

^*Corresponding author for this work

School of Mechanical Engineering and Automation

CAS - Institute of Mechanics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Aiming at the demand for map expression in the human-robot co-existing environments, a multi-layer map including semantic grid map, semantic topological map and semantic concept map is proposed and constructed. Firstly, 2D LIDAR and RGB-D sensors are used to construct object semantic grid map combined with SLAM and object semantic segmentation method. Semantic topological map is then constructed using virtual door detection and Bayesian estimation method based on room and object containment relationships. Finally, according to the semantic grid and the semantic topological map, a seven-step ontology creation method is used to build a semantic concept map. The effectiveness of the proposed multi-layer map is verified by testing in multiple scenarios.

Original language	English
Title of host publication	CCRIS 2022 - Conference Proceeding
Subtitle of host publication	2022 3rd International Conference on Control, Robotics and Intelligent System
Publisher	Association for Computing Machinery
Pages	30-35
Number of pages	6
ISBN (Electronic)	9781450396851
DOIs	https://doi.org/10.1145/3562007.3562012
State	Published - 26 Aug 2022
Event	3rd International Conference on Control, Robotics and Intelligent System, CCRIS 2022 - Virtual, Online, China Duration: 26 Aug 2022 → 28 Aug 2022

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	3rd International Conference on Control, Robotics and Intelligent System, CCRIS 2022
Country/Territory	China
City	Virtual, Online
Period	26/08/22 → 28/08/22

Keywords

mobile robot
semantic concept map
semantic grid map
semantic topological map

Access to Document

10.1145/3562007.3562012

Cite this

Zhang, W., Qi, X., Zhao, Y., Wang, W., & Yang, X. (2022). Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments. In CCRIS 2022 - Conference Proceeding: 2022 3rd International Conference on Control, Robotics and Intelligent System (pp. 30-35). (ACM International Conference Proceeding Series). Association for Computing Machinery . https://doi.org/10.1145/3562007.3562012

@inproceedings{292b1bf8fd4c48be912c845ced595499,

title = "Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments",

abstract = "Aiming at the demand for map expression in the human-robot co-existing environments, a multi-layer map including semantic grid map, semantic topological map and semantic concept map is proposed and constructed. Firstly, 2D LIDAR and RGB-D sensors are used to construct object semantic grid map combined with SLAM and object semantic segmentation method. Semantic topological map is then constructed using virtual door detection and Bayesian estimation method based on room and object containment relationships. Finally, according to the semantic grid and the semantic topological map, a seven-step ontology creation method is used to build a semantic concept map. The effectiveness of the proposed multi-layer map is verified by testing in multiple scenarios.",

keywords = "mobile robot, semantic concept map, semantic grid map, semantic topological map",

author = "Weiyue Zhang and Xianyu Qi and Yufei Zhao and Wei Wang and Xiangdong Yang",

note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 3rd International Conference on Control, Robotics and Intelligent System, CCRIS 2022 ; Conference date: 26-08-2022 Through 28-08-2022",

year = "2022",

month = aug,

day = "26",

doi = "10.1145/3562007.3562012",

language = "英语",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery ",

pages = "30--35",

booktitle = "CCRIS 2022 - Conference Proceeding",

address = "美国",

}

Zhang, W, Qi, X, Zhao, Y, Wang, W & Yang, X 2022, Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments. in CCRIS 2022 - Conference Proceeding: 2022 3rd International Conference on Control, Robotics and Intelligent System. ACM International Conference Proceeding Series, Association for Computing Machinery , pp. 30-35, 3rd International Conference on Control, Robotics and Intelligent System, CCRIS 2022, Virtual, Online, China, 26/08/22. https://doi.org/10.1145/3562007.3562012

Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments. / Zhang, Weiyue; Qi, Xianyu; Zhao, Yufei et al.
CCRIS 2022 - Conference Proceeding: 2022 3rd International Conference on Control, Robotics and Intelligent System. Association for Computing Machinery , 2022. p. 30-35 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments

AU - Zhang, Weiyue

AU - Qi, Xianyu

AU - Zhao, Yufei

AU - Wang, Wei

AU - Yang, Xiangdong

PY - 2022/8/26

Y1 - 2022/8/26

N2 - Aiming at the demand for map expression in the human-robot co-existing environments, a multi-layer map including semantic grid map, semantic topological map and semantic concept map is proposed and constructed. Firstly, 2D LIDAR and RGB-D sensors are used to construct object semantic grid map combined with SLAM and object semantic segmentation method. Semantic topological map is then constructed using virtual door detection and Bayesian estimation method based on room and object containment relationships. Finally, according to the semantic grid and the semantic topological map, a seven-step ontology creation method is used to build a semantic concept map. The effectiveness of the proposed multi-layer map is verified by testing in multiple scenarios.

AB - Aiming at the demand for map expression in the human-robot co-existing environments, a multi-layer map including semantic grid map, semantic topological map and semantic concept map is proposed and constructed. Firstly, 2D LIDAR and RGB-D sensors are used to construct object semantic grid map combined with SLAM and object semantic segmentation method. Semantic topological map is then constructed using virtual door detection and Bayesian estimation method based on room and object containment relationships. Finally, according to the semantic grid and the semantic topological map, a seven-step ontology creation method is used to build a semantic concept map. The effectiveness of the proposed multi-layer map is verified by testing in multiple scenarios.

KW - mobile robot

KW - semantic concept map

KW - semantic grid map

KW - semantic topological map

UR - https://www.scopus.com/pages/publications/85140045395

U2 - 10.1145/3562007.3562012

DO - 10.1145/3562007.3562012

M3 - 会议稿件

AN - SCOPUS:85140045395

T3 - ACM International Conference Proceeding Series

SP - 30

EP - 35

BT - CCRIS 2022 - Conference Proceeding

PB - Association for Computing Machinery

T2 - 3rd International Conference on Control, Robotics and Intelligent System, CCRIS 2022

Y2 - 26 August 2022 through 28 August 2022

ER -

Zhang W, Qi X, Zhao Y, Wang W, Yang X. Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments. In CCRIS 2022 - Conference Proceeding: 2022 3rd International Conference on Control, Robotics and Intelligent System. Association for Computing Machinery . 2022. p. 30-35. (ACM International Conference Proceeding Series). doi: 10.1145/3562007.3562012

Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this