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Online calibration of stereo rigs for long-term autonomy

Warren, Michael, McKinnon, David, & Upcroft, Ben (2013) Online calibration of stereo rigs for long-term autonomy. In 2013 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Kongresszentrum Karlsruhe, Karlsruhe, Germany, pp. 3692-3698.

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Abstract

Stereo-based visual odometry algorithms are heavily dependent on an accurate calibration of the rigidly fixed stereo pair. Even small shifts in the rigid transform between the cameras can impact on feature matching and 3D scene triangulation, adversely affecting pose estimates and applications dependent on long-term autonomy. In many field-based scenarios where vibration, knocks and pressure change affect a robotic vehicle, maintaining an accurate stereo calibration cannot be guaranteed over long periods.

This paper presents a novel method of recalibrating overlapping stereo camera rigs from online visual data while simultaneously providing an up-to-date and up-to-scale pose estimate. The proposed technique implements a novel form of partitioned bundle adjustment that explicitly includes the homogeneous transform between a stereo camera pair to generate an optimal calibration. Pose estimates are computed in parallel to the calibration, providing online recalibration which seamlessly integrates into a stereo visual odometry framework.

We present results demonstrating accurate performance of the algorithm on both simulated scenarios and real data gathered from a wide-baseline stereo pair on a ground vehicle traversing urban roads.

Impact and interest:

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ID Code: 60978
Item Type: Conference Paper
Additional URLs:
Keywords: visual odometry algorithms, long-term autonomy, robotic vehicle, computer vision, bundle adjustment, constrained optimisation, robotics
DOI: 10.1109/ICRA.2013.6631096
ISBN: 978-1-4673-5641-1
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 [please consult the author]
Deposited On: 27 Jun 2013 22:26
Last Modified: 18 Nov 2014 13:56

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