Parameter Identification and Adaptive Control of Cooperating Robots

Abstract

The major aim of this research project is to study the dynamics and control problems related to open and closed chain robotic systems. The research effort investigates aspects of load sharing and internal force control in case of closed chain manipulation which has been generally ignored thus far in current literature. This research demonstrates a practical solution to dual-arm continuous control problem for heavy link industrial manipulators such as IBM 7540. Integration of vision and force sensors in dual- arm workcells is also described. Analytical and empirical solutions using pseudo-inverse and back error propagation are developed. Insightful study of back error propagation indicates the relationship of neural algorithms to nonlinear least squares fit and established notions in estimation theory. A novel approach to camera- calibration and vision guided robot path-tracking is also advanced. Detailed results and discussions are included in the publications cited in the report.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1992
Accession Number
ADA256984

Entities

People

  • Devendra P. Garg

Organizations

  • Duke University

Tags

Communities of Interest

  • Autonomy
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Automation
  • Control Systems
  • Cooperative Control
  • Dynamics
  • Engineering
  • Manufacturing
  • Materials Science
  • Mechanical Engineering
  • Neural Networks
  • Payload
  • Robotics
  • Simulations
  • Supervisory Control
  • Systems Science
  • Theses
  • Trajectories

Readers

  • Calculus or Mathematical Analysis
  • Robotics and Automation.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy