Real-Time Vergence Control for Binocular Robots

Abstract

In binocular systems, vergence is the process of adjusting the angle between the eyes (or cameras) so that both eyes are directed at the same world point. Its utility is most obvious for foveate systems such as the human visual system, but it is a useful strategy for non-foveate binocular robots as well. This paper discusses the vergence problem and outlines a general approach to vergence control, consisting of a control loop driven by an verge the eyes of the Rochester Robot in real time. Vergence error is estimated with the cepstral disparity filter. The cepstral filter is analyzed, and it is shown in this application to be equivalent to correlation with an adaptive prefilter; carrying this idea to its logical conclusion converts the cepstral filter into phase correlation. The demonstration system uses a PD controller in cascade with the error estimator. An efficient real-time implementation of the error estimator is discussed, and empirical measurements of the performance of both the disparity estimator and the overall system are presented. (sdw)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1990
Accession Number
ADA228817

Entities

People

  • David J. Coombs
  • Thomas J. Olson

Organizations

  • University of Rochester

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Automata Theory
  • Computations
  • Computer Languages
  • Computer Science
  • Computer Vision
  • Computers
  • Control Systems
  • Digital Signal Processing
  • Estimators
  • Eye Movements
  • Frequency
  • Image Processing
  • Neural Networks
  • Power Spectra
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Human-Computer Interaction (HCI).
  • Robotics and Automation.

Technology Areas

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