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Evaluation of Field of View Width in Stereo-vision-Based Visual Homing

Published online by Cambridge University Press:  03 July 2019

D. M. Lyons ,
B. Barriage  and
L. Del Signore
D. M. Lyons*
Affiliation:
Robotics and Computer Vision Lab, Fordham University, Bronx, NY10458, USA. E-mails: [email protected], [email protected]
B. Barriage
Affiliation:
Robotics and Computer Vision Lab, Fordham University, Bronx, NY10458, USA. E-mails: [email protected], [email protected]
L. Del Signore
Affiliation:
Robotics and Computer Vision Lab, Fordham University, Bronx, NY10458, USA. E-mails: [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

Visual homing is a local navigation technique used to direct a robot to a previously seen location by comparing the image of the original location with the current visual image. Prior work has shown that exploiting depth cues such as image scale or stereo-depth in homing leads to improved homing performance. While it is not unusual to use a panoramic field of view (FOV) camera in visual homing, it is unusual to have a panoramic FOV stereo-camera. So, while the availability of stereo-depth information may improve performance, the concomitant-restricted FOV may be a detriment to performance, unless specialized stereo hardware is used. In this paper, we present an investigation of the effect on homing performance of varying the FOV widths in a stereo-vision-based visual homing algorithm using a common stereo-camera. We have collected six stereo-vision homing databases – three indoor and three outdoor. Based on over 350,000 homing trials, we show that while a larger FOV yields performance improvements for larger homing offset angles, the relative improvement falls off with increasing FOVs, and in fact decreases for the widest FOV tested. We conduct additional experiments to identify the cause of this fall-off in performance, which we term the ‘blinder’ effect, and which we predict should affect other correspondence-based visual homing algorithms.

Keywords

Visual homingRGB-DAutonomous robotsComputer visionMobile robots
Type
Articles
Information
Robotica , Volume 38 , Issue 5 , May 2020 , pp. 787 - 803
Copyright
Copyright © Cambridge University Press 2019

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