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dc.contributor.authorLee, Chen-Kuien_US
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dc.description.abstract本論文提出一個混合式人工智慧的控制方法來處理車型機器人的停車最佳化設計。其中包含了基因演算法、以及派翠網路(Petri net)、模糊控制。基因演算法主要用於求出最合適的倒車位置,而派翠網路則取代傳統的流程設計,建立一個在原始路徑受干擾或車格被佔的情況下可替代的停車路徑,模糊控制系統則用於導引控制。 本文首先介紹停車系統的完整架構,接著導入智慧型的平行停車方法,其中包含了路徑規劃,決策選擇以及軌跡追蹤控制器,最後以模擬來驗證此方法的可行性並展現其效能。zh_TW
dc.description.abstractThis thesis devotes to design and implement a hybrid artificial intelligent control scheme for a car-like mobile robot to perform the task of optimal parking. The control scheme consists of several techniques: genetic algorithm, Petri net and fuzzy control. The binary genetic algorithm is used to determine the feasible parking locations. The Petri-net is used to replace the traditional system flow chart and to plan alternative parking routes especially in global space. The parking routine can be performed if the initial assigned route is interfered or when targeted the parking space is occupied. The fuzzy control system is primarily used to derive along an optimal parking route. In this thesis, the overall configuration of the car parking system is introduced. An intelligent parallel parking control scheme is addressed next which includes a trajectory planner, a decisional kernel and a trajectory tracking controller. The optimal solution is then put into several computer simulations to verify the applicability of the proposed control scheme and to manifest the distinguished features of the proposed scheme.en_US
dc.description.tableofcontents誌謝 i 中文摘要 ii Abstract iii Contents iv List of figures v Chapter 1 Introduction 1 Chapter 2 Architecture of Parking System 4 2.1 Problem description 4 2.2 Modeling of the car-like vehicle 4 2.3 Reference trajectories for parallel parking 6 2.4 Ready-for-parking space 7 Chapter 3 Petri Nets and GAs 10 3.1 Introduction of Petri Nets 10 3.1.1 Classical Petri Nets 10 3.1.2 Basic mathematical properties 11 3.2 Character of Petri nets 12 3.3 Optimal path planning with GA 15 3.3.1 Performance specifications 15 3.3.2 Genetic algorithm operators 17 Chapter 4 Fuzzy Controller Design 20 4.1 Problem description & analysis 20 4.2 Consideration of terminal orientation angle 22 4.3 Parameter optimization 23 4.4 Simulation results 24 4.5 Practical application 27 Chapter 5 Conclusion 28 REFERENCES 29zh_TW
dc.subjectGenetic Algorithmen_US
dc.subjectPetri netsen_US
dc.subjectFuzzy Controlen_US
dc.subjectParallel Parkingen_US
dc.titleAutonomous Vehicle Parking Using Hybrid Artificial Intelligent Approachen_US
dc.typeThesis and Dissertationzh_TW
item.openairetypeThesis and Dissertation-
item.fulltextno fulltext-
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