Simultaneous localization and map building based on improved particle filter in grid map

Author

Kun Wang ; Liying Su ; Shucai Wang ; Yueqing Yu

Author_Institution

Coll. of Mech. Eng. & Appl. Electron. Technol., Beijing Univ. of Technol., Beijing, China

Volume

2

fYear

2011

fDate

12-14 Aug. 2011

Firstpage

963

Lastpage

966

Abstract

The ability to simultaneous localization and precise mapping is a predetermination of autonomous robots. But because of the unknown location, the unpredictable environment information, the method of simultaneous localization and map building based on improved Particle Filter in grid map is presented to solve these uncertain problems. The distribution over robot poses and map information is estimated with Bayes´ rules and the improved Particle Filter respectively. The simulation result shows the method reduces the complexity of the data and enhances the real-time performance of the improved algorithm. With the method, the robot localizes itself accurately as well as builds grid map with higher accuracy. The proposed algorithm is effective and reliable to realize simultaneous localization and mapping.

Keywords

Bayes methods; SLAM (robots); mobile robots; particle filtering (numerical methods); pose estimation; Bayes rules; autonomous robots; grid map; improved particle filter; robot pose estimation; simultaneous localization and map building; uncertain problems; Mobile robots; Particle filters; Real time systems; Robot kinematics; Simultaneous localization and mapping; Improved Particle Filter; MSRDS; SLAM; grid map; mobile robot;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on

Conference_Location

Harbin, Heilongjiang, China

Print_ISBN

978-1-61284-087-1

Type

conf

DOI

10.1109/EMEIT.2011.6023255

Filename

6023255