Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

Particle filter-based heading estimation using magnetic compasses for mobile robot navigation

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)
Woong Kwon ; Mechatronics & Manuf. Technol. Center, Samsung Electron. Co. Ltd., Suwon ; Kyung-Shik Roh ; Hak-Kyung Sung

Heading information is critical for the control and/or navigation of mobile devices and robots. To get accurate heading information robustly, we propose a method which combines particle filtering with magnetic compasses. Although magnetic compasses can provide absolute heading angle, they have not been used for indoor applications since serious magnetic interferences are commonly founded in home/office environments. We overcome this difficulty by 1) suggesting statistical calibration of a magnetic compass, 2) deriving necessary conditions of the Earth's magnetic field area, and 3) designing an event-based particle filter based on likelihood calculated from conditional probability. Particle filter is an emerging key technology which can be applied to nonlinear/non-Gaussian model, beyond the limitations of Kalman filter. We take advantage of particle filter to optimally fuse the information from both magnetic compasses and odometry data. Experimental results on mobile robot navigation in indoor environments show reliability and robustness of the proposed method

Published in:

Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on

Date of Conference:

15-19 May 2006