Hierarchical control structure for multisensor object recognition system

Author

Chen Hong ; He Yongbao

Author_Institution

Dept. of Comput. Sci., Fudan Univ., Shanghai, China

Volume

2

fYear

1993

fDate

19-21 Oct. 1993

Firstpage

811

Abstract

Multisensors can be used to overcome problems associated with intelligent object recognition systems. The introduction of multisensors into such a system emphasizes the need for an effective method for combining sensor outputs, and a complicated system requires intelligent control. We propose a hierarchical control structure (HCS) to build a recognition system and introduce a fuzzy neural net (FNN) method to fuse multisensor information. This paper describes the concept of HCS, the derivation of fuzzy rules, the FNN´s construction and training, etc. Then, experimental results involving parts recognition in the application of an assembly robot are presented.<>

Keywords

assembling; fuzzy set theory; image recognition; industrial robots; intelligent control; neural nets; sensor fusion; assembly robot; fuzzy neural net; fuzzy rule derivation; hierarchical control structure; intelligent control systems; multisensor data fusion; multisensor object recognition system; parts recognition; training; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Intelligent control; Intelligent sensors; Intelligent systems; Neural networks; Object recognition; Sensor systems;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on

Conference_Location

Beijing, China

Print_ISBN

0-7803-1233-3

Type

conf

DOI

10.1109/TENCON.1993.320137

Filename

320137