日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:1704.04712

Learn-Memorize-Recall-Reduce A Robotic Cloud Computing Paradigm

Learn-Memorize-Recall-Reduce A Robotic Cloud Computing Paradigm

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著者: Shaoshan Liu, Bolin Ding, Jie Tang, Dawei Sun, Zhe Zhang, Grace Tsai, Jean-Luc Gaudiot

分類: cs.DC, cs.AI, cs.RO

原文アブストラクト

The rise of robotic applications has led to the generation of a huge volume of unstructured data, whereas the current cloud infrastructure was designed to process limited amounts of structured data. To address this problem, we propose a learn-memorize-recall-reduce paradigm for robotic cloud computing. The learning stage converts incoming unstructured data into structured data; the memorization stage provides effective storage for the massive amount of data; the recall stage provides efficient means to retrieve the raw data; while the reduction stage provides means to make sense of this massive amount of unstructured data with limited computing resources.