無人搬運車常應用於自動化工廠之物料搬運系統，其運作方式可分為依循實體或光磁軌道行走以及自主導航兩大類型。實體或光磁軌道導引之無人搬運車得根據所佈線之有限路徑行走；因此穩定性高，但路徑彈性上受到限制為其缺點。全自主導航無人搬運車並不需要根據任何佈線之實體或光磁軌道路徑便可行走；因此路徑彈性高，但得搭配高階定位及避障感測器，同時穩定度也是重要考量。有鑑於上述兩大類型之特性，本文提出一結合光學導引路徑以及區段式自主路徑的虛實路徑（Cyber-physical Track）無人搬運車系統，其包括虛實路徑設計、路徑規劃器以及無人搬運車感測與控制器。在虛實路徑設計部分，本文以特定顏色線段路徑進行建構實體路徑（Physical Track），並在實體路徑上設置條碼，以辨識路徑上之特定點（包括工件取放點以及虛實路徑接合點）位置。虛擬路徑（Cyber Track）則是建構於虛實路徑接合點間，由無人搬運車動態自主導航器導引之區段式彈性路徑；因此虛擬路徑為回路軌道上的不需事先建構的捷徑。路徑規劃器則以A*演算法針對軌道上不同工件取放點之派車任務進行虛實路徑規劃。為了因應虛實路徑規劃之需求，無人搬運車裝設低成本之線掃描攝影擷取特定顏色線段路徑並進行位置條碼之解碼；配備七組超音波感測器進行障礙物偵測；使用增量式編碼器計算里程與方位；最後開發虛實路徑控制器，並導入模糊避障演算法。最後，本文以一包括六個工件取放點以及四個虛實路徑接合點之回路路徑進行探討，並以相關實驗結果驗證此一虛實路徑無人搬運車系統可行性。

Automated guided vehicles (AGVs) are popularly used in material handling systems of automated factories. The operation of an AGV can be categorized as the guidance with rail tracks or optical/ magnetic tracks and the guidance with autonomous navigation. The AGV had to follow the deployed tracks for the guidance with rail tracks or optical/ magnetic tracks. Although such a system exhibits high reliability and simple control schemes, limited track combination is the drawback. Contrarily, autonomous navigation approaches did not need any deployed tracks; however, they employed advanced localization and obstacle detection sensor for navigation. Therefore, autonomous navigation approaches provided high trajectory flexibility; nevertheless, complicated system architecture and reliability would be practical concerns. To combine the advantages of two aforementioned movement systems, this study proposes a cyber-physical track (CPT) AGV system that used optical guidance tracks and regional autonomous tracks as well. The CPT AGV system is composed of the CPT design, path planning and control system. The physical track system is formed by a number of visible track segments with a specific color. Bar code plates were placed beside the track to identify specific locations such as loading/ unloading buffers and cyber and physical track junctions (CPTJs). Cyber tracks were freely formed between any of two distinct CPTJs without a physical track connection, and the regional autonomous navigation was applied accordingly. Hence, cyber represents an invisible short-cut track in a track system. The path planning was realized with A* algorithm that is capable to find an optimal path from CPT segments to deal with a "from-to" movement command. To facilitate the CPT operation, a low cost line scanner camera was used to detect the color track and the identification shown on a bar code plate; seven sonar sensors were used to detect obstacles surrounding the robot; two incremental wheel encoders were desired to obtain the odometry. In addition to sensor modules, a controller was implemented for path planning and fuzzy logic based reactive navigation. Finally, a CPT system containing six loading/ unloading buffers and 4 CPTJs was produced for discussion, and the experimental results were used to evaluate the feasibility of CPT AGV systems.

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