Enabling grasping of unknown objects through a synergistic use of edge and surface information

Gert Kootstra*, Mila Popović, Jimmy Alison Jørgensen, Kamil Kuklinski, Konstantsin Miatliuk, Danica Kragic, Norbert Krüger

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Scopus)

Abstract

Grasping unknown objects based on visual input, where no a priori knowledge about the objects is used, is a challenging problem. In this paper, we present an Early Cognitive Vision system that builds a hierarchical representation based on edge and texture information which provides a sparse but powerful description of the scene. Based on this representation, we generate contour-based and surface-based grasps. We test our method in two real-world scenarios, as well as on a vision-based grasping benchmark providing a hybrid scenario using real-world stereo images as input and a simulator for extensive and repetitive evaluation of the grasps. The results show that the proposed method is able to generate successful grasps, and in particular that the contour and surface information are complementary for the task of grasping unknown objects. This allows for dealing with rather complex scenes.

Original languageEnglish
Pages (from-to)1190-1213
Number of pages24
JournalInternational journal of robotics research
Volume31
Issue number10
DOIs
Publication statusPublished - 1 Sep 2012
Externally publishedYes

Keywords

  • dexterous hands
  • grasping unknown objects
  • vision-based grasping
  • visual scene representation

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