Automatic Identification of Remote Environments and Calibration of Virtual Models.

Abstract

A method is presented to automatically estimate parameters and identify constraints of remote environments in a teleoperated robot system and then to use that information to create virtual models of the remote environment. Such a model can be used in virtual training systems and in teleoperated systems with time delays. In addition, automatic parameter estimation can help the operator to improve task performance time and safety, and to plan object handling strategies. Ideally the system would determine these parameters while normal tasks are performed without interference in task accomplishment. The parameters are of two types: inherent object properties, which include weight, size, coefficient of friction, etc., and object/environment constraint parameters (i.e., parameters describing the trajectory of constrained motion and forces applied by the constraints.) In addition to constraint parameters, constraint identification includes determination of whether the constraint exists and development of the constraint model.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 05, 1997
Accession Number
ADA321016

Entities

People

  • Timothy M. Schulteis

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Automatic
  • Calibration
  • Closed Loop Systems
  • Computational Science
  • Computer Graphics
  • Computers
  • Control Systems
  • Estimators
  • Hidden Markov Models
  • Identification
  • Markov Models
  • Measurement
  • Mechanical Engineering
  • Probability
  • Time Intervals

Readers

  • Computational Modeling and Simulation
  • Operations Research
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy