Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/14309
Title: Incorporation of feature tracking into simultaneous localization and map building via sonar data
Authors: Ip, YL
Rad, AB
Keywords: Extend Kalman filters EKF
Feature extraction and tracking
Mobile robot
Simultaneous localization and map building
Sonar sensors
Issue Date: 2004
Publisher: Kluwer Academic Publ
Source: Journal of intelligent and robotic systems: theory and applications, 2004, v. 39, no. 2, p. 149-172 How to cite?
Journal: Journal of Intelligent and Robotic Systems: Theory and Applications 
Abstract: Simultaneous Localization and Map building (SLAM) is referred to as the ability of an Autonomous Mobile Robot (AMR) to incrementally extract the surrounding features for estimating its pose in an unknown location and unknown environment. In this paper, we propose a new technique for extraction of significant map features from standard Polaroid sonar sensors to address the SLAM problem. The proposed algorithm explicitly initializes and tracks the line (or wall) features from a comparison between two overlapping sensor measurements buffers. The experimental studies on a Pioneer 2DX mobile robot equipped with sonar sensors suggest that SLAM problem can be solved by the proposed algorithm. The estimated trajectory of AMR from the standard model based on Extended Kalman Filter (EKF) localization for the same experiment is also provided for comparison.
URI: http://hdl.handle.net/10397/14309
ISSN: 0921-0296
DOI: 10.1023/B:JINT.0000015402.60437.6a
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