Effect of Field of View on Stereovision-based Visual Homing
Robotics, Computer Vision, Stereovision, Visual Homing, Navigation
Artificial Intelligence and Robotics | Computer Engineering | Robotics
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.
IEEE International Conference on Tools with AI, Nov 2017, Boston MA
Damian Lyons, Ben Barriage and Luca Del Signore “Effect of Field of View on Stereovision-based Visual Homing” IEEE International Conference on Tools with AI, Nov 2017, Boston MA
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