Towards Manipulation-Driven Vision

Abstract

For the purposes of manipulation, the authors would like to know what parts of the environment are physically coherent ensembles, that is, which parts will move together, and which parts are more or less independent. It takes a great deal of experience before this judgement can be made from purely visual information. This paper develops active strategies for acquiring that experience through experimental manipulation, using tight correlations between arm motion and optic flow to detect both the art itself and the boundaries of objects with which it comes into contact. The number of papers written on techniques for visual segmentation is vast. Methods for characterizing the shape of an object through tactile information also are being developed, such as shape from probing or pushing. But while it has long been known that motor strategies can aid vision, work on active vision has focused almost exclusively on moving cameras. There is much to be said about bringing a manipulator into the equation, as the authors have shown in this paper. Many variants and extensions to the experimental "poking" strategy explored here are possible.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2001
Accession Number
ADA434691

Entities

People

  • Giorgio Metta
  • Paul M. Fitzpatrick

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automata Theory
  • Boundaries
  • Brain
  • Cognitive Neuroscience
  • Cognitive Science
  • Computer Languages
  • Computer Science
  • Computer Vision
  • Computers
  • Electrical Engineering
  • Neural Networks
  • Neurosciences
  • Object Recognition
  • Psychology
  • Reliability

Readers

  • Computer Vision.
  • Robotics and Automation.
  • Theoretical Analysis.