Title

Effect of Field of View on Stereovision-based Visual Homing

Degree of Contribution

Lead

Document Type

Conference Proceeding

Keywords

Robotics, Computer Vision, Stereovision, Visual Homing, Navigation

Disciplines

Artificial Intelligence and Robotics | Computer Engineering | Robotics

Abstract

Navigation is challenging for an autonomous robot operating in an unstructured environment. Visual homing is an AI local navigation technique used to direct a robot to a previously seen location, and is inspired by biological models. Most visual homing uses a panoramic camera. Prior work has shown that exploiting depth cues in homing from, e.g., a stereo-camera, leads to improved performance. However, many stereo-cameras have a limited field of view (FOV).

We present a stereovision database methodology for visual homing. We use two databases we have collected, one indoor and one outdoor, to evaluate the effect of FOV on the performance of our homing with stereovision algorithm. Based on over 120,000 homing trials, we show that contrary to intuition, a panoramic field of view does not necessarily lead to the best performance, and we discuss the implications of this.

Publication Title

IEEE International Conference on Tools with AI, Nov 2017, Boston MA

Article Number

1064

Publication Date

11-2017

Language

English

Peer Reviewed

1

Version

Published

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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