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
ARKIN, RC
[J]. 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
Koczy, LT
Hirota, K
[J]. 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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