Collaborative SLAM System Based on Shared Priori Maps

Chunxu Wu; Yicheng Shou; Zhen Li; Xiangdong Liu

doi:10.1007/978-981-19-6613-2_658

Collaborative SLAM System Based on Shared Priori Maps

Chunxu Wu, Yicheng Shou, Zhen Li^*, Xiangdong Liu

^*Corresponding author for this work

Beijing Institute of Technology

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

Abstract

Multi-robot system outperforms in efficiency for cooperative task, where the challenging burden of information exchange for surrounding environment is facilitated by collaborative simultaneous localization and mapping (SLAM). However, the utilization of environmental information, i.e., mapping, should be specifically put into efficient use and merged from the viewpoint of computation saving and localization accuracy improvement. Towards these issues, this paper proposes the Collaborative SLAM system based on shared priori maps which includes multi-agent initialization and a new map sharing and reuse mechanism among various active agents in an incremental way. Finally, based on the data set recorded in the actual laboratory environment, the proposed Collaborative SLAM system is evaluated from the perspectives of localization accuracy and computational power consumption.

Original language	English
Title of host publication	Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control
Editors	Liang Yan, Haibin Duan, Yimin Deng, Liang Yan
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	6825-6835
Number of pages	11
ISBN (Print)	9789811966125
DOIs	https://doi.org/10.1007/978-981-19-6613-2_658
Publication status	Published - 2023
Event	International Conference on Guidance, Navigation and Control, ICGNC 2022 - Harbin, China Duration: 5 Aug 2022 → 7 Aug 2022

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	845 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	International Conference on Guidance, Navigation and Control, ICGNC 2022
Country/Territory	China
City	Harbin
Period	5/08/22 → 7/08/22

Keywords

Collaborative simultaneous localization and mapping
Expansion and optimization
Localization
Map utilization
Motion capture system
Priori map

Access to Document

10.1007/978-981-19-6613-2_658

Cite this

Wu, C., Shou, Y., Li, Z., & Liu, X. (2023). Collaborative SLAM System Based on Shared Priori Maps. In L. Yan, H. Duan, Y. Deng, & L. Yan (Eds.), Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control (pp. 6825-6835). (Lecture Notes in Electrical Engineering; Vol. 845 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-6613-2_658

Wu, Chunxu ; Shou, Yicheng ; Li, Zhen et al. / Collaborative SLAM System Based on Shared Priori Maps. Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control. editor / Liang Yan ; Haibin Duan ; Yimin Deng ; Liang Yan. Springer Science and Business Media Deutschland GmbH, 2023. pp. 6825-6835 (Lecture Notes in Electrical Engineering).

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title = "Collaborative SLAM System Based on Shared Priori Maps",

abstract = "Multi-robot system outperforms in efficiency for cooperative task, where the challenging burden of information exchange for surrounding environment is facilitated by collaborative simultaneous localization and mapping (SLAM). However, the utilization of environmental information, i.e., mapping, should be specifically put into efficient use and merged from the viewpoint of computation saving and localization accuracy improvement. Towards these issues, this paper proposes the Collaborative SLAM system based on shared priori maps which includes multi-agent initialization and a new map sharing and reuse mechanism among various active agents in an incremental way. Finally, based on the data set recorded in the actual laboratory environment, the proposed Collaborative SLAM system is evaluated from the perspectives of localization accuracy and computational power consumption.",

keywords = "Collaborative simultaneous localization and mapping, Expansion and optimization, Localization, Map utilization, Motion capture system, Priori map",

author = "Chunxu Wu and Yicheng Shou and Zhen Li and Xiangdong Liu",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Guidance, Navigation and Control, ICGNC 2022 ; Conference date: 05-08-2022 Through 07-08-2022",

year = "2023",

doi = "10.1007/978-981-19-6613-2_658",

language = "English",

isbn = "9789811966125",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "6825--6835",

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address = "Germany",

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Wu, C, Shou, Y, Li, Z & Liu, X 2023, Collaborative SLAM System Based on Shared Priori Maps. in L Yan, H Duan, Y Deng & L Yan (eds), Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control. Lecture Notes in Electrical Engineering, vol. 845 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 6825-6835, International Conference on Guidance, Navigation and Control, ICGNC 2022, Harbin, China, 5/08/22. https://doi.org/10.1007/978-981-19-6613-2_658

Collaborative SLAM System Based on Shared Priori Maps. / Wu, Chunxu; Shou, Yicheng; Li, Zhen et al.
Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control. ed. / Liang Yan; Haibin Duan; Yimin Deng; Liang Yan. Springer Science and Business Media Deutschland GmbH, 2023. p. 6825-6835 (Lecture Notes in Electrical Engineering; Vol. 845 LNEE).

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

TY - GEN

T1 - Collaborative SLAM System Based on Shared Priori Maps

AU - Wu, Chunxu

AU - Shou, Yicheng

AU - Li, Zhen

AU - Liu, Xiangdong

PY - 2023

Y1 - 2023

N2 - Multi-robot system outperforms in efficiency for cooperative task, where the challenging burden of information exchange for surrounding environment is facilitated by collaborative simultaneous localization and mapping (SLAM). However, the utilization of environmental information, i.e., mapping, should be specifically put into efficient use and merged from the viewpoint of computation saving and localization accuracy improvement. Towards these issues, this paper proposes the Collaborative SLAM system based on shared priori maps which includes multi-agent initialization and a new map sharing and reuse mechanism among various active agents in an incremental way. Finally, based on the data set recorded in the actual laboratory environment, the proposed Collaborative SLAM system is evaluated from the perspectives of localization accuracy and computational power consumption.

AB - Multi-robot system outperforms in efficiency for cooperative task, where the challenging burden of information exchange for surrounding environment is facilitated by collaborative simultaneous localization and mapping (SLAM). However, the utilization of environmental information, i.e., mapping, should be specifically put into efficient use and merged from the viewpoint of computation saving and localization accuracy improvement. Towards these issues, this paper proposes the Collaborative SLAM system based on shared priori maps which includes multi-agent initialization and a new map sharing and reuse mechanism among various active agents in an incremental way. Finally, based on the data set recorded in the actual laboratory environment, the proposed Collaborative SLAM system is evaluated from the perspectives of localization accuracy and computational power consumption.

KW - Collaborative simultaneous localization and mapping

KW - Expansion and optimization

KW - Localization

KW - Map utilization

KW - Motion capture system

KW - Priori map

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SN - 9789811966125

T3 - Lecture Notes in Electrical Engineering

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BT - Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control

A2 - Yan, Liang

A2 - Duan, Haibin

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PB - Springer Science and Business Media Deutschland GmbH

T2 - International Conference on Guidance, Navigation and Control, ICGNC 2022

Y2 - 5 August 2022 through 7 August 2022

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Wu C, Shou Y, Li Z , Liu X. Collaborative SLAM System Based on Shared Priori Maps. In Yan L, Duan H, Deng Y, Yan L, editors, Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control. Springer Science and Business Media Deutschland GmbH. 2023. p. 6825-6835. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-19-6613-2_658

Collaborative SLAM System Based on Shared Priori Maps

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