Fuzzy Map Matching for the Atlas SLAM of Mobile Robots

Author

Dai, Xuefeng ; Yao, Zhifeng ; Ning, Xiaomei

Author_Institution

Coll. of Comput. & Control Eng., Qiqihar Univ., Qiqihar, China

fYear

2010

fDate

22-23 May 2010

Firstpage

1

Lastpage

4

Abstract

A novel approach of reducing computation complexity for simultaneous localization and mapping (SLAM) of mobile robots, which based on self-organizing fuzzy neural networks (SONN) was proposed in this paper. The matching component for local maps in the atlas SLAM system is replaced by an SONN. Our approach is superior to the original one by taking all of the feature parameters in a local map instead of a set of map signature elements. In addition, the computation cost which is required to determine the active local map and to close loop was reduced to a reasonable size.

Keywords

closed loop systems; computational complexity; fuzzy neural nets; mobile robots; Atlas simultaneous localization and mapping; active local map; close loop; computation complexity; fuzzy map matching; map signature elements; mobile robots; self-organizing fuzzy neural networks; Computer networks; Educational institutions; Educational technology; Fuzzy control; Fuzzy neural networks; Large-scale systems; Mobile robots; Neurons; Simultaneous localization and mapping; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-5872-1

Electronic_ISBN

978-1-4244-5874-5

Type

conf

DOI

10.1109/IWISA.2010.5473347

Filename

5473347