Simultaneously learning to recognize and control a low-cost robotic arm

  • Authors:
  • Fredrik Larsson;Erik Jonsson;Michael Felsberg

  • Affiliations:
  • Computer Vision Laboratory, Department of Electrical Engineering, Linköping University, 581 83 Linköping, Sweden;Computer Vision Laboratory, Department of Electrical Engineering, Linköping University, 581 83 Linköping, Sweden;Computer Vision Laboratory, Department of Electrical Engineering, Linköping University, 581 83 Linköping, Sweden

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2009

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Abstract

In this paper, we present a visual servoing method based on a learned mapping between feature space and control space. Using a suitable recognition algorithm, we present and evaluate a complete method that simultaneously learns the appearance and control of a low-cost robotic arm. The recognition part is trained using an action precedes perception approach. The novelty of this paper, apart from the visual servoing method per se, is the combination of visual servoing with gripper recognition. We show that we can achieve high precision positioning without knowing in advance what the robotic arm looks like or how it is controlled.