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arXiv · 1811.08352

Near Real-Time Object Recognition for Pepper based on Deep Neural Networks Running on a Backpack

Esteban Reyes·Cristopher Gómez·Esteban Norambuena·Javier Ruiz-del-Solar
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Abstract

The main goal of the paper is to provide Pepper with a near real-time object recognition system based on deep neural networks. The proposed system is based on YOLO (You Only Look Once), a deep neural network that is able to detect and recognize objects robustly and at a high speed. In addition, considering that YOLO cannot be run in the Pepper's internal computer in near real-time, we propose to use a Backpack for Pepper, which holds a Jetson TK1 card and a battery. By using this card, Pepper is able to robustly detect and recognize objects in images of 320x320 pixels at about 5 frames per second.

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Esteban Reyes, Cristopher Gómez, Esteban Norambuena, Javier Ruiz-del-Solar. 2018-11-20. Near Real-Time Object Recognition for Pepper based on Deep Neural Networks Running on a Backpack. https://arxiv.org/abs/1811.08352

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