Implementations of robot visual servo by learning

Zhao Qingjie*, Deng Hongbin, Duan Xingguang, Hu Haidong

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper uses learning methods to acquire image features from eigen subspace transform and acquire the nonlinear relation between image features and robot control commands through a wavelet function neural network. The stages include data-sampling, model-learning, and robot visual servo. The servo stage consists of acquiring an image, transforming it into image features, computing robot joints by the trained neural network, communicating and controlling the robot to move, until the desired image features are achieved. Implementations of related algorithms are given. Experiments are carried out successfully on a real robot-vision system.

Original languageEnglish
Title of host publication3rd International Conference on Innovative Computing Information and Control, ICICIC'08
DOIs
Publication statusPublished - 2008
Event3rd International Conference on Innovative Computing Information and Control, ICICIC'08 - Dalian, Liaoning, China
Duration: 18 Jun 200820 Jun 2008

Publication series

Name3rd International Conference on Innovative Computing Information and Control, ICICIC'08

Conference

Conference3rd International Conference on Innovative Computing Information and Control, ICICIC'08
Country/TerritoryChina
CityDalian, Liaoning
Period18/06/0820/06/08

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