近年來工業4.0的概念被提出，智慧工廠相關技術發展也日益受到重視，利用虛實整合系統(Cyber-Physical System, CPS)，將廠內之設備歸納於實體世界(Physical world)，透過網路協定(Networking)上傳設備之資訊至虛擬空間(Cyber space)的使用者介面，對傳統製造業進行資訊數位化與流程客製化。無人搬運車(Automated Guided Vehicle, AGV)作為工廠內之物流要角，為唯一穿梭產線與倉儲之間之設備，藉由其高效、準確等特性，可迅速完成搬運任務。然而多數針對無人搬運車之研究，著墨於導航與路徑規劃方面，缺乏了狀態監控、通訊協定以及使用者介面等落實虛實整合系統之必要部分。因此本文以一自行設計與實現之全向輪自走車為載具，提出與展示無人搬運車應用於智慧工廠之三大使用場景，任務規劃、人機整合以及狀態監控，並利用虛實整合之概念依序由實體世界載具建立、導航方式實現、感測器安裝，通訊協定之TCP Socket、Http連線將實體世界裡之資訊上傳至虛擬空間中，建立使用者介面、人機整合資訊以及狀態監控面板。任務規劃場景中，工作人員透過使用者介面將無人搬運車調派至指定地點，與機械手臂進行資訊交換以夾取物件，完成任務；人機整合場景中，利用關鍵點檢測(Keypoint detection)算法，檢測來自監控畫面中人員之動作意圖，使無人搬運車做出適當反應；狀態監控場景中，監控面板根據感測器之資訊，將工況非正常之無人搬運車調離產線，避免阻礙其他無人搬運車之運行，以維持生產效率。綜合以上研究成果，期望本文所研究之方法與開發之功能，未來可廣泛應用於智慧工廠與相關產業。

Automated guided vehicles (AGVs) play key roles in the modern manufacturing industry due to the ability to connect production line and storage system. In this decade, the concept of Industry 4.0 has been put forward to not only automate production lines but also digitize information and processes, emphasizing the application of Cyber-physical system (CPS) in the smart factory. The physical world contains the devices such as machine tools, conveyor belts, and AGVs. The cyber space offers user interface and monitoring dashboard, that allows users to make orders and understand the status of factories. The bridge between physical world and cyber space is networking, uploading the information from physical world, sending commands from cyber space. However, lots of research has focused on the navigation and route planning of AGVs, lacking key parts of CPS like status monitoring, networking, user interface. As a result, this thesis develops a self-design AGV based on Omni-wheels, demonstrating three important scenarios in the smart factory, including task planning, human-machine integration, and status monitoring. Utilizing the concept of CPS, an AGV platform is set up and sensors installed in the real world. In the communication protocol part, taking advantage of TCP Socket and Http, transmitting the information to the cyber space. Finally, user interface, human-machine integration, status-monitoring dashboard are established in the cyber space to achieve scenes as follows. First, workers can allocate AGVs carrying materials to specific location where manipulators are through the user interface, then manipulators gripping materials to finish task planning. Second, by the assistance of artificial neutral network algorithm called Keypoint detection, the positions of human’s joints can be discovered from the video captured by the IP camera. Human’s intention can be analyzed by these positions, and AGV will react simultaneously. Third, in order to maintain the production efficiency, when the status-monitoring dashboard detects the abnormal status of the AGV, the AGV will be transferred away from the production line to make sure others successfully finish their tasks. Based on the above research results, it is expected that the methods developed in this thesis can be widely applied in smart factories and related industries in the future.

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