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A data-driven grasp planning method based on Gaussian Process Classifier

  • Harbin Institute of Technology

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

Abstract

This paper presents a grasp planning method for grasping novel objects from point clouds provided by the Kinect camera. By applying machine learning, the planning method can generate two points which represent the contact point and direction of grasp. This method is based on three components: 1) grasp configuration which can present the location of contact points and the direction of grasp, 2) features which take force closure and grasp stability into account, and 3) Gaussian Process Classifier which is used to calculate the grasp quality by using the features of each grasp configuration. Two experiments are carried out to verify our method. The results demonstrate that the robot using this approach can successfully grasp objects with partial point clouds.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Mechatronics and Automation, ICMA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2626-2631
Number of pages6
ISBN (Electronic)9781479970964
DOIs
StatePublished - 2 Sep 2015
Event12th IEEE International Conference on Mechatronics and Automation, ICMA 2015 - Beijing, China
Duration: 2 Aug 20155 Aug 2015

Publication series

Name2015 IEEE International Conference on Mechatronics and Automation, ICMA 2015

Conference

Conference12th IEEE International Conference on Mechatronics and Automation, ICMA 2015
Country/TerritoryChina
CityBeijing
Period2/08/155/08/15

Keywords

  • Gaussian Process
  • force-closure
  • grasp planning
  • point clouds
  • robotic grasping

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