Rough level planning method for a robot using SOFM neural network

Kimmo Pulakka; Veli Kujanpää

Rough level planning method for a robot using SOFM neural network

Kimmo Pulakka
, Veli Kujanpää

Tampere University of Technology (TUT)

Research output: Contribution to journal › Article › Scientific › peer-review

6 Citations (Scopus)

Abstract

In this paper a path planning method for off-line programming of a joint robot is described. The method can automatically choose the easiest and safest route for an industrial robot from one position to another. The method is based on the use of a Self Organised Feature Map (SOFM) neural network. By using the SOFM neural network the method can adapt to different working environments of the robot. According to test results one can conclude that the SOFM neural network is a useful tool for the path planning problem of a robot.

Original language	English
Pages (from-to)	415-423
Journal	Robotica
Volume	16
Issue number	4
Publication status	Published - 1998
MoE publication type	Not Eligible

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This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

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https://www.cambridge.org/core/journals/robotica/article/rough-level-path-planning-method-for-a-robot-using-sofm-neural-network/9B570408859D406A8146B0AEAE20ED0C

Cite this

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title = "Rough level planning method for a robot using SOFM neural network",

abstract = "In this paper a path planning method for off-line programming of a joint robot is described. The method can automatically choose the easiest and safest route for an industrial robot from one position to another. The method is based on the use of a Self Organised Feature Map (SOFM) neural network. By using the SOFM neural network the method can adapt to different working environments of the robot. According to test results one can conclude that the SOFM neural network is a useful tool for the path planning problem of a robot.",

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year = "1998",

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AU - Pulakka, Kimmo

AU - Kujanpää, Veli

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AB - In this paper a path planning method for off-line programming of a joint robot is described. The method can automatically choose the easiest and safest route for an industrial robot from one position to another. The method is based on the use of a Self Organised Feature Map (SOFM) neural network. By using the SOFM neural network the method can adapt to different working environments of the robot. According to test results one can conclude that the SOFM neural network is a useful tool for the path planning problem of a robot.

M3 - Article

SN - 0263-5747

VL - 16

SP - 415

EP - 423

JO - Robotica

JF - Robotica

IS - 4

ER -

Rough level planning method for a robot using SOFM neural network

Abstract

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