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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 連豊力 | zh_TW |
| dc.contributor.advisor | Feng-Li Lian | en |
| dc.contributor.author | 李昀諴 | zh_TW |
| dc.contributor.author | Yun-Xian Li | en |
| dc.date.accessioned | 2024-09-05T16:09:58Z | - |
| dc.date.available | 2024-09-06 | - |
| dc.date.copyright | 2024-09-05 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-08-04 | - |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/95323 | - |
| dc.description.abstract | 科技發展迅速，機器人已經可以獨自執行各種複雜的任務，不需要額外的人為參與，從而提升我們日常生活的便利性。為了讓機器人能夠自主執行任務，機器人必須能夠感知周遭的環境，以便在場景中移動與避開障礙物。
本論文提出一個單眼視覺里程計，用於機器人在都市環境的定位。透過線段偵測、合併、分群與排除異常值，偵測出畫面中建築物外牆上的水平與垂直結構線，並透過矩形幾何約束，從偵測到的線條在三維空間中建立網格平面，經由追蹤建立的網格平面來估測機器人的位置。為了讓本論文所提出的演算法能在即時條件下執行，加入了可靠性測試，透過重投影特徵將估測資料做降取樣處理，進而提升運算的效率。 本論文透過模擬、室內與室外的實驗驗證了演算法的效能，展示在實際的都市環境中定位的能力。 | zh_TW |
| dc.description.abstract | Nowadays, mobile robots can perform complex tasks independently, reducing the requirement for human involvement and thus significantly improving the convenience of our everyday lives. To perform tasks independently, mobile robots need to determine their location, sense its surroundings for navigation and avoid obstacles.
This thesis proposes a monocular visual odometry for a mobile robot localization in urban environments. The proposed algorithm detects the horizontal and vertical structural lines on a building facade using image processing techniques including line segment detection, segments merging, clustering and outlier removal. Then, the rectangular geometric constraint is applied to form the grid mesh plane in 3-D space using the detected line features, and the mobile robot position is estimated by tracking the plane in camera images. For the proposed algorithm to operate in the real-time, a reliability testing is involved to enhance the calculation efficiency by downsampling data via feature reprojection. The proposed algorithm in this thesis has validated the performance through simulations and both indoor and outdoor experiments, demonstrating its capability for localization in noisy urban environments. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-09-05T16:09:58Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-09-05T16:09:58Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 摘要 iii ABSTRACT iv CONTENTS vi LIST OF FIGURES viii LIST OF TABLES xii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Formulation 4 1.3 Contribution 4 1.4 Organization of the Thesis 6 Chapter 2 Background and Literature Survey 7 2.1 Type of Visual Sensors 7 2.2 Data Processing Methods 9 2.3 Estimation Methods 11 Chapter 3 Related Algorithms 12 3.1 Pinhole Camera Model 12 3.2 Line Representation 14 3.3 Density-Based Spatial Clustering of Applications with Noise 15 3.4 Random Sample Consensus 16 Chapter 4 Proposed Algorithm 19 4.1 Overview 19 4.2 Line Segments Detection and Merging 22 4.3 Extract Line Features from Grid Mesh Plane 26 4.3.1 Depth Estimation with Rectangular Constraint 26 4.3.2 Target Plane Detection and Line Features Extraction 29 4.4 Plane Tracking with RANSAC 32 4.4.1 Feature Matching 32 4.4.2 Motion Estimation with RANSAC 32 4.5 Update States 35 4.5.1 Reliability Testing 35 4.5.2 Update Existing Features 36 4.5.3 Add New Features 37 4.5.4 Remove Invalid Features 37 Chapter 5 Synthetic and Real-World Experiments 38 5.1 Evaluate Performance in Simulation 38 5.1.1 Synthetic Scenes 38 5.1.2 Evaluate Performance Using Dynamic Time Warping 45 5.1.3 Estimate Without and With Reliability Testing 47 5.1.4 Summary of Performance in Simulation 60 5.2 Real-World Experiments Executed in Real-Time 61 5.2.1 Experiments Setup 61 5.2.2 Indoor Hallway Experiments 63 5.2.3 Outdoor Building Facade Experiments 69 5.2.4 Summary of Real-World Experiments 77 Chapter 6 Conclusions and Future Works 79 6.1 Conclusions 79 6.2 Future Works 80 References 82 Appendix A Estimated Results of Indoor Hallway Experiments 89 | - |
| dc.language.iso | en | - |
| dc.subject | 線特徵 | zh_TW |
| dc.subject | 視覺里程計 | zh_TW |
| dc.subject | 影像處理 | zh_TW |
| dc.subject | 單眼視覺 | zh_TW |
| dc.subject | 幾何約束 | zh_TW |
| dc.subject | geometric constraint | en |
| dc.subject | monocular vision | en |
| dc.subject | image processing | en |
| dc.subject | line features | en |
| dc.subject | visual odometry | en |
| dc.title | 基於網格平面的線特徵與矩形幾何約束之單眼視覺里程計 | zh_TW |
| dc.title | Monocular Visual Odometry Based on Line Features on Grid Mesh Plane and Rectangular Geometric Constraint | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 王富正;江明理 | zh_TW |
| dc.contributor.oralexamcommittee | Fu-Cheng Wang;Ming-Li Chiang | en |
| dc.subject.keyword | 視覺里程計,線特徵,幾何約束,單眼視覺,影像處理, | zh_TW |
| dc.subject.keyword | visual odometry,line features,geometric constraint,monocular vision,image processing, | en |
| dc.relation.page | 98 | - |
| dc.identifier.doi | 10.6342/NTU202402036 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2024-08-07 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 電機工程學系 | - |
| 顯示於系所單位： | 電機工程學系 | |
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