Title :
Mobile robot global localization using particle filters
Author :
Cen, Guanghui ; Matsuhira, Nobuto ; Hirokawa, Junko ; Ogawa, Hideki ; Hagiwara, Ichiro
Author_Institution :
Dept. of Mech. Sci. & Eng., Tokyo Inst. of Technol., Tokyo
Abstract :
Mobile robot global localization is the problem of determining a robotpsilas pose in an environment by using sensor data, when the initial position is unknown. Particle filter based Probabilistic algorithm called Monte Carlo localization is the current popular approach to solve the robot localization problem. In this paper we introduce the multi-sensor based Monte Carlo Localization (MCL) method which represents a robotpsilas belief by a set of weighted samples and use the laser range finder (LRF) sensor to measurement update. We also proposed likelihood based particle filter to solve the kidnapped problem. The experiment results illustrate the efficiency and robustness of particle filter approach for our mobile robot.
Keywords :
Monte Carlo methods; laser ranging; mobile robots; particle filtering (numerical methods); probability; sensor fusion; Monte Carlo localization; kidnapped problem; laser range finder sensor; mobile robot global localization; multisensor; particle filter; probabilistic algorithm; robot pose determination; Automatic control; Control systems; Electronic mail; Mobile robots; Monte Carlo methods; Particle filters; Robot kinematics; Robot sensing systems; Robustness; Spatial resolution; Global Localization; Likelihood; Mobile Robot; Particle Filter;
Conference_Titel :
Control, Automation and Systems, 2008. ICCAS 2008. International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-89-950038-9-3
Electronic_ISBN :
978-89-93215-01-4
DOI :
10.1109/ICCAS.2008.4694593
