Visual Feedback Control of a Robot in an Unknown Environment (Learning Control Using Neural Networks).

Visual Feedback Control of a Robot in an Unknown Environment (Learning Control Using Neural Networks).

by Saeid Nahavandi, Xiao Nan-Feng

Type Book
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Summary

In this chapter, a visual feedback control approach based on neural network is presented for a robot with a camera installed on its end-effecter to trace an object in an unknown environment. Firstly, the necessary conditions for mapping the image features of the object to be traced to the joint angles of the robot are derived. Secondly, a method is proposed to generate a goal trajectory of the robot by measuring the image feature parameters of the object to be traced. Thirdly, a multilayer neural network is used to learn off-line the mapping in order to produce on line the reference inputs for controlling the robot. Fourthly, a multilayer neural network-based learning controller is designed for the compensation the nonlinear robotic dynamics. Lastly, the effectiveness of.

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Titles

  • Full Title: Visual Feedback Control of a Robot in an Unknown Environment (Learning Control Using Neural Networks).

Notes

  • En.

Identifiers

  • Isbns: 3866112858; 9783866112858
  • Oclc Number: (OCoLC)884021595

Publication Statement

  • Publisher: INTECH Open Access Publisher
  • Date: 2006

Physical Description

  • Extent: 1 online resource

Summary

  • In this chapter, a visual feedback control approach based on neural network is presented for a robot with a camera installed on its end-effecter to trace an object in an unknown environment. Firstly, the necessary conditions for mapping the image features of the object to be traced to the joint angles of the robot are derived. Secondly, a method is proposed to generate a goal trajectory of the robot by measuring the image feature parameters of the object to be traced. Thirdly, a multilayer neural network is used to learn off-line the mapping in order to produce on line the reference inputs for controlling the robot. Fourthly, a multilayer neural network-based learning controller is designed for the compensation the nonlinear robotic dynamics. Lastly, the effectiveness of.

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