Principal component analysis for 3D-manipulator robot control system

Moussa Hamadache, Jaehoon Kim, Dongik Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


In this paper, a shape recognition technique for a 3-DOF manipulator robot control system is proposed. This work is devised into three parts. First, the shapes were recognized under the Principal Component Analysis (PCA) algorithm and the shape's characteristics (position and orientation) were extracted and stored in the PCA-bases. Second, based on the Graphical User Interface (GUI) tool, a simulation on 3D-space of the 3-DOF manipulator robot was performed. Finally, the PCA-bases were applied as a command-signal to the 3-DOF manipulator robot control system. Several shapes were considered and tested to verify the method.
Original languageEnglish
Title of host publication2012 16th IEEE Mediterranean Electrotechnical Conference
Place of PublicationYasmine Hammamet, Tunisia
PublisherIEEE Xplore
Publication statusPublished - 25 Mar 2012


  • Principal component analysis
  • 3D manipulator robot control system
  • Shape recognition technique
  • Shape extraction
  • Eigenvalues and eigenfunctions
  • Covariance matrix
  • Shape recognition


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