Learning to Act on Objects

  • Lorenzo Natale
  • Sajit Rao
  • Giulio Sandini
Conference paper

DOI: 10.1007/3-540-36181-2_57

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)
Cite this paper as:
Natale L., Rao S., Sandini G. (2002) Learning to Act on Objects. In: Bülthoff H.H., Wallraven C., Lee SW., Poggio T.A. (eds) Biologically Motivated Computer Vision. BMCV 2002. Lecture Notes in Computer Science, vol 2525. Springer, Berlin, Heidelberg

Abstract

In biological systems vision is always in the context of a particular body and tightly coupled to action. Therefore it is natural to consider visuo-motor methods (rather than vision alone) for learning about objects in the world. Indeed, initially it may be necessary to act on something to learn that it is an object! Learning to act involves not only learning the visual consequences of performing a motor action, but also the other direction, i.e. using the learned association to determine which motor action will bring about a desired visual condition.

In this paper we show how a humanoid robot uses its arm to try some simple pushing actions on an object, while using vision and proprioception to learn the effects of its actions. We show how the robot learns a mapping between the initial position of its arm and the direction the object moves in when pushed, and then how this learned mapping is used to successfully position the arm to push/pull the target object in a desired direction.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Lorenzo Natale
    • 1
  • Sajit Rao
    • 1
  • Giulio Sandini
    • 1
  1. 1.LIRA LabDIST. Univ of Genova, ItalyGenovaItaly

Personalised recommendations