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Integration of Visual Cues for Robotic Grasping


Book Chapter


In this paper, we propose a method that generates grasping actions for novel objects based on visual input from a stereo camera. We are integrating two methods that are advantageous either in predicting how to grasp an object or where to apply a grasp. The first one reconstructs a wire frame object model through curve matching. Elementary grasping actions can be associated to parts of this model. The second method predicts grasping points in a 2D contour image of an object. By integrating the information from the two approaches, we can generate a sparse set of full grasp configurations that are of a good quality. We demonstrate our approach integrated in a vision system for complex shaped objects as well as in cluttered scenes.

Author(s): Bergström, Niklas and Bohg, Jeannette and Kragic, Danica
Book Title: Computer Vision Systems
Volume: 5815
Pages: 245-254
Year: 2009
Series: Lecture Notes in Computer Science
Publisher: Springer Berlin Heidelberg

Department(s): Autonomous Motion
Bibtex Type: Book Chapter (incollection)
Paper Type: Conference

DOI: 10.1007/978-3-642-04667-4_25
Language: English
URL: http://dx.doi.org/10.1007/978-3-642-04667-4_25
Attachments: pdf


  title = {Integration of Visual Cues for Robotic Grasping},
  author = {Bergstr{\"o}m, Niklas and Bohg, Jeannette and Kragic, Danica},
  booktitle = {Computer Vision Systems},
  volume = {5815},
  pages = {245-254},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer Berlin Heidelberg},
  year = {2009},
  url = {http://dx.doi.org/10.1007/978-3-642-04667-4_25}