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2016 | OriginalPaper | Buchkapitel

Autonomous Wheeled Robot Navigation with Uncalibrated Spherical Images

verfasst von : Lingyan Ran, Yanning Zhang, Tao Yang, Peng Zhang

Erschienen in: Intelligent Visual Surveillance

Verlag: Springer Singapore

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Abstract

This paper focuses on the use of spherical cameras for autonomous robot navigation tasks. Previous works of literature mainly lie in two categories: scene oriented simultaneous localization and mapping and robot oriented heading fields lane detection and trajectory tracking. Those methods face the challenges of either high computation cost or heavy labelling and calibration requirements. In this paper, we propose to formulate the spherical image navigation as an image classification problem, which significantly simplifies the orientation estimation and path prediction procedure and accelerates the navigation process. More specifically, we train an end-to-end convolutional network on our spherical image dataset with novel orientation categories labels. This trained network can give precise predictions on potential path directions with single spherical images. Experimental results on our Spherical-Navi dataset demonstrate that the proposed approach outperforms the comparing methods in realistic applications.

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Metadaten
Titel
Autonomous Wheeled Robot Navigation with Uncalibrated Spherical Images
verfasst von
Lingyan Ran
Yanning Zhang
Tao Yang
Peng Zhang
Copyright-Jahr
2016
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-3476-3_6