Cart (Loading....) | Create Account
Close category search window

Model based vision as feedback for virtual reality robotics environments

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Natonek, E. ; Vision Lab., Swiss Federal Inst. of Technol., Lausanne, Switzerland ; Zimmerman, T. ; Fluckiger, L.

Task definition methods for robotic systems are often difficult to use. The “on-line” programming methods are often time expensive or risky for the human operator or the robot itself. On the other hand, “off-line” techniques are tedious and complex. In addition operator training is costly and time consuming. In a Virtual Reality Robotics Environment (VRRE), users are not asked to write down complicated functions, but can operate complex robotic systems in an intuitive and cost-effective way. However a VRRE is only effective if all the environment changes and object movements are fed-back to the virtual manipulating system. The paper describes the use of a VRRE for a semi-autonomous robot system comprising an industrial 5-axis robot, its virtual equivalent and a model based vision system used as feed-back. The user is immersed in a 3-D space built out of models of the robot's environment. He directly interacts with the virtual “components”, defining tasks and dynamically optimizing them. A model based vision system locates objects in the real workspace to update the VRRE through a bi-directional communication link. In order to enhance the capabilities of the VRRE, a reflex-type behavior based on vision has been implemented. By locally (independently of the VRRE) controlling the real robot, the operator is discharged of small environmental changes due to transmission delays. Thus once the tasks have been optimized on the VRRE, they are sent to the real robot and a semi autonomous process ensures their correct execution thanks to a camera directly mounted on the robot's end effector. On the other hand if the environmental changes are too important, the robot stops, re-actualizes the VRRE with the new environmental configuration, and waits for task redesign. Because the operator interacts with the robotic system at a task oriented high level, VRRE systems are easily portable to other robotics environments (mobile robotics and micro assembly)

Published in:

Virtual Reality Annual International Symposium, 1995. Proceedings.

Date of Conference:

11-15 Mar 1995

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.