Extrinsics autocalibration for dense planar visual odometry
File(s)zienkiewicz_davison_jfr2014.pdf (6.47 MB)
Accepted version
Author(s)
Zienkiewicz, J
Davison, A
Type
Journal Article
Abstract
A single downward-looking camera can be used as a high-precision visual odometry sensor in a wide range of real-world mobile robotics applications. In particular, a simple and computationally efficient dense alignment approach can take full advantage of the local planarity of floor surfaces to make use of the whole texture available rather than sparse feature points. In this paper, we present and analyze highly practical solutions for autocalibration of such a camera's extrinsic orientation and position relative to a mobile robot's coordinate frame. We show that two degrees of freedom, the out-of-plane camera angles, can be autocalibrated in any conditions, and that bringing in a small amount of information from wheel odometry or another independent motion source allows rapid, full, and accurate six degree-of-freedom calibration. Of particular practical interest is the result that this can be achieved to almost the same level even without wheel odometry and based only on widely applicable assumptions about nonholonomic robot motion and the forward/backward direction of its movement. We show the accurate, rapid, and robust performance of our autocalibration techniques for varied camera positions over a range of low-textured real surfaces, both indoors and outdoors.
Date Issued
2015-08-01
Date Acceptance
2014-07-12
Citation
Journal of Field Robotics, 2015, 32 (5), pp.803-825
ISSN
1556-4967
Publisher
Wiley
Start Page
803
End Page
825
Journal / Book Title
Journal of Field Robotics
Volume
32
Issue
5
Copyright Statement
© 2014 Wiley Periodicals, Inc. This is the accepted version of the following article: Zienkiewicz, J. and Davison, A. (2015), Extrinsics Autocalibration for Dense Planar Visual Odometry. J. Field Robotics, 32: 803–825, which has been published in final form at http://dx.doi.org/10.1002/rob.21547.
Sponsor
Dyson Technology Limited
Dyson Technology Limited
Grant Number
PO 4500098215
PO 4500501004
Subjects
Science & Technology
Technology
Robotics
Industrial Engineering & Automation
0801 Artificial Intelligence and Image Processing
0906 Electrical and Electronic Engineering
0913 Mechanical Engineering
Publication Status
Published
Date Publish Online
2014-11-19