By Topic

Urban localization method for mobile robots based on dead reckoning sensors, GPS, and map matching

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

4 Author(s)
Yu-Cheol Lee ; Department of Robot Research, ETRI, Republic of Korea ; Christiand ; Wonpil Yu ; Sunghoon Kim

This paper presents a localization method in urban environments by using dead reckoning sensors, Global Positioning System (GPS), and taking into account the benefits of map matching. Extended Kalman Filter (EKF) is used as the main framework to fuse the information from sensors. However, the result of the EKF greatly depends on how the robot utilizes and judges the position measurement which comes from GPS since the GPS easily gives wrong position measurement due to the phenomenon called multipath effect. Under the assumption that the robot must operate only on the main road, a map matching is used to filter out the wrong GPS measurements which fall outside the main road. An experiment has been conducted in urban environment to validate the proposed method. Experimental results show that our proposed method has superior performance compared to the EKF without map matching.

Published in:

Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on

Date of Conference:

9-12 Oct. 2011