Experimental Comparison of Extended Kalman and Particle Filter in Mobile Robotic Localization

Author

Angel, Julián M. ; De la Rosa, Fernando

Author_Institution

Comput. Sci. & Syst. Dept., Univ. de los Andes, Bogota, Colombia

fYear

2009

fDate

22-25 Sept. 2009

Firstpage

157

Lastpage

162

Abstract

This paper presents an implementation and comparison between odometry and probabilistic algorithms for the mobile robot localization problem in indoor environments.The hardware and software tools used for the experiments are briefly described. Also, a software architecture is proposed to make easier the development of computer applications including the tested algorithms which are used to get the results to compare.

Keywords

Kalman filters; distance measurement; mobile robots; particle filtering (numerical methods); probability; software architecture; extended Kalman; indoor environment; mobile robot localization problem; mobile robotic localization; odometry; particle filter; probabilistic algorithm; software architecture; Automotive engineering; Computer science; Electronic mail; Hardware; Indoor environments; Kalman filters; Mobile computing; Mobile robots; Particle filters; Software tools; Bayes Filter; Kalman Filter; Localization; Mobile Robotics; Odometry; Particle Filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Robotics and Automotive Mechanics Conference, 2009. CERMA '09.

Conference_Location

Cuernavaca, Morelos

Print_ISBN

978-0-7695-3799-3

Type

conf

DOI

10.1109/CERMA.2009.32

Filename

5341995