Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/11772
Title: Sensor fusion of monocular cameras and laser rangefinders for line-based simultaneous localization and mapping (SLAM) tasks in autonomous mobile robots
Authors: Zhang, X
Rad, AB
Wong, YK
Issue Date: 2012
Source: Sensors, Jan. 2012, v. 12, no. 1, p. 429-452
Abstract: This paper presents a sensor fusion strategy applied for Simultaneous Localization and Mapping (SLAM) in dynamic environments. The designed approach consists of two features: (i) the first one is a fusion module which synthesizes line segments obtained from laser rangefinder and line features extracted from monocular camera. This policy eliminates any pseudo segments that appear from any momentary pause of dynamic objects in laser data. (ii) The second characteristic is a modified multi-sensor point estimation fusion SLAM (MPEF-SLAM) that incorporates two individual Extended Kalman Filter (EKF) based SLAM algorithms: monocular and laser SLAM. The error of the localization in fused SLAM is reduced compared with those of individual SLAM. Additionally, a new data association technique based on the homography transformation matrix is developed for monocular SLAM. This data association method relaxes the pleonastic computation. The experimental results validate the performance of the proposed sensor fusion and data association method.
Keywords: Feature fusion
Multi-sensor point estimation fusion (MPEF)
Homography transform matrix
SLAM
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Sensors 
EISSN: 1424-8220
DOI: 10.3390/s120100429
Rights: © 2012 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
The following publication Zhang, X., Rad, A. B., & Wong, Y. K. (2012). Sensor fusion of monocular cameras and laser rangefinders for line-based simultaneous localization and mapping (SLAM) tasks in autonomous mobile robots. Sensors, 12(1), (Suppl. ), 429-452 is available athttps://dx.doi.org/10.3390/s120100429
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