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研究生： 馬嘉鉞
MA, KA UT
論文名稱： 自動導引車彈性編隊導航控制之研究
The Study of Navigation Control for Flexible AGV Formation
指導教授： 陳敬
Chen, Jing
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 電腦與通信工程研究所
Institute of Computer & Communication Engineering
論文出版年： 2022
畢業學年度： 110
語文別： 英文
論文頁數： 80
中文關鍵詞： 自動導引車 、導航 、嵌入式系統 、協作 、編隊
外文關鍵詞： Automated Guided Vehicles, navigation, embedded software, cooperative
相關次數： 點閱：94  下載：1 
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    • 從1956 年歷史上第一個標準化貨櫃投入使用以來，物流運輸業始終傾向於統一貨物大小；因為標準化的貨物體積有利於重型機械作業，亦可減少運輸成本。但貨物體積的統一化也帶來了效率和彈性上的影響。本研究提出一個導航控制方案，以兩台或以上的自動導引車(Automated Guided Vehicles)組成可自定義的隊形，使多台自動導引車以協作形式搬運不同大小的貨物成為可能。
    為了提供最大的隊形彈性，自動導引車之間不存在任何物理性連接或固定，因此自動導引車的編隊並無法使用常見於一般車輛基於導向輪的轉向方式。這為維持自動導引車編隊的隊形帶來挑戰，即使是單純的轉向，也需要拆分為多個動作來進行，期間隊伍中各台自動導引車需要精確維持各自的朝向，速度和自動導引車之間的同步，以保證隊形的穩定。為此，設計中包含一個路線計劃器以及一個中央控制器，路線計劃器為隊伍中各台自動導引車規劃其專屬的路線。而中央控制器則用於控制所有自動導引車的動作，記錄其位置和朝向，以穩定維持由多台自動導引車所組成的隊形。本研究中的自動導引車使用差速轉向方式，確保自動導引車擁有原地
    轉向的能力。在導航技術方面使用正交編碼器以記錄自動導引車的移動距離，同時在工作環境佈設提供導航資訊的標籤，以保證自動導引車能精準地在工作環境中移動。
    本研究包含作為概念驗證的實驗；實驗在一個3 米乘3 米的空間中進行，以三台自動導引車演示本研究提出的導航控制方案。實驗結果顯示在本研究的成果下，自動導引車能組成並維持多種編隊，以運載不同大小的貨物。
    有能力以編隊形式完成協作任務的自動導引車在彈性面和成本面皆具有極大的潛力。例如工廠生產線上的運輸任務不必等候能適配特定貨物大小的自動導引車，而只需要因應貨物大小調整參與運輸任務的自動導引車的數量，這大大提升了自動導引車的調度彈性。而工作環境內所有的運輸任務都可以使用單一規格的自動導引車，自動導引車的維護費用也能受益於規格的統一化而得以減縮。

    Ever since the first modern container aboard the tanker ship SS Ideal X in 1956, cargo transport tends to retain their freights with a specific size, since a fixed size cargo could significantly reduce the difficulty of sorting cargos with machinery. Having a unified standard for cargo could also bring downsides in the form of flexibility and efficiency. This study intends to design a cooperative method, of which two or more AGVs (Automated Guided Vehicles) in the system could move together in various formations, in order to transport a single cargo cooperatively. Such a system can provide the ability of transporting cargo of different sizes using multiple ordinary AGVs.
    In order to provide a highly flexible formation mechanism, there are no physical connections between any two AGVs, which means a group of AGVs cannot take advantage of conventional front/rear wheel steering. This brings challenges for an AGV team in maintaining the formation, and even a simple movement (for example, turning at a corner) would take multiple steps to complete. AGVs in the team need to move together with different yaw angles, speeds, and proper timing. This is achieved in this study by planning the paths for every AGV individually via an off-line planner and having a centralized server to control all the AGVs, in addition to precisely measure the position and angle of every AGV. AGVs employ differential steering to gain the ability to change the direction in place, while a set of landmarks in the workspace and two encoder sensors equipped on an AGV provide a highly accurate navigation solution.
    For the purpose of proof of concept, a 3m by 3m workspace is set up for experiments. Three AGVs participate to demonstrate the ability of forming different formations and maintaining the formation during the course of carrying out a transportation task.
    The ability to form various formations and work cooperatively brings a great potential in terms of flexibility and cost reduction. For example, a transport requirement does not need to wait for a specific AGV due to the cargo size. Single type of AGV could reduce the maintenance cost since they use the same parts, and the maintenance staff can specialize in repairing the same type of AGV, which can increase productivity.

    CHAPTER 1 INTRODUCTION 1 1.1 Automated Guided Vehicles 1 1.2 Motivation 2 1.3 Goal 2 1.4 Outline 2 CHAPTER 2 RELATED WORKS 3 2.1 Practical AGV System 3 2.1.1 Port terminals 3 2.1.2 Goods-to-Person 4 2.2 Navigation 6 2.2.1 Line following 6 2.2.2 Tags 7 2.2.3 Laser positioning 7 2.2.4 Light detection and ranging 8 2.2.5 Global positioning system (GPS) 8 2.2.6 Computer vision 8 2.3 Collaborative AGV Systems 11 2.3.1 Fixed formation collaborative AGV system 11 2.3.2 Flexible formation collaborative AGV system 12 2.3.3 Master-slave collaborative AGV system 12 2.4 Discussion 14 CHAPTER 3 DESIGN AND METHODS 15 3.1 Operational Model 15 3.2 Problem formulation 16 3.3 Structure Design 17 3.3.1 Off-line path planner 20 3.3.2 Central controller 20 3.3.3 AGV 22 3.4 Formation Management 23 3.4.1 Supported formations 23 3.4.2 Path planning 25 3.4.3 Rotatory motion 26 3.4.4 Angular motion control 28 3.5 Navigation Mechanism 30 3.5.1 Tags 30 3.5.2 Distance tracking 33 3.6 Workspace Layout 34 3.7 Correction of Position Error 35 3.8 Synchronization 36 3.9 Discussion 37 CHAPTER 4 IMPLEMENTATION 38 4.1 System Environment 38 4.1.1 Client setup 38 4.1.2 Server setup 40 4.2 Configuration Setup 41 4.2.1 Tags layout configuration 41 4.2.2 AGV team configuration 42 4.3 AGV 44 4.3.1 AGV structure 44 4.3.2 Workflow 45 4.3.3 Commands of operations 46 4.3.4 Rectilinear motion based on distance tracking 47 4.3.5 Rotatory motion based on distance tracking 48 4.3.6 Angular motion based on distance tracking 49 4.3.7 Rectilinear motion based on tag reading 51 4.3.8 Rotatory motion based on tag reading 52 4.4 Off-Line Path Planner 53 4.4.1 Overall workflow 53 4.4.2 Path planning 53 4.4.3 Location converting 55 4.4.4 Team rotation control 57 4.4.5 Team rectilinear motion control 58 4.5 Central Controller 60 4.5.1 Overall workflow 60 4.5.2 Command handler 61 4.5.3 Synchronizer 62 4.5.4 Position tracker 63 CHAPTER 5 EVALUATION 64 5.1 Experimental Environment 64 5.1.1 Hardware setup 64 5.1.2 Workspace setup 66 5.2 System Verification 67 5.2.1 Formations 68 5.2.2 Moving straight forward 70 5.2.3 Turning 71 5.2.4 Traveling with load 72 5.3 Discussion 75 CHAPTER 6 CONCLUSIONS 76 6.1 Conclusions 76 6.2 Future Works 76 REFERENCES 78 APPENDIX 80

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