Object grasping of a mobile robot using image features and virtual points

Kai-Tai Song*, Hong Tze Chen

*Corresponding author for this work

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

3 Scopus citations

Abstract

This paper presents a novel method of autonomous grasping design for a mobile manipulator, such that the robot can find and grasp a target object in a complex environment. Scale invariant feature transform (SIFT) algorithm is adopted to search and recognize features of the object to be grasped. Histogram-enhanced feature matching (HEFM) is developed to obtain depth estimate and reject unreliable feature points in order to improve the feature matching accuracy. The concept of virtual points is proposed to facilitate image-based visual servo controller design. Experimental results of autonomous object grasping validate the proposed method.

Original languageEnglish
Title of host publicationICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
Pages4370-4375
Number of pages6
StatePublished - 1 Dec 2009
EventICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan
Duration: 18 Aug 200921 Aug 2009

Publication series

NameICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings

Conference

ConferenceICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
CountryJapan
CityFukuoka
Period18/08/0921/08/09

Keywords

  • Image recognition
  • Mobile robots
  • Visual servo control

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