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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kovotsky, L., Baillargeon, R.: The development of calibration-based reasoning about collision events in young infants. Cognition, Vol 67 (1998), 311–351. Elsevier
Spelke, E.S.: Initial Knowledge: six suggestions. Cognition,Vol 50 (1994), 431–445. Elsevier
Spelke, E.S., Breinlinger, K., Macomber, J., Jacobsen, K.: Origins of Knowledge. Psychological Review, Vol 99 (1992), 605–632.
Rizzolatti, G., Fadiga, L., Gallese, V., Fogassi, L.: Premotor cortex and the recognition of motor actions. Cognitive Brain Research, Vol 3 (1996), 131–141. Elsevier
Metta, Panerai, Manzotti, Sandini: Babybot: an artificial developing robotic agent. From Animals to Animats: The sixth International Conference on the simulation of Adaptive Behavior. (2000)
Sandini, G., Tagliasco, V.: An Anthropomorphic Retina-like Structure for Scene Analysis. Computer Vision, Graphics and Image Processing, Vol 14(3) (1980), 365–372
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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. https://doi.org/10.1007/3-540-36181-2_57
Download citation
DOI: https://doi.org/10.1007/3-540-36181-2_57
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00174-4
Online ISBN: 978-3-540-36181-7
eBook Packages: Springer Book Archive