By Topic

A mobile robot self-localization approach based on unidirectional vision

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

5 Author(s)
Ke Wang ; Key Laboratory of Measurement and Control of CSE, Ministry of Education, Nanjing, 210096, P.R. China ; Guanglei Huo ; Lijun Zhao ; Ruifeng Li
more authors

This paper presents a self-localization system for mobile robot in large-scale indoor environments. For a structured corridor environment, the vision information is adopted to track the robot pose with a predefined hybrid metric-topological map. A nonlinear unidirectional camera model is developed to project the probabilistic map elements with uncertainty manipulation. Extended Information filters are deployed to estimate the robot pose. The proposed system can perform localization tasks on-the-fly, with the features of efficient map modeling and computational simplicity. Experimental results are provided to demonstrate the performance and effectiveness of the proposed techniques.

Published in:

2012 IEEE International Conference on Mechatronics and Automation

Date of Conference:

5-8 Aug. 2012