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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57113完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 傅立成(Li-Chen Fu) | |
| dc.contributor.author | Yu-Chi Lin | en |
| dc.contributor.author | 林友騏 | zh_TW |
| dc.date.accessioned | 2021-06-16T06:35:16Z | - |
| dc.date.available | 2017-08-04 | |
| dc.date.copyright | 2014-08-04 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-08-04 | |
| dc.identifier.citation | [1] Y. Ye and J. K. Tsotsos, 'Sensor Planning for 3D Object Search,' CVIU, vol. 73, pp. 145-168, 1999.
[2] K. Sjo, D. Lopez, C. Paul, P. Jensfelt, and D. Kragic, 'Object Search and Localization for an Indoor Mobile Robot,' Journal of Computing and Information Technology, pp. 67–80, 2009. [3] A. Aydemir, M. Gobelbecker, A. Pronobis, K. Sjoo, and P. Jensfelt, 'Plan-based Object Search and Exploration Using Semantic Spatial Knowledge in the Real World,' in Proceedings of the 5th European Conference on Mobile Robots (ECMR'11), ed, 2011. [4] A. Aydemir, K. Sjoo, J. Folkesson, A. Pronobis, and P. Jensfelt, 'Search in the real world: Active visual object search based on spatial relations,' in 2011 IEEE International Conference on Robotics and Automation (ICRA), 2011, pp. 2818-2824. [5] J. Ma, T. H. Chung, and J. Burdick, 'A probabilistic framework for object search with 6-DOF pose estimation,' Int. J. Rob. Res., vol. 30, pp. 1209-1228, 2011. [6] L. L. S. Wong, L. P. Kaelbling, and T. Lozano-Perez, 'Manipulation-based active search for occluded objects,' in 2013 IEEE International Conference on Robotics and Automation (ICRA), 2013, pp. 2814-2819. [7] M. Dogar, M. Koval, A. Tallavajhula, and S. Srinivasa, 'Object search by manipulation,' in 2013 IEEE International Conference on Robotics and Automation (ICRA), 2013, pp. 4973-4980. [8] M. Dogar, M. Koval, A. Tallavajhula, and S. Srinivasa, 'Object search by manipulation,' Autonomous Robots, vol. 36, pp. 153-167, 2014/01/01 2014. [9] M. Gupta, T. Ruhr, M. Beetz, and G. S. Sukhatme, 'Interactive environment exploration in clutter,' in 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013, pp. 5265-5272. [10] R. B. Rusu and S. Cousins, '3D is here: Point Cloud Library (PCL),' in 2011 IEEE International Conference on Robotics and Automation (ICRA), 2011, pp. 1-4. [11] P. E. Hart, N. J. Nilsson, and B. Raphael, 'A Formal Basis for the Heuristic Determination of Minimum Cost Paths,' IEEE Transactions on Systems Science and Cybernetics, vol. 4, pp. 100-107, 1968. [12] M. A. Fischler and R. C. Bolles, 'Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,' Commun. ACM, vol. 24, pp. 381-395, 1981. [13] C. Harris and M. Stephens, 'A combined corner and edge detector,' in In Proc. of Fourth Alvey Vision Conference, ed, 1988, pp. 147-151. [14] I. Sipiran and B. Bustos, 'Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes,' The Visual Computer, vol. 27, pp. 963-976, 2011. [15] F. Tombari, S. Salti, and L. Di Stefano, 'A combined texture-shape descriptor for enhanced 3D feature matching,' in 2011 18th IEEE International Conference on Image Processing (ICIP), 2011, pp. 809-812. [16] S. Salti, F. Tombari, and L. Di Stefano, 'SHOT: Unique signatures of histograms for surface and texture description,' Computer Vision and Image Understanding, vol. 125, pp. 251-264, 2014. [17] P. J. Besl and N. D. McKay, 'A method for registration of 3-D shapes,' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, pp. 239-256, 1992. [18] M. Dogar, K. Hsiao, M. Ciocarlie, and S. Srinivasa, 'Physics-Based Grasp Planning Through Clutter,' in Proceedings of Robotics: Science and Systems, ed. Sydney, Australia, 2012. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57113 | - |
| dc.description.abstract | 隨著機器人與相關研究的發展由工廠漸漸走向辦公室及家庭環境,機器人在人類生活環境中服務與互動顯得十分重要,機器人應該要能做為人類生活中的幫手並提供各式服務,而在各項服務中,搜尋並遞送物品對使用者來說是很實用的一項技能。為了達成此功能,前人的研究多假設物品放在開放空間中,機器人在室內環境中以影像搜尋目標物並抓取之,過程中機器人規劃出最佳的路徑移動並且徹底觀察環境中的每個角落。然而,在真實世界中,物品很可能被其他物品所阻擋以致單純的影像搜尋不可能找到物品,因此,近期的文獻提及了以機器手臂移除障礙物以達成目標物搜尋之規劃,這些研究成果規劃機器人移動障礙物的順序並探索後方空間。
在本篇論文中,我們結合了以機器手臂移除障礙物與視覺主動搜尋之規劃,提出了一整合兩種方式之物品搜尋系統,機器人可以變換位置觀察環境,亦可以使用手臂移動障礙物來進行搜尋。本篇論文提出之規劃概念是以最小化預期搜尋時間以及在發現目標物後最小化目標物抓取時間為目標,使用A*演算法並在搜尋空間內進行取樣以達成在有限時間內完成規劃。此外,本論文加入了視覺回授以確保機器人準確地執行計畫。最後,我們透過在書架內物品阻擋的環境中搜尋目標物的實驗來驗證本論文提出方法之優越性。 | zh_TW |
| dc.description.abstract | As robots and robotic researches marching from factory to office and home, the ability of robot to interact with complex human-living environment becomes pivotal. To show its value, the robot should be able to do various tasks as an assistant in human-living environment. Searching and delivering object in indoor environment is one of the tasks practical to user. Previous study mainly focused on visual search of objects in indoor environment. The search is performed by a mobile robot which plans a best route to observe the environment and discover the target object. However, in real world, objects may be occluded by other objects or structures, which means pure visual search is impossible to find these targets. As a result, some recent works discussed the object search method by removing objects that block and hide the target object.
In this thesis, we propose an object search planning system that combines visual and arm manipulation search. The robot can either reposition one of the accessible object with its arm or move its platform to view the environment from a different position to discover the target object. The concept of planning is A* Planning which minimizes the expected time to discover the target and then the time to grasp the target in clutter after its discovery. Visual sensor feedback is included to assure the accuracy of each action performed by the robot. We evaluate the proposed approach with experiment in the scenario of object search in a shelf environment where objects may occlude or block access to one another. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T06:35:16Z (GMT). No. of bitstreams: 1 ntu-103-R01921003-1.pdf: 3148284 bytes, checksum: 044fb0c40d6046f1e66b0e620767f4b7 (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i 中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vii LIST OF TABLES ix Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Formulation 2 1.3 Challenges 4 1.4 Related Works 4 1.5 Objectives 6 1.6 Thesis Organization 6 Chapter 2 Preliminaries 7 2.1 System Overview 7 2.1.1 Hardware System 7 2.1.2 Software System 8 2.2 A* Algorithm 8 2.3 Random Sample Consensus (RANSAC) 9 2.4 Object Feature Detector & Descriptor 10 2.4.1 5D Harris Corner Detector 10 2.4.2 ColorSHOT Descriptor 12 Chapter 3 Workspace Model and Object Models 14 3.1 Workspace Model 14 3.2 Object Geometry Model 16 3.2.1 Geometric Primitive Model-based Object Modeling 16 3.3 Object Pose Model 17 3.4 Object Manipulation Model 18 3.4.1 Grasp Manipulation 18 3.4.2 Place Manipulation 19 3.4.3 Push-aside Manipulation 20 3.5 Object Pose Prediction after Manipulation 21 3.5.1 Grasp Manipulation 21 3.5.2 Push-aside Manipulation 22 Chapter 4 Planning and Sensor Feedback in Execution 24 4.1 Robot Pose Sampling 24 4.2 Search Planning 25 4.2.1 Actions in Search Planning 25 4.2.2 RGB-D Camera Perception Model 26 4.2.3 Hidden Target and Reveal Condition 27 4.2.4 Object Accessibility in Search Planning 28 4.2.5 Graph in Search Planning 28 4.2.6 A* Object Search Planning 29 4.2.7 Action Sampling in Search Planning 32 4.3 Grasp Planning 33 4.3.1 Object Accessibility in Grasp Planning 34 4.3.2 Graph in Grasp Planning 34 4.3.3 A* Object Grasp Planning 35 4.3.4 Action Sampling in Grasp Planning 36 4.4 Sensor Feedback in Execution 38 4.4.1 Object Registration 38 4.4.2 Object Pose Estimation 40 4.4.3 Grasp Action Sensor Feedback 40 4.4.4 Move Action Sensor Feedback 41 Chapter 5 Experiment Result 42 5.1 Experiment Setting 42 5.2 Evaluation on Object Search Planning 42 5.3 Evaluation on Object Grasp Planning 51 5.4 Overall Test 54 Chapter 6 Conclusion 57 6.1 Future Works 57 REFERENCE 59 | |
| dc.language.iso | en | |
| dc.subject | 機器手臂操作 | zh_TW |
| dc.subject | 搜尋物體規劃 | zh_TW |
| dc.subject | 辦公室機器人 | zh_TW |
| dc.subject | robot arm manipulation | en |
| dc.subject | object search planning | en |
| dc.subject | office robot | en |
| dc.title | 基於搜尋演算法之規劃移動式機器手臂尋找與夾取遮蔽目標物 | zh_TW |
| dc.title | Search Algorithm based Planning on Finding and Grasping of
Occluded Target Object with a Mobile Robot Manipulator | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 羅仁權(Ren C. Luo),宋開泰(Kai-Tai Song),胡竹生(Jwu-Sheng Hu),范欽雄(Chin-Shyurng Fahn) | |
| dc.subject.keyword | 機器手臂操作,搜尋物體規劃,辦公室機器人, | zh_TW |
| dc.subject.keyword | robot arm manipulation,object search planning,office robot, | en |
| dc.relation.page | 60 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-08-04 | |
| 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 |
| 顯示於系所單位: | 電機工程學系 | |
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|---|---|---|---|
| ntu-103-1.pdf 未授權公開取用 | 3.07 MB | Adobe PDF |
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