Motor Control of a Limb Segment Actuated by Artificial Muscles

Abstract

In this article we present a biologically inspired motor control scheme based on sensory-motor interaction modalities within the Central Nervous System, and its application to the control of a single joint limb segment actuated by two pneumatic McKibben muscles. The embedded Artificial Neural Network (ANN) module's architecture, whose functioning is regulated by reinforcement learning, is similar to the connectivity of cerebellar cortex. Various biologically plausible learning schemes, which enable functional plasticity in the cerebellar cortex, are discussed. The simulation and experimental results are then reported. Keywords - Motor control, brain models, artificial neural networks, reinforcement learning, artificial muscles.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411774

Entities

People

  • B. Tondu
  • C. Darlot
  • S. Eskiizmirliler

Organizations

  • Örebro University

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Amplitude
  • Brain
  • Cells
  • Central Nervous System
  • Cerebellum
  • Climbing
  • Compressed Air
  • Engineering
  • Fungi
  • Image Processing
  • Inner Tubes
  • Learning
  • Nervous System
  • Neural Networks
  • Reinforcement Learning
  • Simulations

Readers

  • Neuroscience
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Neural Networks