本論文研究目的在於建立一套可讓室內自走機器人可有效進行物件搜尋的系統，包含室內自走機器人對物件的初始登錄、移動間看到物件時的更新登錄，並整合成一系列可操作流程架構。
機器人在建立室內地圖後，提供使用者註冊預搜尋物件之影像，同時利用機械視覺標註物品座標並建立座標資料庫，利用此資料庫結合導航系統達成完成智慧機器人了解地圖物件資訊與搜索之目標功能。本研究設計一物件註冊系統，使用RGB-D攝影機擷取預註冊物件之去背影像，並建立該物件資料庫。物件搜尋系統則以SIFT演算法取得偵測特徵點和影像深度學習，提取當前機器人視野影像之物件定界框，利用該定界框投射在點陣雲圖中計算該物件世界座標位置。為減少環境光線變化不穩定因素，本研究利用DBSCAN密度聚類算法規畫一套可適應此定位不穩定之座標歸納系統，可有效並修正估測座標位置誤差。本研究提出之可操作影像註冊系統與物件搜索系統皆可與一般機器人SLAM結合，並有效及時更新物件座標位置。

This research aims to build an effective system for indoor service robots to search for objects. The system is formed by an integrated easy-to-operation structure, which includes an object initial-registration module and real-time in-motion registration module when an object appears to inside the view of the robot.
After the robot builds the indoor map, the users provide the images of the objects to be searched for registration, the vision system will register the positions of the objects in the map, and the data set embedded to the map can be used by the robot for object searching. The object registration system uses RGBD camera to capture the image of the object and removes the background before the SIFT features of this object are created for recognition and the recognition bounding box is used for definition of the object position. In order to reduce the ill-effect of varied illumination conditions to the object recognition, this research implements DBSCAN technique to stabilize and reduce the error of the object positions. This innovative object registration and search system can be integrated to SLAM navigation systems, and provide the effective object search capabilities.

參考文獻
1. SONY公司, https://direct.sony.com/aibo/ .last accessed July 2019
2. Designboom, https://www.designboom.com/technology/vava-mobile-pet-cam-robot-01-11-2019/ .last accessed July 2019
3. 小米公司, https://www.mi.com/tw/mi-robot-vacuum/ .last accessed July 2019
4. Hugh Durrant-Whyte, et al. "Simultaneous Localisation and Mapping (SLAM):
Part I The Essential Algorithms." 2006 IEEE Robotics & Automation Magazine
5. D. Nister, O. Naroditsky, J.Bergen. "Visual odometry." Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.
6. David G. Lowe. "Distinctive Image Features from Scale-Invariant Keypoints" Accepted for publication in the International Journal of Computer Vision, 2004.
7. HerbertBay, AndreasEssa, TinneTuytelaarsb, LucVan Gool. "Speeded-Up Robust Features (SURF)" Computer Vision and Image Understanding Volume 110, Issue 3, June 2008, Pages 346-359
8. Ethan Rublee, Vincent Rabaud, Kurt Konolige, Gary Bradski. "ORB: an efficient alternative to SIFT or SURF " 2011 International Conference on Computer Vision.
9. Martin A. Fischler, Robert C. Bolles "Random Sample Consensus: A Paradigm for Model Fitting with Apphcatlons to Image Analysis and Automated Cartography"
10. Mahalanobis distanc, https://en.wikipedia.org/wiki/Mahalanobis_distance
11. Mathematical morphology, https://en.wikipedia.org/wiki/Mathematical_morphology
12. Robot Operating System (ROS), http://www.iceira.ntu.edu.tw/project-plans/195-robot-operating-system-ros
13. Kinect v2基礎介紹, https://en.wikipedia.org/wiki/Kinect
14. Yingzhong Tian, Xining Liu, Long Li and Wenbin Wang, et al. "Intensity-Assisted ICP for Fast Registration of 2D-LIDAR" Sensors 2019, 19, 2124; doi:10.3390/s19092124
15. Larry Li. "Time-of-Flight Camera – An Introduction SLOA190B" January 2014 Revised May 2014
16. M. Labbé and F. Michaud, "RTAB-Map as an Open-Source Lidar and Visual SLAM Library for Large-Scale and Long-Term Online Operation," in Journal of Field Robotics, vol. 36, no. 2, pp. 416–446, 2019.
17. Lo¨ıc Schwaller, St´ephane Robin and Michael Stumpf. "A closed-form approach to Bayesian inference in tree-structured graphical models." arXiv:1504.02723v4 [stat.ML] May 2017
18. J. Redmon and A. Farhadi. "Yolov3: An incremental improvement." arXiv preprint arXiv:1804.02767, 2018.
19. Gaussian_pyramid, https://en.wikipedia.org/wiki/Pyramid_(image_processing)#Gaussian_pyramid
20. Difference of Gaussians , https://en.wikipedia.org/wiki/Difference_of_Gaussians
21. Saad Albawi, Tareq Abed Mohammed, Saad Al-Zawi."Understanding of a convolutional neural network." 2017 International Conference on Engineering and Technology (ICET)
22. Shuran Song, Samuel P. Lichtenberg, Jianxiong Xiao."SUN RGB-D: A RGB-D Scene Understanding Benchmark Suite" Proceedings of 28th IEEE Conference on Computer Vision and Pattern Recognition (CVPR2015)
23. DBSCAN (Density-Based Spatial Clustering of Applications with Noise. https://de.wikipedia.org/wiki/DBSCAN