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Bio-inspired Control of Dexterous Manipulation

  • Rosana Matuk Herrera
  • Fabio Leoni
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3809)

Abstract

Robots successfully manipulate objects in controlled environments. However, they fail in unknown environments. Few years old children lift and manipulate unfamiliar objects more dexterously than today’s robots. Therefore, roboticists are looking for inspiration on neurophysiological studies to improve their robotics control models. We present an artificial intelligence control model for dexterous manipulation, and a grip and load force control algorithm, strongly inspired on neurophysiological studies of the human manipulation process.

Keywords

Robotics dexterous manipulation neural networks reinforcement learning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Rosana Matuk Herrera
    • 1
  • Fabio Leoni
    • 2
  1. 1.Department of Computer Science, Facultad de Ciencias Exactas y NaturalesUniversidad de Buenos AiresArgentina
  2. 2.ARTS LabScuola Superiore Sant’AnnaPisaItaly

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