Service robot localization using improved Particle filter

Author

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

Author_Institution

Dept. Mech. Sci. & Eng., Tokyo Inst. of Technol., Tokyo

fYear

2008

fDate

1-3 Sept. 2008

Firstpage

2454

Lastpage

2459

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 ApriAlphatrade Platform.

Keywords

mobile robots; particle filtering (numerical methods); position control; service robots; state estimation; tracking; ApriAlpha platform; global localization; mobile robot localization; particle filter; position tracking; posterior distribution; robot pose; service robot localization; state estimation; Computer vision; Mobile robots; Particle filters; Robot kinematics; Robot localization; Robot sensing systems; Robotics and automation; Robustness; Service robots; Spatial resolution; Cluster Particle Filter; Global Localization; Particle Filter; Service Robot;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4244-2502-0

Electronic_ISBN

978-1-4244-2503-7

Type

conf

DOI

10.1109/ICAL.2008.4636580

Filename

4636580