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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 連豊力(Feng-Li Lian) | |
| dc.contributor.author | Kuo-Chun Huang | en |
| dc.contributor.author | 黃國郡 | zh_TW |
| dc.date.accessioned | 2022-11-23T09:18:23Z | - |
| dc.date.available | 2021-08-04 | |
| dc.date.available | 2022-11-23T09:18:23Z | - |
| dc.date.copyright | 2021-08-04 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-07-26 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79956 | - |
| dc.description.abstract | 本篇論文針對避障控制系統的問題提出解決方案。本文的主要貢獻包括牛耕式轉行運動與快速沃羅諾伊圖的結合(B-RV)以及具有標準傳感器融合過程的重新規劃導航系統。 B-RV是用以確定機器人的參考路徑亦為全域路徑規劃。結合牛耕式轉行運動和沃羅諾伊路線圖，機器人可以遍歷整個空間。為了使機器人具有更高的智能性，機器人將在每次運行過程中透過相似性比對來優化路徑。迴授過程使機器人更加安全。 對於所提出的導航系統，該機器人不僅能夠應對未知的障礙場景，而且能夠在理論和實作上追蹤路徑。 藉由修改過後的Bug 演算法可以重新規劃覆蓋路徑以解決未知障礙場景的問題。而機器人的定位分成，局部姿態估計和全局姿勢估計。局部姿勢估計將里程計和慣性測量的數據融合在一起，記錄在局部坐標。而全局估計，採用GPS進行全局定位。使用擴展卡爾曼濾波器進行感測器融合後，即可進行機器人控制和導航。 模擬和實驗都在機器人作業系統（ROS）下進行。模擬結果證實所提出演算法在覆蓋路徑過程中比傳統的方法更為有效。為了驗證所提出系統的效果，進行了多次實驗。在草雕和迴授並優化的路徑規劃實驗結果證實所提出的解決方案可以應用在現實世界中。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-23T09:18:23Z (GMT). No. of bitstreams: 1 U0001-2607202109161000.pdf: 20691020 bytes, checksum: 67097249f2e62b66a08c74b2dd578783 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 摘要 i ABSTRACT iii CONTENTS v LIST OF FIGURES viii LIST OF TABLES xii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Formulation 7 1.2.1 Boustrophedon Motions and Rapid Voronoi Diagram (B-RV) 8 1.2.2 Replanning Navigation System with Standard Sensor Fusion Process 10 1.3 Contributions 11 1.3.1 Boustrophedon Motions and Rapid Voronoi Diagram (B-RV) 12 1.3.2 Replanning Navigation System with Standard Sensor Fusion Process 13 1.4 Organization of the Thesis 15 Chapter 2 Background and Literature Survey 16 2.1 Autonomous Driving Systems 16 2.2 Mowing Navigation Systems 17 2.2.1 Real-Time Kinematic Global Positioning System (RTK-GPS) 18 2.2.2 Odometry 19 2.2.3 Ultrasonic Sensor 19 2.2.4 Inertial Measurement Unit (IMU) 20 2.2.5 Sensor Fusion 20 2.3 Coverage Path Planning 22 Chapter 3 Related Algorithms 27 3.1 Equal Map Projection 27 3.2 Canny Edge Detection 28 3.3 Ramer–Douglas–Peucker Algorithm 31 3.4 Approximate k-Nearest Neighbor (k-NN) Searching Using KD-Tree 33 3.5 Dijkstra Algorithm 35 3.6 Similarity Measures 37 3.6.1 Hausdorff Distance 37 3.6.2 Dynamic Time Warping (DTW) 39 3.6.3 Area 41 Chapter 4 System Overview 43 4.1 Preliminaries 43 4.2 Coordinate Frames 44 4.3 System Structure 47 Chapter 5 Boustrophedon Motions and Rapid Voronoi Diagram (B-RV) 50 5.1 System Architecture 51 5.2 Custom Boundary Generator for Grass Carving 52 5.3 Categorized Different Polygons 59 5.4 Sweeping Direction Determining 61 5.5 Grid-Based Boustrophedon Motion for Coverage Path Planning 64 5.6 Comparison of Path within Different Mode 66 5.7 Boustrophedon Motion Cells Sorting 71 5.8 Voronoi Roadmap Construction 74 5.9 Dijkstra Traveling based on Roadmap 77 5.9.1 Determining the Backtracking Point 77 5.9.2 Bridge Each Boustrophedon Motion Cells with Voronoi Roadmap 79 5.10 Feedback Coverage Path Planning by Similarity Measures 81 Chapter 6 Replanning Navigation System with Standard Sensor Fusion Process 86 6.1 Replanning Mechanism based on Modified Bug Algorithm 86 6.2 Pose Estimation with Standard Sensor Fusion Process Using Extended Kalman Filter 89 6.3 Mower Navigation 95 6.3.1 Position Controller 97 6.3.2 Yaw Controller 99 6.4 Summary 100 Chapter 7 Simulation and Experimental Results and Analysis 102 7.1 Overview the Procedures of the Simulations and Experiments 102 7.2 Simulation Setting 107 7.2.1 Simulating Platform 107 7.2.2 Simulation Scenarios 109 7.3 Simulation Results 113 7.3.1 Replanning Mechanism System 113 7.3.2 Feedback Planning by Similarity Measures 116 7.3.3 Comparison of B-RV in Multiple Obstacles Irregular Environment 125 7.4 Experimental Setup 135 7.4.1 Overview of the Environment 135 7.4.2 Hardware Platform 139 7.4.3 Software Platform 144 7.5 Experiments Analysis 145 7.5.1 Grass Carving 145 7.5.2 Feedback Planning by Similarity Measures 150 7.6 Summary 159 Chapter 8 Conclusions and Future Works 161 8.1 Conclusions 161 8.2 Future Works 163 References 165 Notation 174 APPENDIX A 176 | |
| dc.language.iso | en | |
| dc.subject | 沃羅諾伊圖 | zh_TW |
| dc.subject | 機器人 | zh_TW |
| dc.subject | 避障 | zh_TW |
| dc.subject | 覆蓋式路徑規劃 | zh_TW |
| dc.subject | 牛耕式轉行運動 | zh_TW |
| dc.subject | Robot | en |
| dc.subject | Voronoi diagram | en |
| dc.subject | Boustrophedon motions | en |
| dc.subject | Coverage Path Planning | en |
| dc.subject | Obstacle Avoidance | en |
| dc.title | 基於牛耕式轉行運動與快速沃羅諾伊圖結合回授覆蓋式路徑規劃之避障控制系統 | zh_TW |
| dc.title | An Obstacle Avoidance Control System Using Boustrophedon Motions and Rapid Voronoi Diagram Combined with Feedback Coverage Planning | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 李後燦(Hsin-Tsai Liu),黃正民(Chih-Yang Tseng),許志明 | |
| dc.subject.keyword | 機器人,避障,覆蓋式路徑規劃,牛耕式轉行運動,沃羅諾伊圖, | zh_TW |
| dc.subject.keyword | Robot,Obstacle Avoidance,Coverage Path Planning,Boustrophedon motions,Voronoi diagram, | en |
| dc.relation.page | 203 | |
| dc.identifier.doi | 10.6342/NTU202101738 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2021-07-27 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
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| U0001-2607202109161000.pdf | 20.21 MB | Adobe PDF | 檢視/開啟 |
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