General guiding model for mobile robots and its complexity reduced neuro-fuzzy approximation

被引：12

作者：

Baranyi, P ^{[1
]}

Nagy, I ^{[1
]}

Korondi, P ^{[1
]}

Hashimoto, H ^{[1
]}

机构：

[1] Tech Univ Budapest, Dept Telcomm & Telemat, H-1111 Budapest, Hungary

来源：

NINTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2000), VOLS 1 AND 2 | 2000年

关键词：

D O I：

10.1109/FUZZY.2000.839191

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The development of techniques for autonomous mobile robot navigation has been in focus for several decades [1,]. The main objectives of this paper are twofold. One is to extend the potential based guiding (PBG) model to a more general form that can be approximated by a common type neuro-fuzzy algorithm. The extended model eliminates the strongly alternating behavior of PBG. The second is to propose a computation complexity reduction method for the general form of the neuro-fuzzy technique. Same examples are given to show the effectiveness of the extended guiding model.

引用

页码：1029 / 1032

页数：4

共 14 条

[1] MOTOR SCHEMA - BASED MOBILE ROBOT NAVIGATION [J].

ARKIN, RC .

INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 1989, 8 (04) :92-112

[2]

BRONSTEIN J, 1991, IEEE J ROBOTIC AUTOM, V7, P278

[3]

BROOKS R, 1991, 1293 MIT

[4]

FUKUDA T, 1999, IEEE INT FUZZ SYST C, V3, P1203

[5]

HOFFMANN F, 1999, FUZZY LOGIC TECHNIQU

[6]

KLEMENT EP, UNPUB INT J GEN SYST

[7] Size reduction by interpolation in fuzzy rule bases [J].

Koczy, LT ;

Hirota, K .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1997, 27 (01) :14-25

[8]

KOCZY LT, 1990, P INT C FL NN IIZUKA

[9]

KUBOTA N, 1999, IEEE INT FUZZ SYST C, V2, P986

[10]

LAMMENS J, 1993, P NATO ASI BIOL TECH

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