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研究生： 蔡亞倫
Tsai, Ya-Lun
論文名稱： 基於MQTT之雲端與邊緣端無人搬運車管理系統設計與實作
Design and Implementation of a Cloud and Edge-Based Automated Guided Vehicle Management System Using MQTT
指導教授： 楊竹星
Yang, Chu-Sing
共同指導教授: 謝錫堃
Shieh, Ce-Kuen
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年： 2023
畢業學年度： 111
語文別： 中文
論文頁數： 80
中文關鍵詞： 無人搬運車 、MQTT 、邊緣端 、雲端 、Kafka 、Redis
外文關鍵詞： AGV, MQTT, Edge, Cloud, Kafka, Redis
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    • 隨著工業4.0的迅速發展，智慧工廠已成為熱門的工業趨勢，也是不可或缺的組成部分。現今已有許多技術被廣泛應用於智慧工廠中，例如 RFID、AI、擴增實境、工業機器人、移動機器人等。其中，無人搬運車（Automated Guided Vehicle，AGV）也是智慧工廠中的一個關鍵組件。

    目前，AGV 的相關研究主要聚焦於演算法的設計與優化，例如在最短時間或最少資源內完成路徑規劃、任務分配以及車輛管理等。然而，針對 AGV 管理系統的設計與實作方面的研究相對較少。有關 AGV 管理系統的現行設計存在幾個不足之處。首先，其設計未充分考慮不同 AGV 任務的性質，例如某些任務需要快速回應，而有些任務則允許稍有延遲。其次，在系統中傳遞不同類型消息時，未考慮這些消息可能具有不同的重要程度與傳輸流量。舉例來說，有些類型的消息流量較大，而有些則較小。在處理這些消息時，有些消息即使偶爾丟失也不會對系統造成嚴重影響，但有些則必須確保準確傳遞，以避免可能引發錯誤的情況。最後，現有設計未考慮系統的可擴展性與可用性，以及擴展與縮減過程中可能造成的消息遺失。

    所以本研究設計並實作一套 AGV 管理系統，並提供管理人員實時監控與操作功能，涵蓋人員權限管理、實時監控、任務發布操作以及歷史資訊查閱等功能。為了模擬真實工廠環境，我們採用腳本程式來模擬環境控制設備和 AGV 的運行。系統運行於 AWS 雲平台，並進行容器化部署。而本地端設備與伺服器的溝通，使用輕量且可靠的 MQTT 協定進行通訊。此外考慮到不同 AGV 任務對於響應速度的需求，本研究將系統架構分為邊緣端和雲端以解決此問題，然後也詳細規劃並設計了這兩個端點的架構。此外，根據不同消息的傳輸量與重要性，設計了不同種類消息的傳遞流程和方式。再來，還探討了系統的可擴展性和可用性，以應對隨著工廠規模的擴大，無人搬運車和環境控制設備需求增加所帶來的負載增加。最後，本研究還在邊緣端設計了一個架構，以解決在邊緣端架設多台 MQTT Broker 造成的問題，和動態調整 MQTT Broker 數量可能會造成的消息遺失。

    最後，本研究對邊緣端和雲端的相關性能進行了壓力測試實驗，以測試系統的效能。

    In the era of Industry 4.0, smart factories have become essential, incorporating technologies like RFID, AI, augmented reality, and various types of robots, including Automated Guided Vehicles (AGVs).

    Currently, research on AGV focuses on algorithm design and optimization, such as completing path planning, task allocation, and vehicle management in the shortest time or with the least resources. However, research on AGV management systems is relatively scarce. The existing design of AGV management systems has several shortcomings. Firstly, the design doesn't fully consider different AGV tasks. Secondly, when transmitting different types of messages, the design doesn't consider these messages may have different levels of importance and transmission flow. Finally, the current design does not consider the scalability and availability of the system, Additionally, the potential message loss during the process of scaling up or down.

    Therefore, this study designs and implements an AGV management system that provides real-time monitoring and operation functions for managers, including personnel authorization management, real-time monitoring, task release operations, and historical information inquiry. We use script programs to simulate the operation of environmental control equipment and AGVs. The system runs on AWS and is deployed using containerization. Communication between local devices and servers is achieved using the lightweight and reliable MQTT protocol. Additionally, considering the different response time requirements for different AGV tasks, this study divides the system architecture into edge and cloud sides to solve this problem and designs the architectures for both sides in detail. Moreover, we design the delivery process and method for different types of messages based on their transmission volume and importance. We also explore the system's scalability and availability to cope with the increasing demand for AGVs and environmental control equipment as the factory scales up. Finally, we design an architecture for the edge side to address the problem of setting up multiple MQTT Brokers on the edge and the potential message loss caused by dynamically adjusting the number of MQTT Brokers.

    Finally, stress testing experiments are conducted to evaluate the system's performance on both the edge and cloud sides, ensuring its efficiency in real-world scenarios.

    中文摘要 I Abstract III 誌謝 X 目錄 XI 表目錄 XIV 圖目錄 XV 第一章 緒論 1 1-1 研究背景 1 1-2 研究動機與目的 1 1-3 論文結構 3 第二章 背景知識與相關研究 4 2-1 無人搬運車 (Automated guided vehicle, AGV) 4 2-1.1 無人搬運車任務 4 2-1.2 無人搬運車管理系統 5 2-2 通訊協定 6 2-2.1 超文本傳輸協定(HTTP) 和 webSocket 協定 7 2-2.2 MQTT 協定 8 2-2.3 分散式 MOTT Broker 11 2-3 軟體系統 12 2-3.1 Kafka 13 2-3.2 非關聯型資料庫 Redis 與 MongoDB 14 2-3.3 Nginx 16 第三章 系統設計與實作 17 3-1 系統架構概述 17 3-2 邊緣端 18 3-2.1 邊緣端與本地端 19 3-2.2 邊緣端架構 19 3-2.3 動態調整分散式 MQTT Broker 24 3-2.4 避免邊緣端單點故障 29 3-3 雲端 32 3-3.1 Kafka 與邊緣端 33 3-3.2 Kafka 與雲端 35 3-3.3 資料庫 35 3-3.4 後端伺服器 38 3-4 消息種類與傳遞流程 40 3-4.1 傳輸協定與傅輸可靠性 40 3-4.2 消息傳遞流程 41 第四章 實驗結果與分析 48 4-1 邊緣端系統效能測試 48 4-1.1 不同數量之 MQTT Broker 之效能影響 48 4-1.2 不同QoS之效能差異 52 4-2 雲端資料庫系統效能測試 55 4-2.1 索引鍵測試 55 4-2.2 Redis 快取測試 56 第五章 結論與未來方向 58 參考文獻 59 附錄 65 A 功能展示與說明65 B 環境模擬 70 C 後端 Restful API 74 D 資料庫表格設計 78 E UML補充說明 79

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