Advertisement

Distributed Control of Complex Arm Movements

Reaching Around Obstacles and Scratching Itches
  • David Zipser
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7375)

Abstract

This paper presents a computational theory for generating the complicated arm movements needed for tasks such as reaching while avoiding obstacles, or scratching an itch on one arm with the other hand. The required movements are computed using many control units with virtual locations over the entire surface of the arm and hand. These units, called brytes, are like little brains, each with its own input and output and its own idea about how its virtual location should move. The paper explains how a previously developed gradient method for dealing with ill-posed multi-joint movements [1] can be applied to large numbers of spatially distributed controllers. Simulations illustrate when the arm movements are successful and when and why they fail. Many of these failures can be avoided by a simple method that adds intermediate reaching goals. The theory is consistent with a number of existing experimental observations.

Keywords

Joint Angle Movement Vector Obstacle Avoidance Scene Representation Egocentric Reference Frame 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Torres, E.B., Zipser, D.: Reaching to Grasp with a Multi-jointed Arm (I): A Computational Model. Journal of Neurophysiology 88, 1–13 (2002)CrossRefGoogle Scholar
  2. 2.
    Zipser, D.: Brytes or How to make big brains out of lots of small brains, parts 1, 2, 3. Redwood Center for Theoretical Neuroscience (2009, 2010), archive.org/search.php?query=david+zipser
  3. 3.
    Todorov, E.: Optimality principles in sensorimotor control. Nature Neuroscience 7, 907–915 (2006)CrossRefGoogle Scholar
  4. 4.
    Graziano, et al.: Coding of visual space by premotor neurons. Science 11, 1054–1057 (1994)CrossRefGoogle Scholar
  5. 5.
    Ferraina, S., Brunamonti, E., Giusti, M.A., Costa, S., Genovesio, A., Caminiti, R.: Reaching in Depth: Hand Position Dominates over Binocular Eye Position in the Rostral SuperioParietal Lobule. The Journal of Neuroscience 29(37), 11461 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • David Zipser
    • 1
  1. 1.Department of Cognitive Science, UCSD and Visiting ScholarUC BerkeleyBerkeleyUSA

Personalised recommendations