Robotic Manipulator Control Performance Evaluation.

Abstract

A robotic manipulator dynamically based controller performance baseline is established by the creation and utilization of a hierarchical robotic evaluation environment. Creation of a hierarchical robotic evaluation environment provides an original solution to the problems that previously constrained real-time evaluation of modern manipulator control schemes. Utilization of that environment fulfills the application of proposed theories. The performance baseline is established by simulated and experimental evaluation of feedforward dynamics and feedback loop design for joint motion high speed trajectory tracking robot control. The real-time performance produced by application of all proposed robotic control techniques to harmonic and gear driven manipulators can be extrapolated from the baseline. A feedforward loop composed of uncoupled inertia and gravity dynamics exhibited the best tracking accuracy. Forces unmodeled by those dynamics can be effectively treated as disturbances to the feedback loop. Dynamic based control techniques exhibited the potential to control high speed gross motion of a manipulator without additional sensor devices.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1986
Accession Number
ADA172919

Entities

People

  • Michael B. Leahy Jr.

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Assembly Languages
  • Centrifugal Force
  • Computational Complexity
  • Computations
  • Computer Programming
  • Computer Programs
  • Computers
  • Control Systems
  • Equations
  • Language
  • Measurement
  • Operating Systems
  • Probability
  • Probability Distributions
  • Programming Languages
  • Random Variables

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control