Stereo vision based self-localization of autonomous mobile robots

Abdul Bais, Robert Sablatnig, Jason Gu, Yahya M. Khawaja, Muhammad Usman, Ghulam M. Hasan, Mohammad T. Iqbal

Research output: Chapter in Book/Conference paperConference paperpeer-review

9 Citations (Scopus)


This paper presents vision based self-localization of tiny autonomous mobile robots in a known but highly dynamic environment. The problem covers tracking the robot position with an initial estimate to global self-localization. The algorithm enables the robot to find its initial position and to verify its location during every movement. The global position of the robot is estimated using trilateration based techniques whenever distinct landmark features are extracted. Distance measurements are used as they require fewer landmarks compared to methods using angle measurements. However, the minimum required features for global position estimation are not available throughout the entire state space. Therefore, the robot position is tracked once a global position estimate is available. Extended Kalman filter is used to fuse information from multiple heterogeneous sensors. Simulation results show that the new method that combines the global position estimation with tracking results in significant performance gain.

Original languageEnglish
Title of host publicationRobot Vision - Second International Workshop, RobVis 2008, Proceedings
Number of pages14
Publication statusPublished - 27 Aug 2008
Externally publishedYes
Event2nd International Workshop on Robot Vision, RobVis 2008 - University of Auckland, New Zealand
Duration: 18 Feb 200820 Feb 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4931 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd International Workshop on Robot Vision, RobVis 2008
Country/TerritoryNew Zealand
CityUniversity of Auckland


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