Monocameral Visual Recognition of Marcus Hand Postures for Personal Robotic Assistants

Abstract

The postures recognition is the first step for the gestures tracking of an artificial or a natural hand. In this article, we show a visuo-motor tracking of mobile hand configurations, which is based on symbolic representations able of supporting the biomechanical and perceptual information relative to evolving postures. After recognition, we have a virtual skeleton to identify simulated artificial hands. Such postures identification is adapted to an artificial Marcus hand developed as a human prosthesis. Nevertheless, the complex mechatronic device, this symbolic representation allows the visual identification and tracking of hand points of interest, such as tactile sensors and finger joints. In this way, a feedback for the perception-action cycle is obtained to improve the man- machine interaction in Personal Robotics, with special regard to the assistance of disabled people.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412553

Entities

People

  • C. Laschi
  • J. Finat
  • M. Gonzalo-tasis
  • P. Dario

Organizations

  • University of Valladolid

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Automata Theory
  • Boundaries
  • Cognitive Systems Engineering
  • Computer Science
  • Computer Stereo Vision
  • Computers
  • Data Analysis
  • Identification
  • Mathematical Models
  • Models
  • Operating Systems
  • Recognition
  • Robotics
  • Robots
  • Topology
  • Visual Servoing

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Vision.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • Autonomy