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

Camera-based observation of obstacle motions to derive statistical data for mobile robot motion planning

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

2 Author(s)
Kruse, E. ; Inst. for Robitics & Process Control, Tech. Univ. Braunschweig, Germany ; Wahl, F.M.

Mobile robots for advanced applications have to act in environments which contain moving obstacles. Motions of obstacles (e.g. humans) usually are not precisely predictable, but neither they are completely random. Long-term observation of obstacle behavior may yield knowledge about prevailing motion patterns. This paper presents concepts and results of an experimental system. Using cameras mounted at the ceiling, the workspace is observed. The image data is processed and transformed into a compact statistical representation of motion patterns. Mobile robot motion planning benefits from such additional knowledge: trajectories are rated in terms of collision probability and expected time for reaching the goal; planning yields efficient paths which are adapted to obstacle behavior

Published in:

Robotics and Automation, 1998. Proceedings. 1998 IEEE International Conference on  (Volume:1 )

Date of Conference:

16-20 May 1998

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.