Pose Determination of a Grasped Object Using Limited Sensing

Abstract

This report explores methods for determining the pose of a grasped object using only limited sensor information. The problem of pose determination is to find the position of an object relative to the hand. The information is useful when grasped objects are being manipulated. The problem is hard because of the large space of grasp configurations and the large amount of uncertainty inherent in dexterous hand control. By studying limited sensing approaches, the problem's inherent constraints can be better understood. This understanding helps to show how additional sensor data can be used to make recognition methods more effective and robust. This report introduces three approaches for pose determination. The first is based on an interpretation tree representation of possible object feature placements on finger segments. The tree is built in real-time based on the hand's configuration and an object model. The method is highly efficient as it only explores consistent paths through the tree.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
May 01, 1991
Accession Number
ADA259496

Entities

People

  • David M. Siegel

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Cyber
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Computer Science
  • Computer Vision
  • Computers
  • Coordinate Systems
  • Detection
  • Detectors
  • Electrical Engineering
  • Joints (Anatomy)
  • Materials
  • Measurement
  • Object Recognition
  • Operating Systems
  • Recognition
  • Simulators
  • Strain Gages

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Robotics and Automation.

Technology Areas

  • Space
  • Space - Space Objects