博碩士論文 104521037 詳細資訊

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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)
★ 即時的SIFT特徵點擷取之低記憶體硬體設計★ 即時的人臉偵測與人臉辨識之門禁系統
★ 應用於多導程心電訊號之無損壓縮演算法與實現★ 離線自定義語音語者喚醒詞系統與嵌入式開發實現
★ 晶圓圖缺陷分類與嵌入式系統實現★ 補償無乘法數位濾波器有限精準度之演算法設計技巧
★ 可規劃式維特比解碼器之設計與實現★ 以擴展基本角度CORDIC為基礎之低成本向量旋轉器矽智產設計
★ JPEG2000靜態影像編碼系統之分析與架構設計★ 適用於通訊系統之低功率渦輪碼解碼器
★ 應用於多媒體通訊之平台式設計★ 適用MPEG 編碼器之數位浮水印系統設計與實現
★ 適用於視訊錯誤隱藏之演算法開發及其資料重複使用考量★ 一個低功率的MPEG Layer III 解碼器架構設計
★ 具有高品質反量化演算的AAC解碼器 之平台式設計★ 適用於第三代行動通訊之最大事後機率演算法發展及渦輪碼解碼器超大型積體電路設計
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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 [1] J. Graham and K. Shillcutt, "Robot tracking of human subjects in field environments," Proceedings of the 8th International Symposium on Artificial Intelligence, Robotics and Automation in Space (2003) pp. 1-7.
[2] L. Mattos and E. Grant, "Passive sonar applications: target tracking and navigation of an autonomous robot," Robotics and Automation, 2004. Proceedings. ICRA ′04. 2004 IEEE International Conference on, 2004, pp. 4265-4270 Vol.5.
[3] J. H. Lee, T. Tsubouchi, K. Yamamoto and S. Egawa, "People Tracking Using a Robot in Motion with Laser Range Finder," 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, 2006, pp. 2936-2942.
[4] G. Feng, Y. Yang, X. Guo and G. Wang, "A compressed infrared motion sensing system for human-following robots," 11th IEEE International Conference on Control & Automation (ICCA), Taichung, 2014, pp. 649-654.
[5] C. Hu, X. Ma and X. Dai, "A Robust Person Tracking and Following Approach for Mobile Robot," 2007 International Conference on Mechatronics and Automation, Harbin, 2007, pp. 3571-3576.
[6] A. Ess, B. Leibe, K. Schindler and L. Van Gool, "A mobile vision system for robust multi-person tracking," 2008 IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, AK, 2008, pp. 1-8.
[7] M. Ramasubramanian, M. A. D. Rangaswamy and G. N. V. R. Reddy, "A survey study on detecting and tracking objective methods," 2014 IEEE National Conference on Emerging Trends In New & Renewable Energy Sources And Energy Management (NCET NRES EM), Chennai, 2014, pp. 159-164.
[8] Greg Welch, Gary Bishop, "An introduction to the Kalman Filter", University of North Carolina at Chapel Hill Department of Computer Science. Tech. Rep., pp. 95-041, July 2006.
[9] Particle Filtering https://artint.info/html/ArtInt_158.html
[10] Yizong Cheng, "Mean shift, mode seeking, and clustering," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no. 8, pp. 790-799, Aug. 1995.
[11] Reoxiang Li, Bing Zeng and M. L. Liou, "A new three-step search algorithm for block motion estimation," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 4, no. 4, pp. 438-442, Aug 1994.
[12] Shan Zhu and Kai-Kuang Ma, "A new diamond search algorithm for fast block matching motion estimation," Proceedings of ICICS, 1997 International Conference on Information, Communications and Signal Processing. Theme: Trends in Information Systems Engineering and Wireless Multimedia Communications (Cat., 1997, pp. 292-296 vol.1.
[13] Ce Zhu, Xiao Lin, L. Chau and Lai-Man Po, "Enhanced hexagonal search for fast block motion estimation," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 10, pp. 1210-1214, Oct. 2004.
[14] H. A. Choudhury and M. Saikia, "Survey on block matching algorithms for motion estimation," 2014 International Conference on Communication and Signal Processing, Melmaruvathur, 2014, pp. 036-040.
[15] T. Baraskar, V. R. Mankar and R. Jain, "Survey on block based pattern search techniques for motion estimation," 2015 International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), Davangere, 2015, pp. 513-518.
[16] K. Belloulata, S. Zhu, J. Tian and X. Shen, "A novel cross-hexagon search algorithm for fast block motion estimation," International Workshop on Systems, Signal Processing and their Applications, WOSSPA, Tipaza, 2011, pp. 1-4.
[17] N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR′05), San Diego, CA, USA, 2005, pp. 886-893 vol. 1.
[18] INRIA video segmentation dataset. http://pascal.inrialpes.fr/data/human/
[19] O. Barnich and M. Van Droogenbroeck, "ViBe: A Universal Background Subtraction Algorithm for Video Sequences," in IEEE Transactions on Image Processing, vol. 20, no. 6, pp. 1709-1724, June 2011.
[19] ZED stereo camera. https://www.stereolabs.com/zed/
[20] Innorover輪型越野自走車http://resource.innovati.com.tw/
[21] Klein, D.: BoBot - Bonn benchmark on tracking. https://archive.is/UBw37
指導教授 蔡宗漢(Tsung-Han Tsai) 審核日期 2019-1-18
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