Learning Humanoid Arm Gestures

Abstract

While biological motion control systems are generally simple and robust, their robotic analogs tend to be just the opposite. While functions has driven many of the colorful architectures to date, we feel that a biologically-inspired system for monitoring the energy consumption of virtual muscles can lead to the development of more humanoid motion and gesture.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA434138

Entities

People

  • Bryan G. Adams

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Chemical Reactions
  • Computer Science
  • Control
  • Control Systems
  • Electrical Engineering
  • Energy Consumption
  • Energy Production
  • Engineering
  • Environmental Monitoring
  • Feedback
  • Learning
  • Mechanical Impedance
  • Metabolism
  • Robots
  • Simulations
  • Systems Biology

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Neuroscience

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy