Robust feature extraction and control design for autonomous grasping and mobile manipulation

Kai-Tai Song*, Che Hao Chang, Chia How Lin

*Corresponding author for this work

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

6 Scopus citations

Abstract

This paper presents a novel design of visual servo control of a mobile manipulator for autonomous grasping of a target object. In this design, scale invariant feature transform (SIFT) algorithm is adopted to search and recognize the object to grasp. Random sample consensus (RANSAC) algorithm is used to remove outliers and find the refined homography matrix between database and current image. Robust feature matching provides reliable feature points to the image-based visual servo control loop. Experimental results show that the mobile manipulator can find and grasp a target object autonomously using the proposed method.

Original languageEnglish
Title of host publication2010 International Conference on System Science and Engineering, ICSSE 2010
Pages445-450
Number of pages6
DOIs
StatePublished - 11 Oct 2010
Event2010 International Conference on System Science and Engineering, ICSSE 2010 - Taipei, Taiwan
Duration: 1 Jul 20103 Jul 2010

Publication series

Name2010 International Conference on System Science and Engineering, ICSSE 2010

Conference

Conference2010 International Conference on System Science and Engineering, ICSSE 2010
CountryTaiwan
CityTaipei
Period1/07/103/07/10

Keywords

  • Feature extraction
  • Image recognition
  • Mobile robot
  • Visual servo control

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