Service robot localization using improved particle filter

Guanghui Cen; Nobuto Matsuhira; Junko Hirokawa; Hideki Ogawa; Ichiro Hagiwara

doi:10.1109/ICAL.2008.4636580

Service robot localization using improved particle filter

Guanghui Cen, Nobuto Matsuhira, Junko Hirokawa, Hideki Ogawa, Ichiro Hagiwara

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

2 Citations (Scopus)

Abstract

Recently, Particle filter becomes the most popular approach in mobile robot localization and has been applied with great success to a variety of state estimation problems. In this paper, the particle filter is applied in position tracking and global localization. Moreover, the posterior distribution of robot pose in global localization is usually multimodal due to the symmetry of the environment and ambiguous detected features. Considering these characteristics, we proposed the cluster particle filter to improve the global localization robustness and accuracy. Experiment results show the effectiveness and robustness of our approach in our service robot ApriAlpha™ Platform.

Original language	English
Title of host publication	Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008
Pages	2454-2459
Number of pages	6
DOIs	https://doi.org/10.1109/ICAL.2008.4636580
Publication status	Published - 2008 Nov 26
Externally published	Yes
Event	IEEE International Conference on Automation and Logistics, ICAL 2008 - Qingdao, China Duration: 2008 Sept 1 → 2008 Sept 3

Publication series

Name	Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008

Conference

Conference	IEEE International Conference on Automation and Logistics, ICAL 2008
Country/Territory	China
City	Qingdao
Period	08/9/1 → 08/9/3

Keywords

Cluster particle filter
Global localization
Particle filter
Service robot

ASJC Scopus subject areas

Artificial Intelligence
Hardware and Architecture
Control and Systems Engineering

Access to Document

10.1109/ICAL.2008.4636580

Cite this

Cen, G., Matsuhira, N., Hirokawa, J., Ogawa, H., & Hagiwara, I. (2008). Service robot localization using improved particle filter. In Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008 (pp. 2454-2459). [4636580] (Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008). https://doi.org/10.1109/ICAL.2008.4636580

Service robot localization using improved particle filter. / Cen, Guanghui; Matsuhira, Nobuto; Hirokawa, Junko et al.

Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008. 2008. p. 2454-2459 4636580 (Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008).

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

Cen, G, Matsuhira, N, Hirokawa, J, Ogawa, H & Hagiwara, I 2008, Service robot localization using improved particle filter. in Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008., 4636580, Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008, pp. 2454-2459, IEEE International Conference on Automation and Logistics, ICAL 2008, Qingdao, China, 08/9/1. https://doi.org/10.1109/ICAL.2008.4636580

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title = "Service robot localization using improved particle filter",

abstract = "Recently, Particle filter becomes the most popular approach in mobile robot localization and has been applied with great success to a variety of state estimation problems. In this paper, the particle filter is applied in position tracking and global localization. Moreover, the posterior distribution of robot pose in global localization is usually multimodal due to the symmetry of the environment and ambiguous detected features. Considering these characteristics, we proposed the cluster particle filter to improve the global localization robustness and accuracy. Experiment results show the effectiveness and robustness of our approach in our service robot ApriAlpha{\texttrademark} Platform.",

keywords = "Cluster particle filter, Global localization, Particle filter, Service robot",

author = "Guanghui Cen and Nobuto Matsuhira and Junko Hirokawa and Hideki Ogawa and Ichiro Hagiwara",

year = "2008",

month = nov,

day = "26",

doi = "10.1109/ICAL.2008.4636580",

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series = "Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008",

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AU - Cen, Guanghui

AU - Matsuhira, Nobuto

AU - Hirokawa, Junko

AU - Ogawa, Hideki

AU - Hagiwara, Ichiro

PY - 2008/11/26

Y1 - 2008/11/26

N2 - Recently, Particle filter becomes the most popular approach in mobile robot localization and has been applied with great success to a variety of state estimation problems. In this paper, the particle filter is applied in position tracking and global localization. Moreover, the posterior distribution of robot pose in global localization is usually multimodal due to the symmetry of the environment and ambiguous detected features. Considering these characteristics, we proposed the cluster particle filter to improve the global localization robustness and accuracy. Experiment results show the effectiveness and robustness of our approach in our service robot ApriAlpha™ Platform.

AB - Recently, Particle filter becomes the most popular approach in mobile robot localization and has been applied with great success to a variety of state estimation problems. In this paper, the particle filter is applied in position tracking and global localization. Moreover, the posterior distribution of robot pose in global localization is usually multimodal due to the symmetry of the environment and ambiguous detected features. Considering these characteristics, we proposed the cluster particle filter to improve the global localization robustness and accuracy. Experiment results show the effectiveness and robustness of our approach in our service robot ApriAlpha™ Platform.

KW - Cluster particle filter

KW - Global localization

KW - Particle filter

KW - Service robot

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T3 - Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008

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Service robot localization using improved particle filter

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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