Mobile robot control in dynamic environments based on hybrid intelligent system

Author

Zhuang, Xiaodong ; Meng, Qingchun ; Yang, Shaojun

Author_Institution

Intelligent Control Lab., Ocean Univ. of Qingdao, Shandong, China

Volume

3

fYear

2002

fDate

6-9 Oct. 2002

Abstract

A hybrid intelligent control system is proposed for robot navigation. Fuzzy modelization and planning is combined with reinforcement learning to perform robust and optimal control. Fuzzy modelization and planning is efficient, but it lacks self-adaptability. Learning control can obtain the optimal control policy by on-line learning, but it takes long time for the strategy to converge. The hybrid method obtains the advantages of both and has better control performance than either of them. In the computer simulation experiment, the hybrid intelligent method can perform efficient and optimal control for robot navigation in dynamic environments.

Keywords

intelligent control; learning (artificial intelligence); mobile robots; optimal control; path planning; robust control; fuzzy modelization; hybrid intelligent control; hybrid method; learning control; optimal control; planning; reinforcement learning; robot navigation; robust control; Control systems; Fuzzy control; Hybrid intelligent systems; Intelligent control; Intelligent robots; Learning; Mobile robots; Navigation; Optimal control; Robot control;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 2002 IEEE International Conference on

ISSN

1062-922X

Print_ISBN

0-7803-7437-1

Type

conf

DOI

10.1109/ICSMC.2002.1176063

Filename

1176063