By Topic

Evaluation of a Parallel Architecture and Algorithm for Mapping and Localization

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
$33 $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)
Damian M. Lyons ; Robotics and Computer Vision Laboratory, Computer & Information Science Department, 340 JMH, Fordham University, Bronx, NY 10458 USA. phone: 718-817-4485; fax: 718-817-4488; e-mail: ; Giselle R. Isner

The Beowulf cluster approach to parallel computation offers a potentially cheap and robust source of computational power for high complexity algorithms in robotics. The challenge is to integrate this approach with the mobility and time critical response constraints of many robotic algorithms. The key contributions of this paper are: (1) introduction of a computational architecture for integrating a cluster into the control architecture of one or more robots, (2) a cluster implementation of Thrun et al's Concurrent Localization and Mapping (CML) algorithm, and (3) presentation of results to illustrate the performance of the implemented CML algorithm and validate the architectural approach.

Published in:

2007 International Symposium on Computational Intelligence in Robotics and Automation

Date of Conference:

20-23 June 2007