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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 王立昇 | |
| dc.contributor.author | Chih-Yuan Wu | en |
| dc.contributor.author | 吳至原 | zh_TW |
| dc.date.accessioned | 2021-06-08T02:51:12Z | - |
| dc.date.copyright | 2017-08-25 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2017-08-15 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/20508 | - |
| dc.description.abstract | 本文研究主旨為強化用於擬剛體編隊控制之載具定位與姿態識別系統，由一台高處攝影機進行影像補捉及載具監控，提供一個全域座標系統，結合影像處理與K-means分群法，使擬剛體隊形系統掌握各載具的絕對位置、姿態，並能在複雜的環境下適應及辨識出載具，將原本獨立的各載具編成擬剛體隊形後搭配路徑規劃演算法，實際整合軟硬體並進行實驗。
我們採用擬剛體編隊法設計多載具的運動隊形，將擬剛體的形變理論用在編隊設計上，使多載具隊形的變化由一組空間齊性形變張量決定，並容許隊形拉伸、剪變、旋轉，使隊形更能適應較複雜的環境。在路徑規劃部分以快速探索隨機樹(RRT)，配合路線平化技巧建構出隊伍中心路徑。接著設計虛擬位能函數來得到擬剛體的形變張量求得各載具之規劃路徑。 系統首先由M3006V網路攝影機偵測各載具初始座標與姿態，接著計算出個別載具與其所設定之擬剛體編隊初始化的隊形位置距離與期望的姿態夾角，回傳給主控電腦控制載具進行編隊初始化任務。初始化任務完畢後，由Kinect初步偵測環境並於主控電腦規劃路徑，於隊伍運動中以多載具協同機制控制載具間的運動以完成編隊運動之任務。 | zh_TW |
| dc.description.abstract | The purpose of this thesis is to design an initialization scheme for the pseudo-rigid formation control of a multi-vehicle system. The scheme combines K-means clustering method and image processing method. By these methods, we can identify and control each vehicle by integrating the path-planning algorithm, hardware and software in the experiments.
The concept adopted to design the formation of vehicles is the pseudo-rigid body theory, which is determined by a homogenous deformation tensor. It allows the formation to stretch, to shear and to rotate, making it adapt to the complex environment. In addition, the Rapidly-Exploring Random Tree (RRT) method was used with the technique of route adjustments to construct the motion of formation center. Then, the deformation matrix is found by utilizing the method of virtual potential function, in which the routes of each vehicle are computed. In the initialization process, firstly we use the Webcam M3006V to detect the environment and to perform the path-planning algorithm on the main control computer. The color noises in the environment can be removed through the K-means theory. Once the initialization process is done, the coordinated control algorithm for multi-vehicle system is designed for route-following situations. The sensor Kinect was used to detect the obstacle boundary, ultrasonic system was invoked to detect the distance of obstacles, Fuzzy theory was applied to adjust the parameter of the deformation matrix. Experimental results showed that the designed initialization scheme works so that the pseudo-rigid formation can be realized to attain the destination while the obstacle can be avoided | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T02:51:12Z (GMT). No. of bitstreams: 1 ntu-106-R03543042-1.pdf: 3073592 bytes, checksum: 71cdff2fa0ae80402f4b64d9472f7f24 (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 致謝 I
中文摘要 II ABSTRACT III 目錄 IV 圖目錄 VII 表目錄 X 第一章 緒論 1 1.1 前言與研究動機 1 1.2 文獻回顧 2 1.2.1 多載具路徑規劃 2 1.2.2 擬剛體 3 1.2.3 分群法 3 1.3 研究內容與成果 4 1.4 論文架構 5 第二章 擬剛體編隊設計與路徑規劃 6 2.1 擬剛體介紹 6 2.2 擬剛體隊形表示法 8 2.3 路徑規劃 11 2.3.1 快速探索隨機樹(Rapidly-Exploring Random Tree) 12 2.3.2 路徑縮短 13 2.3.3 虛擬力場調整路徑 14 2.3.4 貝茲曲線平滑 16 2.3.5 禁止路徑 17 2.4 擬剛體編隊設計 18 2.4.1 Lennard-Jones potential介紹 18 2.4.2 內部虛擬位能函數 19 2.4.3 外部虛擬位能函數 20 2.4.4 虛擬位能函數分析 20 第三章 硬體架構與系統整合 22 3.1 硬體架構 22 3.1.1 M3006V型網路攝影機 23 3.1.2 Kinect 感測器 24 3.1.3 超音波感測器 27 3.1.4 馬達編碼器(Encoder) 29 3.2 系統運作架構 30 3.2.1 整體架構 30 3.2.2 編隊初始化策略 31 第四章 影像處理 32 4.1 影像基本概念 32 4.2 HSV色彩模型與轉換 33 4.2.1 HSV色彩模型 33 4.2.2 RGB與HSV轉換 33 4.3 影像分割 34 4.4 影像二值化 34 4.5 數學形態學 35 4.6 攝影機校正 38 第五章 K-MEANS分群法 40 5.1 K-MEANS簡介 40 5.2 K-MEANS分群法 41 5.2.1 概念 41 5.2.2 SSE 41 5.2.3 K-means分群法求解流程 42 5.3 ELBOW METHOD 44 5.4 加入ELBOW METHOD之K-MEANS分群法求解流程 46 第六章 控制器與避障設計 48 6.1 載具運動方程式 48 6.2 載具路徑追蹤控制 49 6.2.1 模糊控制簡介 49 6.2.2 路徑追蹤控制 50 6.3 擬剛體初始化編隊 54 6.3.1 姿態調整策略 54 6.3.2 載具隊形初始化策略 55 6.4 多載具協同控制 56 第七章 擬剛體編隊結合視覺系統之實驗與分析 58 7.1 實驗架構 58 7.2 攝影機校正與影像分割實驗 58 7.2.1 攝影機校正實驗 58 7.2.2 影像分割 60 7.3 加入K-MEANS分群法顏色定位實驗 62 7.3.1 單純環境下定位實驗 62 7.3.2 複雜環境下定位實驗 64 7.4 擬剛體編隊行進實驗 69 第八章 結論與未來方向 70 參考文獻 71 | |
| dc.language.iso | zh-TW | |
| dc.title | 基於K-means分群法全域影像定位之擬剛體編隊控制 | zh_TW |
| dc.title | Global Vision Positioning System based on K-means Clustering for Pseudo-rigid Formation Control | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 105-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 卓大靖,王和盛,張帆人 | |
| dc.subject.keyword | 擬剛體,編隊,K-means,路徑規劃, | zh_TW |
| dc.subject.keyword | Pseudo-Rigid Body,Formation,K-means,Path-Planning, | en |
| dc.relation.page | 74 | |
| dc.identifier.doi | 10.6342/NTU201703287 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2017-08-15 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 應用力學研究所 | zh_TW |
| 顯示於系所單位： | 應用力學研究所 | |
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