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研究生: 柯霽祐
JI-YOU KE
論文名稱: 以Android行動裝置及雲端影像處理為基礎的主從式機器人
A Client-Server Robot Based on Android Device and Cloud Image Processing
指導教授: 高維文
Wei-Wen Kao
口試委員: 黃緒哲
Shiuh-Jer Huang
林紀穎
Chi-Ying Lin
學位類別: 碩士
Master
系所名稱: 工程學院 - 機械工程系
Department of Mechanical Engineering
論文出版年: 2016
畢業學年度: 104
語文別: 中文
論文頁數: 52
中文關鍵詞: 影像處理TLD物體追蹤Android物聯網雙輪運動機器人
外文關鍵詞: image processing, TLD, object tracking, Android, IoT, 2dw robot.
相關次數: 點閱:241下載:7
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  • 智慧型手機人手一機,將人們帶入了物聯網時代。跟隨著時代的進步,演算的成本不斷下降,高品質的攝影機也越賣越便宜,而有許多高度依賴視覺的機器人不斷的上市。但對於機器人內建的處理器而言,影像處理的工作還是過於繁重,因此將繁重的運算交由雲端科技解決,是更理想的解決方式。

    本論文題出自行建置一主從式系統架構,其中包含一台雙輪運動機器人,以及一個雲端的影像處理器。雙輪運動機器人上搭載了一台 Android 手機,於手機上運行NIO 伺服器,以傳送串流影像至雲端,以及接收雲端運算的結果,並以結果決定機器人的行動。雲端的影像處理器採用 TLD 演算架構,能夠追蹤任意物體,同時線上學習其物體辨識模型。雲端處理器也是於 Android 系統上執行。


    The idea of the internet of Things (IoT) has been a heated topic for scholars and engineers since smartphone gained popularity among almost every person at every age. As the cost of both computing and high-quality camera are reducing, more and more robots with higher dependency on visual sensor have come to the market.Yet the loading of image processing for a built-in computer is still too heavy. Thus, a solution of combining cloud computing technology would be more ideal.

    This research is based on a client-server architecture system we built, consisting of a 2WD (two-wheel drive) robot and a cloud image processor. The system is then modified to set up an IoT environment, serving as a backbone for the robot’s tracking function. The mobile robot in the system is equipped with an Android phone which is used as a server to transfer image stream to the cloud, and receiving the processed result, then determine the motion of robot. The image processor on the cloud is based on the TLD (Tracking-Learning-Detection) framework, it is able to track an arbitrary object and built the model for detection online. The image processor also run on Android OS.

    Abstract I 摘要 II 致謝 III 目錄 V 圖目錄 VI 第一張 緒論 1 1.1 前言 1 1.2 研究動機與方法 2 1.3 文獻回顧 3 1.4 論文架構 4 第二張 實驗平台架構 5 2.1 軟體開發環境簡介 5 2.1.1 Android 5 2.1.2 Arduino 6 2.2 系統通訊架構 7 2.2.1 無線傳輸 8 2.2.2 串列傳輸 10 2.3 硬體開發平台簡介 13 2.3.1 UART(Universal Asynchronous Receiver/Transmitter) 14 2.3.2 PWM (Pulse Width Modulation) 15 2.3.3 機器人遙控器 16 2.3.4 機器人測試 APP 18 2.4 系統運作流程 23 2.4.1 Android伺服器運作流程 23 2.4.2 Android 客戶端 24 2.4.3 物體追蹤運作流程 26 第三章 TLD演算結構 27 3.1 追蹤器 28 3.1.1 KLT (Kanade- Lucas-Tomasi) 28 3.1.2 光流(Optical flow)之定義 29 3.1.3 特徵點篩選 30 3.1.4 高斯金字塔特徵追蹤 31 3.2檢測器 31 3.2.1 變異數分類器(Patch Variance Classifier): 32 3.2.2 整體分類器(Ensemble Classifier): 32 3.2.3 隨機蕨分類器 32 3.2.4 最近鄰分類器(Nearest Neighbor Classifier,NN 分類器) 33 3.3合併器(integrator) 34 3.4.1 P專家(P-expert) 34 3.4.2 N專家(N-expert) 35 第四張 實驗結果及討論 36 4.1 實驗用平台硬體規格 36 4.2 實驗環境及實驗流程 39 4.2.1 實驗環境 39 4.2.2 實驗流程 40 4.3 實驗數據 43 4.4 結果分析 48 第五章 結論與未來展望 49 5.1 結論 49 5.2 個人建議 49 5.3 未來展望 50 參考文獻 51

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