Cooperative motion control of 2-DOF robot arms by recurrent neural network

Yingda Dai; Masami Konishi; Jun Imai; Tatsushi Nishi

Cooperative motion control of 2-DOF robot arms by recurrent neural network

Yingda Dai, Masami Konishi, Jun Imai, Tatsushi Nishi

Research output: Contribution to conference › Paper › peer-review

Abstract

Recently Robotics has been applied in many fields. Robot designers have focused the applications that from the standardization factory, in which all kinds of industrial robots run repeatedly, to the social welfare field, where there is no standard but need higher safety. However, according to today's technology, the ability that robot can quickly enough to adapt a new environment is still worse by far than human. The intent of this paper is to show the control plan for two degrees of freedom (2-DOF) dexterous robot arms both of these two robot arms operate in operation under the realistic environment. This control system can be synthesized quickly by neural network algorithms.

Original language	English
Pages	745-750
Number of pages	6
Publication status	Published - Dec 1 2005
Event	SICE Annual Conference 2005 - Okayama, Japan Duration: Aug 8 2005 → Aug 10 2005

Other

Other	SICE Annual Conference 2005
Country/Territory	Japan
City	Okayama
Period	8/8/05 → 8/10/05

Keywords

Cooperation Control
Neural Network
Robot Arm
Self-learning

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

Cite this

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title = "Cooperative motion control of 2-DOF robot arms by recurrent neural network",

abstract = "Recently Robotics has been applied in many fields. Robot designers have focused the applications that from the standardization factory, in which all kinds of industrial robots run repeatedly, to the social welfare field, where there is no standard but need higher safety. However, according to today's technology, the ability that robot can quickly enough to adapt a new environment is still worse by far than human. The intent of this paper is to show the control plan for two degrees of freedom (2-DOF) dexterous robot arms both of these two robot arms operate in operation under the realistic environment. This control system can be synthesized quickly by neural network algorithms.",

keywords = "Cooperation Control, Neural Network, Robot Arm, Self-learning",

author = "Yingda Dai and Masami Konishi and Jun Imai and Tatsushi Nishi",

year = "2005",

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language = "English",

pages = "745--750",

note = "SICE Annual Conference 2005 ; Conference date: 08-08-2005 Through 10-08-2005",

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T1 - Cooperative motion control of 2-DOF robot arms by recurrent neural network

AU - Dai, Yingda

AU - Konishi, Masami

AU - Imai, Jun

AU - Nishi, Tatsushi

PY - 2005/12/1

Y1 - 2005/12/1

N2 - Recently Robotics has been applied in many fields. Robot designers have focused the applications that from the standardization factory, in which all kinds of industrial robots run repeatedly, to the social welfare field, where there is no standard but need higher safety. However, according to today's technology, the ability that robot can quickly enough to adapt a new environment is still worse by far than human. The intent of this paper is to show the control plan for two degrees of freedom (2-DOF) dexterous robot arms both of these two robot arms operate in operation under the realistic environment. This control system can be synthesized quickly by neural network algorithms.

AB - Recently Robotics has been applied in many fields. Robot designers have focused the applications that from the standardization factory, in which all kinds of industrial robots run repeatedly, to the social welfare field, where there is no standard but need higher safety. However, according to today's technology, the ability that robot can quickly enough to adapt a new environment is still worse by far than human. The intent of this paper is to show the control plan for two degrees of freedom (2-DOF) dexterous robot arms both of these two robot arms operate in operation under the realistic environment. This control system can be synthesized quickly by neural network algorithms.

KW - Cooperation Control

KW - Neural Network

KW - Robot Arm

KW - Self-learning

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UR - http://www.scopus.com/inward/citedby.url?scp=33645313492&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:33645313492

SP - 745

EP - 750

T2 - SICE Annual Conference 2005

Y2 - 8 August 2005 through 10 August 2005

ER -

Cooperative motion control of 2-DOF robot arms by recurrent neural network

Abstract

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Keywords

ASJC Scopus subject areas

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