發展基於深度學習之智慧自動撿球機

Development of an Intelligent Automatic Ball Picking Machine Based on Deep Learning

黃芃銘(Pung-Ming Huang)

指導教授 ： 陳冠宇

中原大學/工學院/機械工程研究所/碩士(2020年)

https://doi.org/10.6840/cycu202000886

摘要

本文研究基於深度學習設計並實現以樹莓派為作動車體、電腦為運算主體，整合神經網路、機器視覺、網路傳輸、車體運動等技術，開發出可以自動找球的智慧撿球車。該智慧撿球車與以往只有結合鏡頭的自走車不同的地方，是在於加入了網路傳輸及深度學習這兩種技術，利用智慧撿球車上的鏡頭所擷取到的影像，使用影像壓縮並編碼成Byte型式的影像訊息，透過無線網路的傳輸，從樹莓派傳送到負責運算的電腦主機，把接收到解碼成原來的影像，放入已經訓練好的深度學習模型，判斷出影像中是否有出現目標物，回傳作動訊息，讓智慧撿球車進行收球或找球的動作。

關鍵字

深度學習 ； 機器視覺 ； 網路傳輸 ； 樹莓派

並列摘要

This article studies the design and implementation of the Raspberry Pi as the driving body and the computer as the computing body based on deep learning. It integrates neural network, machine vision, network transmission, and vehicle body movement technology to develop a smart ball that can automatically find the ball car. This smart ball picker is different from the self-propelled cars that have only incorporated lenses in the past. It is based on the addition of two technologies of network transmission and deep learning. Compressed and encoded into Byte type image information, transmitted from the Raspberry Pi to the computer host responsible for calculation through wireless network transmission, decoded the received image into the original image, and put it into a trained deep learning model to determine If there is a target in the image, send an action message to let the smart ball picker collect or find the ball.

並列關鍵字

Deep Learning ； Machine Vision ； Network Transmission ； Raspberry Pi.

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