具即時自動跟隨功能之自走車

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姓名

姚嘉翔(Chia-Hsiang Yao) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

具即時自動跟隨功能之自走車
(A Real-time Tracking Algorithm for Human Following Mobile Robot)

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摘要(中)

智慧型機器人其應用廣泛，未來將是人類忠實及信賴的夥伴，也將是人們家庭生活、醫療健康、生活休閒與社會安全的好助手，隨著人類文明發展與個性化生活型態的改變，智慧型機器人將逐漸融入人們的生活中。在日常生活中，有著許許多多能使生活更為便利的機器，而能隨時跟隨著人們的機器人更是一種趨勢，只要機器能夠判斷出需要跟隨的目標，我們就可以不需要操控機器人而使機器人跟著使用者一起行動。
本系統即是使用即時的影像辨識和處理的前提下，設計出一台可以自動跟隨的自走車，設計此自走車共有四大部份：影像處理、距離感測、微控制處理、馬達控制。單一目標的追蹤是自動跟隨系統中最重要的一部分，本系統的追蹤演算法是結合了行人偵測、顏色直方圖的比對、區塊匹配法。當發生衣服顏色相近的情境時，我們透過Kalman Filter的預測器產生的結果找出哪個才是我們追蹤的目標以避免誤判的情形。而距離感測我們使用ZED鏡頭提供的SDK進行測距。最後將追蹤的結果傳回車上的微控制系統進行處理，經由其結果對馬達進行控制，並透過距離感測與目標保持一定的距離，使其成為一台能夠正確辨別目標物及跟隨的自動跟隨自走車。

摘要(英)

In daily life, there are many machines that can make life more convenient. Robots that can follow people at any time has become more trend. As long as the robot can identify the targets that need to be followed, the robot can be operated from the user without having to manipulate the robot.
The design of this Human Following Mobile Robot has four parts: image processing, distance sensing, micro-control processing, and motor control. The ability to detect and track specific people is considered a key prerequisite for serving mobile robots. This paper presents a tracker using a binocular camera capable of tracking a specific human in both indoor and outdoor environments. The proposed tracker detects the target with the combination of human detection, color histogram, and block matching algorithm (BMA). When the color of the object is similar, the position of the object is determined by the predictor of the Kalman filter. Finally, the mobile robot is controlled based on the depth information of the target object.

關鍵字(中)

★ 自動跟隨
★ 基於影像之追蹤演算法
★ 自走車

關鍵字(英)

★ human-following
★ visual tracking
★ Mobile robot

論文目次

Chapter.1 Introduction 1
1.1 Motivation 1
1.2 Object Tracking 2
1.2.1 Point Tracking 3
1.2.2 Kernel Tracking 4
1.2.3 Silhouette Tracking 5
1.3 Thesis Organization 6
Chapter.2 Human Following System 7
2.1 Introduction 7
2.2 Block Matching Algorithm 8
2.3 Human Detection 11
2.3.1 Histogram of Oriented Gradients (HOG) 12
2.3.2 Support Vector Machine (SVM) 14
2.3.3 Region of Interest (ROI) 14
2.4 Target Detection from Color Histogram 15
2.4.1 Simple Foreground Extractor 17
2.4.2 Kalman Filter 19
Chapter.3 Embedded System Design for Human Following System 21
3.1 Specifications for Embedded Systems and Devices 21
3.1.1 Jetson TX1 22
3.1.2 ZED Stereo Camera[20] 23
3.1.3 Wheeled mobile robot platform 25
3.1.4 LI-PO Battery 26
3.2 System Architecture 27
Chapter.4 The Result of Experiment 28
4.1 The Experimental Results with Joining BMA 28
4.2 The Result of Target Tracking 30
4.3 Tracking trajectory 35
Chapter.5 Conclusion 37
Chapter.6 Reference 38

參考文獻

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指導教授

蔡宗漢(Tsung-Han Tsai)

審核日期

2019-1-18

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