Recognizing 3D Objects Using Tactile Sensing and Curve Invariants

Abstract

A general paradigm for recognizing 3D objects is offered, and applied to some geometric primitives (spheres, cylinders, cones, and tori). The assumption is that a curve on the surface, or a pair of intersecting curves, has been measured with high accuracy (for instance, by a sensory robot). Differential invariants of the curve(s) are then used to recognize the surface. The motivation is twofold: the output of some devices is not surface range data, but such curves. Also, a considerable speedup is obtained by using curve data, as opposed to surface data which usually contains a much higher number of points. We survey global, algebraic methods for recognizing surfaces, and point out their limitations. After introducing some notions from differential geometry and elimination theory, the differential and "semi-differential" approach to the problem is described, and novel invariants which are based on the curve's curvature and torsion are derived.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1997
Accession Number
ADA353693

Entities

People

  • David Keren
  • Ehud Rivlin
  • Han Shimshoni
  • Isaac Weiss

Organizations

  • University of Haifa

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Computer Science
  • Computer Vision
  • Computers
  • Curvature
  • Databases
  • Differential Geometry
  • Eigenvalues
  • Elimination
  • Geometry
  • Object Recognition
  • Recognition
  • Shape
  • Two Dimensional

Fields of Study

  • Computer science
  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Graph Algorithms and Convex Optimization.
  • Systems Analysis and Design

Technology Areas

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