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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅立成(Li-Chen Fu) | |
| dc.contributor.author | Hao-Yun Chen | en |
| dc.contributor.author | 陳顥云 | zh_TW |
| dc.date.accessioned | 2022-11-25T07:45:57Z | - |
| dc.date.available | 2024-08-31 | |
| dc.date.copyright | 2021-11-08 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-08-16 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/82508 | - |
| dc.description.abstract | 隨著時間推移，社會逐漸邁向高齡化以及少子化，進而衍伸了許多如居家照護、勞動成本上升等問題。而機器人近年來的發展恰好為以上問題提供了可能的解決方案。除了在自動化工廠或是倉儲系統中提供服務外，我們希望機器人能夠更進一步在一般民眾的日常生活中協助人們，而為了能夠使機器人在不同場合中提供各式的服務或完成不同的任務，機器人的定位、移動與感知能力尤為重要。其中移動能力正是使機器人能夠提供服務不可或缺的基礎功能。在獲取自身位置資訊以及目標位置後，機器人必須能夠規劃出恰當的路徑到達目標點以進行後續的互動或服務。在現實生活中，機器人的移動導航經常會面臨動態的環境，其中人群的移動是最為常見且容易對機器人的移動造成影響。因此需要建立一個能夠考慮人群動態變化並規劃自身路徑的系統。另外，在人類環境中機器人的移動必須考慮社會觀感，路徑的規畫除了必須考慮移動效率外，也必須同時遵守社會規範以更好的融入人們生活之中。 在本篇研究中，我們提出了一個階層式的路徑規劃算法，首先利用RGB相機結合LiDAR捕捉到機器人周圍的局部人群移動，並且對於機器人附近人們的移動進行預測，接著透過對於人群的分析配合全局路徑規劃器產生機器人適當的全局移動路徑，在決定全局路徑後底層的控制系統接收高階層全局路徑以及周遭人群的預測結果，同時在考慮社會規範後產生對機器人實際的速度控制命令。借助電腦視覺對人類識別的高準確率以及LiDAR的高精度，系統能夠精準的追蹤周圍人類位置。透過高階層路徑規劃，機器人能夠在面對不同場景時使用不同的移動策略，進而使機器人能夠更加靈活的在各種情況下進行移動，而對人群的預測則讓機器人能產生更加高效且符合社會規範的路徑。藉由此系統，機器人在面對由人群造成的高度動態環境中，仍然可以成功規劃出適當的路徑並且在不造成他人心理不適的情況下成功地抵達目的地。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-25T07:45:57Z (GMT). No. of bitstreams: 1 U0001-1608202120174100.pdf: 5008268 bytes, checksum: fdc1a6cf84f6804beb6d343f0e2b64ce (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 口試委員會審定書 # 致謝 I 摘要 II ABSTRACT III TABLE OF CONTENTS V LIST OF FIGURES VIII LIST OF TABLES XI Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Research objectives 3 1.3 Contributions 4 1.4 Thesis Overview 5 Chapter 2 Background and Related Work 6 2.1 Robot Operating System 6 2.2 Mobile Robot Navigation 7 2.3 SLAM and Localization 12 2.4 Crowd Navigation 14 2.4.1 Optimization Based 15 2.4.2 Learning based 18 Chapter 3 Methodology 20 3.1 Human Detection and Tracking 20 3.1.1 Preliminary 21 3.1.1.1 Introduction to Stereo Camera 21 3.1.1.2 Introduction to 3D LiDAR 22 3.1.2 Methodology 24 3.1.2.1 Object detection 24 3.1.2.2 Human Tracking with Unscented Kalman Filter 27 3.1.2.3 LiDAR Camera Calibration 29 3.1.2.4 Multi-Sensor human detection and tracking 31 3.2 Human trajectory prediction and clustering 33 3.2.1 Preliminary 34 3.2.1.1 Generative adversarial network 34 3.2.1.2 Social GAN network 36 3.2.1.3 Human Group Clustering 38 3.3 Hierarchical Crowd Navigation System 40 3.3.1 System Overview 40 3.3.2 Preliminary 41 3.3.2.1 ROS Navigation Framework 41 3.3.3 Methodology 42 3.3.3.1 High-level global path planning by human detection and clustering 42 3.3.3.2 Low-Level Modified Timed-Elastic Band by Predicted Human Trajectory 45 Chapter 4 Experiment 52 4.1 Navigation in Recorded Crowd Environment Dataset 52 4.1.1 Experiment Setup 52 4.1.2 Experiment Results 55 4.2 Navigation in Simulated Crowd Environment 59 4.3 Navigation in Real World Environment 61 Chapter 5 Conclusion and Future Work 67 REFERENCES 69 | |
| dc.language.iso | en | |
| dc.subject | 社交導航 | zh_TW |
| dc.subject | 行人軌跡預測 | zh_TW |
| dc.subject | 群眾間導航 | zh_TW |
| dc.subject | pedestrian trajectory prediction | en |
| dc.subject | Crowd Navigation | en |
| dc.subject | Social Navigation | en |
| dc.title | 基於混合式感測及周遭行人軌跡預測的移動型機器人在人群中之社交導航 | zh_TW |
| dc.title | Social Crowd Navigation of a Mobile Robot based on Human Trajectory Prediction and Hybrid Sensing | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 陳政維(Cheng-Wei Chen) | |
| dc.contributor.oralexamcommittee | 宋開泰(Hsin-Tsai Liu),張文中(Chih-Yang Tseng),許永真 | |
| dc.subject.keyword | 群眾間導航,社交導航,行人軌跡預測, | zh_TW |
| dc.subject.keyword | Crowd Navigation,Social Navigation,pedestrian trajectory prediction, | en |
| dc.relation.page | 73 | |
| dc.identifier.doi | 10.6342/NTU202102407 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2021-08-17 | |
| 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 |
| dc.date.embargo-lift | 2024-08-31 | - |
| 顯示於系所單位： | 電機工程學系 | |
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