Biologically Motivated Computer Vision

Volume 2525 of the series Lecture Notes in Computer Science pp 567-575


Learning to Act on Objects

  • Lorenzo NataleAffiliated withLIRA Lab, DIST. Univ of Genova, Italy
  • , Sajit RaoAffiliated withLIRA Lab, DIST. Univ of Genova, Italy
  • , Giulio SandiniAffiliated withLIRA Lab, DIST. Univ of Genova, Italy

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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.