Robot Arm Control Exploiting Natural Dynamics

Abstract

This thesis presents an approach to robot arm control exploiting natural dynamics. The approach consists of using a compliant arm whose joints are controlled with simple non-linear oscillators. The arm has special actuators which makes it robust to collisions and gives it a smooth compliant motion. The oscillators produce rhythmic commands of the joints of the arm, and feedback of the joint motions is used to modify the oscillator behavior. The oscillators enable the resonant properties of the arm to be exploited to perform a variety of rhythmic and discrete tasks. These tasks include tuning into the resonant frequencies of the arm itself, juggling, turning cranks, playing with a Slinky toy, sawing wood, throwing balls, hammering nails and drumming. For most of these tasks, the controllers at each joint are completely independent, being coupled by mechanical coupling through the physical arm of the robot. The thesis shows that this mechanical coupling allows the oscillators to automatically adjust their commands to be appropriate for the arm dynamics and the task. This coordination is robust to large changes in the oscillator parameters, and large changes in the dynamic properties of the arm.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1999
Accession Number
ADA434727

Entities

People

  • Matthew M. Williamson

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Actuators
  • Collision Avoidance
  • Computations
  • Computer Science
  • Control Systems
  • Detectors
  • Electrical Engineering
  • Engineering
  • Equations
  • Firing Rate
  • Frequency Response
  • Joints (Anatomy)
  • Linear Systems
  • Literature Surveys
  • Mechanical Properties
  • Neural Networks
  • Resonant Frequency

Readers

  • Robotics and Automation.
  • Thermal Physics or Thermal Science.

Technology Areas

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