Title :
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
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;
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
DOI :
10.1109/ICAL.2008.4636580
