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A new feature parametrization for monocular SLAM using line features

Published online by Cambridge University Press:  05 March 2014

Liang Zhao ,
Shoudong Huang ,
Lei Yan  and
Gamini Dissanayake
Liang Zhao*
Affiliation:
Centre for Autonomous Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW 2007, Australia
Shoudong Huang
Affiliation:
Centre for Autonomous Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW 2007, Australia
Lei Yan
Affiliation:
Institute of Remote Sensing and GIS, School of Earth and Space Science, Peking University, Beijing, 100871, China
Gamini Dissanayake
Affiliation:
Centre for Autonomous Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW 2007, Australia
*
*Corresponding author. E-mail: Liang.Zhao-1@uts.edu.au
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Summary

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This paper presents a new monocular SLAM algorithm that uses straight lines extracted from images to represent the environment. A line is parametrized by two pairs of azimuth and elevation angles together with the two corresponding camera centres as anchors making the feature initialization relatively straightforward. There is no redundancy in the state vector as this is a minimal representation. A bundle adjustment (BA) algorithm that minimizes the reprojection error of the line features is developed for solving the monocular SLAM problem with only line features. A new map joining algorithm which can automatically optimize the relative scales of the local maps is used to combine the local maps generated using BA. Results from both simulations and experimental datasets are used to demonstrate the accuracy and consistency of the proposed BA and map joining algorithms.

Keywords

SLAMComputer visionLine feature parametrizationBundle adjustmentMap joining

Information

Type
Articles
Information
Robotica , Volume 33 , Issue 3 , March 2015 , pp. 513 - 536
Copyright
Copyright © Cambridge University Press 2014 

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