By Topic

A hybrid approach towards vision based self-localization of autonomous mobile robots

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

4 Author(s)
Bais, A. ; NWFP Univ. of Eng. & Technol. Peshawar, Peshawar ; Sablatnig, R. ; Khawaja, Y.M. ; Hassan, G.M.

This paper presents a hybrid approach towards self- localization of tiny autonomous mobile robots in a known but highly dynamic environment. The proposed algorithm is intended for two-wheeled differential drive robots which are equipped with a pivoted stereo vision system, two digital encoders, a gyro sensor, two 10g accelerometers and a magnetic compass. The global position of the robot can be estimated by extracting two distinct landmarks from the robot environment and measuring their range and orientation using the stereo vision system. However, distinct landmarks are not available through the entire state space and it is required to track the robot position once a global estimate is available. Tracking of the globally estimated position is performed within the framework of extended Kalman filter. Constant monitoring of the robot observation enables it to detect any unexpected situation. Simulation results show that robot can successfully localize itself at startup and is capable of detecting and recovering from localization failures.

Published in:

Machine Vision, 2007. ICMV 2007. International Conference on

Date of Conference:

28-29 Dec. 2007