Title :
Effective application of Monte Carlo localization for service robot
Author :
Cen, Guanghui ; Nakamoto, Hideichi ; Matsuhira, Nobuto ; Hagiwara, Ichiro
Author_Institution :
Tokyo Inst. of Technol., Tokyo
fDate :
Oct. 29 2007-Nov. 2 2007
Abstract :
At indoor environment, a service robot must know where it is at any time. Thus, reliable position estimation is a basic and key problem. Probabilistic robotics techniques have become one of the dominant paradigms for algorithm design in robotics. Recent work on Monte Carlo Localization with particle-based density representation becomes popular. In this paper we introduce the multi-sensor based Monte Carlo localization (MCL) method which represents a robot´s belief by a set of weighted samples and use the laser range finder (LRF) sensor to measurement update. The experiment results illustrate the effectivity and robust of MCL application for our service robot.
Keywords :
Monte Carlo methods; laser ranging; mobile robots; path planning; position control; service robots; Monte Carlo localization; indoor environment; laser range finder; particle-based density representation; position estimation; probabilistic robotics techniques; service robot; Intelligent robots; Mobile robots; Monte Carlo methods; Notice of Violation; Reliability engineering; Research and development; Robot kinematics; Robot sensing systems; Service robots; USA Councils;
Conference_Titel :
Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-0912-9
Electronic_ISBN :
978-1-4244-0912-9
DOI :
10.1109/IROS.2007.4399409
