An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor

Yang Wang; Weimin Zhang; Fangxing Li; Yongliang Shi; Zhuo Chen; Fuyu Nie; Chi Zhu; Qiang Huang

doi:10.1109/ARSO46408.2019.8948809

An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor

Yang Wang, Weimin Zhang^*, Fangxing Li, Yongliang Shi, Zhuo Chen, Fuyu Nie, Chi Zhu, Qiang Huang

^*Corresponding author for this work

School of Mechatronical Engineering

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

5 Citations (Scopus)

Abstract

In this paper, an optimization algorithm is proposed to achieve efficient global positioning and recovery from kidnap in open environment. Due to the ability of some sensors to achieve global localization efficiently, such as Ultra-Wideband (UWB), Wi-Fi, and camera, we take the UWB sensor to improve AMCL. By comparing various ranging and positioning schemes, we propose a specific analysis of UWB ranging and positioning methods, as well as an observation model for integrating UWB information. Finally, the efficiency of this method is proved by comparison with AMCL. Thus, the time to locate globally is about 3 seconds, while more than 100 seconds using AMCL.

Original language	English
Title of host publication	2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019
Publisher	IEEE Computer Society
Pages	421-426
Number of pages	6
ISBN (Electronic)	9781728131764
DOIs	https://doi.org/10.1109/ARSO46408.2019.8948809
Publication status	Published - Oct 2019
Event	15th IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019 - Beijing, China Duration: 31 Oct 2019 → 2 Nov 2019

Publication series

Name	Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO
Volume	2019-October
ISSN (Print)	2162-7568
ISSN (Electronic)	2162-7576

Conference

Conference	15th IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019
Country/Territory	China
City	Beijing
Period	31/10/19 → 2/11/19

Keywords

Fusion
MCL
UWB

Access to Document

10.1109/ARSO46408.2019.8948809

Cite this

Wang, Y., Zhang, W., Li, F., Shi, Y., Chen, Z., Nie, F., Zhu, C., & Huang, Q. (2019). An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor. In 2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019 (pp. 421-426). Article 8948809 (Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO; Vol. 2019-October). IEEE Computer Society. https://doi.org/10.1109/ARSO46408.2019.8948809

@inproceedings{44ede809c8ab4255b3bb3770ee782e0e,

title = "An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor",

abstract = "In this paper, an optimization algorithm is proposed to achieve efficient global positioning and recovery from kidnap in open environment. Due to the ability of some sensors to achieve global localization efficiently, such as Ultra-Wideband (UWB), Wi-Fi, and camera, we take the UWB sensor to improve AMCL. By comparing various ranging and positioning schemes, we propose a specific analysis of UWB ranging and positioning methods, as well as an observation model for integrating UWB information. Finally, the efficiency of this method is proved by comparison with AMCL. Thus, the time to locate globally is about 3 seconds, while more than 100 seconds using AMCL.",

keywords = "Fusion, MCL, UWB",

author = "Yang Wang and Weimin Zhang and Fangxing Li and Yongliang Shi and Zhuo Chen and Fuyu Nie and Chi Zhu and Qiang Huang",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 15th IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019 ; Conference date: 31-10-2019 Through 02-11-2019",

year = "2019",

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doi = "10.1109/ARSO46408.2019.8948809",

language = "English",

series = "Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO",

publisher = "IEEE Computer Society",

pages = "421--426",

booktitle = "2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019",

address = "United States",

}

Wang, Y, Zhang, W , Li, F, Shi, Y, Chen, Z, Nie, F, Zhu, C & Huang, Q 2019, An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor. in 2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019., 8948809, Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO, vol. 2019-October, IEEE Computer Society, pp. 421-426, 15th IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019, Beijing, China, 31/10/19. https://doi.org/10.1109/ARSO46408.2019.8948809

An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor. / Wang, Yang; Zhang, Weimin ; Li, Fangxing et al.
2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019. IEEE Computer Society, 2019. p. 421-426 8948809 (Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO; Vol. 2019-October).

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

TY - GEN

T1 - An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor

AU - Wang, Yang

AU - Zhang, Weimin

AU - Li, Fangxing

AU - Shi, Yongliang

AU - Chen, Zhuo

AU - Nie, Fuyu

AU - Zhu, Chi

AU - Huang, Qiang

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N2 - In this paper, an optimization algorithm is proposed to achieve efficient global positioning and recovery from kidnap in open environment. Due to the ability of some sensors to achieve global localization efficiently, such as Ultra-Wideband (UWB), Wi-Fi, and camera, we take the UWB sensor to improve AMCL. By comparing various ranging and positioning schemes, we propose a specific analysis of UWB ranging and positioning methods, as well as an observation model for integrating UWB information. Finally, the efficiency of this method is proved by comparison with AMCL. Thus, the time to locate globally is about 3 seconds, while more than 100 seconds using AMCL.

AB - In this paper, an optimization algorithm is proposed to achieve efficient global positioning and recovery from kidnap in open environment. Due to the ability of some sensors to achieve global localization efficiently, such as Ultra-Wideband (UWB), Wi-Fi, and camera, we take the UWB sensor to improve AMCL. By comparing various ranging and positioning schemes, we propose a specific analysis of UWB ranging and positioning methods, as well as an observation model for integrating UWB information. Finally, the efficiency of this method is proved by comparison with AMCL. Thus, the time to locate globally is about 3 seconds, while more than 100 seconds using AMCL.

KW - Fusion

KW - MCL

KW - UWB

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DO - 10.1109/ARSO46408.2019.8948809

M3 - Conference contribution

AN - SCOPUS:85078351855

T3 - Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO

SP - 421

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BT - 2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019

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T2 - 15th IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019

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Wang Y, Zhang W , Li F, Shi Y, Chen Z, Nie F et al. An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor. In 2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019. IEEE Computer Society. 2019. p. 421-426. 8948809. (Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO). doi: 10.1109/ARSO46408.2019.8948809

An improved Adaptive Monte Carlo Localization Algorithm Fused with Ultra Wideband Sensor

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