請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72125完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 連豊力(Feng-Li Lian) | |
| dc.contributor.author | Jyun-Sheng Fu | en |
| dc.contributor.author | 傅鈞笙 | zh_TW |
| dc.date.accessioned | 2021-06-17T06:24:36Z | - |
| dc.date.available | 2021-08-21 | |
| dc.date.copyright | 2018-08-21 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-08-17 | |
| dc.identifier.citation | References
[1: Engel et al. 2014] J. Engel, T. Schops, and D. Cremers, “LSD-SLAM: Large-scale direct monocular SLAM,” in Proceedings of the European Conference on Computer Vision (ECCV), Zurich, Switzerland, 2014. [2: Yamauchi 1997] B. Yamauchi, “A frontier-based approach for autonomous exploration,” in Proceedings of the 1997 IEEE International symposium on computational intelligence in robotics and automation (CIRA-97), Orlando, FL, USA, pp. 146–151. [3: Julier & Uhlmann 1997] S. Julier and J. Uhlmann. “A new extension of the Kalman filter to nonlinear systems,” in Proceedings of the International Symposium on Aerospace/Defense Sensing, Simulation and Controls, 1997. [4: Arulampalam et al. 2002] M. S. Arulampalam, S. Maskell, N. Gordon and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” in IEEE Transactions on Signal Processing, vol. 50, no. 2, pp. 174-188, Feb. 2002. [5: Grisetti et al. 2007] G. Grisetti, C. Stachniss and W. Burgard, “Improved Techniques for Grid Mapping with Rao-Blackwellized Particle Filters,” in IEEE Transactions on Robotics, vol. 23, no. 1, pp. 34-46, Feb. 2007. [6: Grisetti et al. 2005] G. Grisetti, C. Stachniss, and W. Burgard, “Improving grid-based SLAM with Rao-Blackwellized particle filters by adaptive proposals and selective resampling,” in Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, pp. 2443–2448, 2005. [7: Gonzalez-Banos et al. 2002] H. H. Gonzalez-Banos and J.-C. Latombe, “Navigation strategies for exploring indoor environments,” in the International Journal of Robotics Research, vol. 21, no. 10-11, pp. 829–848, 2002. [8: Aghili & Yu 2016] F. Aghili and C. Y. Su, “Robust Relative Navigation by Integration of ICP and Adaptive Kalman Filter Using Laser Scanner and IMU,” in IEEE/ASME Transactions on Mechatronics, vol. 21, no. 4, pp. 2015-2026, Aug. 2016. [9: Arun et al. 1987] K. S. Arun, T. S. Huang and S. D. Blostein, “Least-Squares Fitting of Two 3-D Point Sets,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-9, no. 5, pp. 698-700, Sept. 1987. [10: Mur-Arta et al. 2015] R. Mur-Artal, J. M. M. Montiel and J. D. Tardós, “ORB-SLAM: A Versatile and Accurate Monocular SLAM System,” in IEEE Transactions on Robotics, vol. 31, no. 5, pp. 1147-1163, Oct. 2015. [11: Concha & Civera 2015] A. Concha and J. Civera, “DPPTAM: Dense piecewise planar tracking and mapping from a monocular sequence,” in Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, pp. 5686-5693, 2015. [12: Keidar & Kaminka 2014] Matan Keidar and Gal A. Kaminka, “Efficient frontier detection for robot exploration,” in the International Journal of Robotics Research, vol. 33, no. 2, pp. 215–236, Feb. 2014. [13: Labbé & Michaud 2014] M. Labbé and F. Michaud, “Online global loop closure detection for large-scale multi-session graph-based SLAM,” in Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA, pp. 2661-2666, 2014. [14: Kümmerle et al. 2011] R. Kümmerle, G. Grisetti, H. Strasdat, K. Konolige and W. Burgard, “G2o: A general framework for graph optimization,” in Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China, pp. 3607-3613, 2011. [15: Engel et al. 2014] Jakob Engel, Jürgen Sturm, Daniel Cremers. “Scale-aware navigation of a low-cost quadrocopter with a monocular camera,” in Robotics and Autonomous Systems, Volume 62, Issue 11, pp. 1646-1656, 2014. [16: Engel et al. 2013] J. Engel, J. Sturm and D. Cremers, “Semi-dense Visual Odometry for a Monocular Camera,” in Proceedings of the IEEE International Conference on Computer Vision, Sydney, NSW, Australia, 2013. [17: Moravec 1998] Hans Moravec, “Sensor fusion in certainty grids for mobile robots,” in AI Magazine, Volume 9 Issue 2, pp. 61-74, 1988. [18: Donald Meagher 1982] Donald Meagher, “Geometric modeling using octree encoding,” in Computer Graphics and Image Processing, Volume 19, Issue 2, pp. 129-147. Rensselaer Polytechnic Institute, Troy, New York, USA, 1982. [19: Hornung et al. 2013] A. Hornung, K.M. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard, “OctoMap: An Efficient Probabilistic 3D Mapping Framework Based on Octrees” in Autonomous Robots, pp. 34-189, 2013. [20: Bourgault et al. 2002] F. Bourgault, A. A. Makarenko, S. B. Williams, B. Grocholsky and H. F. Durrant-Whyte, “Information based adaptive robotic exploration,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland, vol.1, pp. 540-545, 2002. [21: Carrillo et al. 2015] H. Carrillo, P. Dames, V. Kumar and J. A. Castellanos, “Autonomous robotic exploration using occupancy grid maps and graph SLAM based on Shannon and Rényi Entropy,” in Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, pp. 487-494, 2015. [22: Stumberg et al. 2017] L. von Stumberg, V. Usenko, J. Engel, J. Stückler and D. Cremers, “From monocular SLAM to autonomous drone exploration,” in Proceedings of the 2017 European Conference on Mobile Robots (ECMR), Paris, France, pp. 1-8, 2017. [23: Heng et al. 2015] L. Heng, A. Gotovos, A. Krause and M. Pollefeys, “Efficient visual exploration and coverage with a micro aerial vehicle in unknown environments,” in Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, pp. 1071-1078, 2015. [24: Alvarez et al. 2016] H. Alvarez, L.M. Paz, J. Sturm, D. Cremers, “Collision Avoidance for Quadrotors with a Monocular Camera,” in Experimental Robotics. Springer Tracts in Advanced Robotics, vol. 109. Springer, Cham, 2016. [25: Cadena et al. 2016] Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, Davide Scaramuzza, Jose Neira, Ian Reid, and John J. Leonard, “Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age,” in IEEE Transactions on Robotics, vol. 32, no. 6, pp. 1309-1332, Dec. 2016. [26: Leung et al. 2006] C. Leung, S. Huang and G. Dissanayake, “Active SLAM using Model Predictive Control and Attractor based Exploration,” in Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, pp. 5026-5031, 2006 [27: Shih et al. 1990] C. L. Shih, T. T. Lee and W. A. Gruver, “A unified approach for robot motion planning with moving polyhedral obstacles,” in IEEE Transactions on Systems, Man, and Cybernetics, vol. 20, no. 4, pp. 903-915, 1990. [28: Antonelli et al. 2005] G. Antonelli, S. Chiaverini and G. Fusco, “A calibration method for odometry of mobile robots based on the least-squares technique: theory and experimental validation,” in IEEE Transactions on Robotics, vol. 21, no. 5, pp. 994-1004, 2005. [29: Pei & Kleeman 2017] Y. Pei and L. Kleeman, “A novel odometry model for wheeled mobile robots incorporating linear acceleration,” in Proceedings of the 2017 IEEE International Conference on Mechatronics and Automation (ICMA), Takamatsu, Japan, 2017. [30: Doucet et al. 2001] A. Doucet, N. de Freitas, N. Gordon, “An Introduction to Sequential Monte Carlo Methods,” in Sequential Monte Carlo Methods in Practice. Statistics for Engineering and Information Science. Springer, New York, NY, 2001. [31: Endres et al. 2014] F. Endres, J. Hess, J. Sturm, D. Cremers and W. Burgard, “3-D Mapping with an RGB-D Camera,” in IEEE Transactions on Robotics, vol. 30, no. 1, pp. 177-187, 2014. [32: Pizzoli et al. 2014] M. Pizzoli, C. Forster and D. Scaramuzza, “REMODE: Probabilistic, monocular dense reconstruction in real time,” in Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, pp. 2609-2616, 2014. [33: Leutenegger et al. 2015] S. Leutenegger, S. Lynen, M. Bosse, R. Siegwart, and P. Furgale, “Keyframe-based visual-inertial odometry using nonlinear optimization,” in The International Journal of Robotics Research, vol. 34, no. 3, pp. 314–334, 2015. [34: Cieslewski et al. 2017] T. Cieslewski, E. Kaufmann and D. Scaramuzza, “Rapid exploration with multi-rotors: A frontier selection method for high speed flight,” in Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada, pp. 2135-2142, 2017. [35: Quigley et al. 2009] M. Quigley, B. Gerkey, K. Conley, J. Faust, T. Foote, J. Leibs, E. Berger, R. Wheeler and A. Ng, “ROS: an open-source Robot Operating System,” ICRA Workshop on Open Source Software, 2009. [36: Koenig & Howard 2004] N. Koenig and A. Howard, “Design and use paradigms for Gazebo, an open-source multi-robot simulator,” in Proceedings of the International Conference on Intelligent Robots and Systems (IROS), Japan, vol.3, pp. 2149-2154, 2004. [37: Cormen et al. 2009] Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein, “Dijkstra’s algorithm,” in Introduction to Algorithms, 3rd edition. MIT Press, USA, 2009. [38: Cormen et al. 2009] Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein, “Heap sort,” in Introduction to Algorithms, 3rd edition. MIT Press, USA, 2009. [39: Laganière 2011] Robert Laganière, “Estimating Projective Relations in Images,” in OpenCV 2 computer vision application programming cookbook: Over 50 recipes to master this library of programming functions for real-time computer vision. Packt Pub, Birmingham, UK, 2011. Websites: [40: Lypiridis 2016] Giannis Lypiridis. (Jul. 2016). ardrone_simulator_gazebo7. GitHub repository. [Online]. Available: https://github.com/iolyp/ardrone_simulator_gazebo7.git [41: Monajjemi 2016] Mani Monajjemi et al. (2016). ardrone_autonomy. GitHub repository. [Online]. Available: https://github.com/AutonomyLab/ardrone_autonomy.git [42: Acuna 2017] Raul Acuna (2017). ardrone_velocity. GitHub repository. [Online]. Available: https://github.com/raultron/ardrone_velocity.git [43: Parrot, Inc.] Parrot, Inc. PARROT AR.DRONE 2.0 ELITE EDITION. [Online]. Available: https://www.parrot.com/global/drones/parrot-ardrone-20-elite-edition | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72125 | - |
| dc.description.abstract | 本篇論文為無人飛行器的自動探索提出了一個完整的系統架構。在此架構下，五個平行運作的程序各自負責不同的功能。首先，一個獨立運行的位置控制器持續地向飛行器傳遞控制訊號。這使得飛行器的位置控制不會受到中斷，即使其他的程序正在等待各自尚未完成的運算。接著，Large Scale Direct SLAM (LSD-SLAM) 程序負責飛行器的自體定位以及半稠密的影像深度估測，而該半稠密深度經蒐集後，由Octomap 程序建立一個三圍的佔據圖(occupancy map)。利用立體空間中的深度點資訊，本系統中的導航程序便能夠處進行飛行器導航與環境探索。幾乎所有單眼影像系統，如LSD-SLAM，都需要進行尺度復原，而本系統架構中的尺度估測程序，可以在一個超聲波距離感測器的幫助下，估測出單眼影像系統的尺度。有了一個估測的尺度後，LSD-SLAM提供的自體定位便能用以進行無人飛行器導航，並且根據所建立的三圍佔據圖達到無碰撞飛行。本論文提供了在模擬環境與實際情況下的無人飛行器位置控制器，並且通過實驗進行測試。本篇論文也提出了無人飛行器的自動環境探索策略。在探索的每一步中，目前可飛行區域的所有邊界點將會被當作是下一個探索點的候選點。對於每一個候選點，與之對應的預期資訊增加量與預期的可追蹤性會被個別計算，並且從中選出最適合的候選點，做為下一個探索點。如此，無人飛行器便能飛往能夠提供最多新資訊的位置，並且能夠持續進行自體定位。最後，通過模擬實驗以及實際實驗，本篇論文對所提出的系統架構以及方法進行了測試與驗證。 | zh_TW |
| dc.description.abstract | In this thesis, a system structure for Unmanned Aerial Vehicle (UAV) quadrotor navigation and exploration is proposed. The system is composed of five nodes running in parallel, each responsible for different tasks. First of all, a pose controller continuously sends control commands to the quadrotor. This enables the quadrotor to continue in pose controlling even when other nodes are waiting for their computations to complete.
The Large Scale Direct SLAM (LSD-SLAM) provides self-localization of the quadrotor and semi-dense depth map estimation. The collected depth maps are then integrated into a three-dimensional occupancy map with the Octomap, and the occupancy information of the currently built map is utilized by the Navigation node, dealing with the navigation of the quadrotor and the exploration of the environment. For the scale recovery of monocular vision-based systems, such as the LSD-SLAM system, the Scale Estimation node provides an estimate of the scale with the aid of an ultrasound sensor. Given the estimated scale, the quadrotor can then be navigated with the re-scaled pose provided by the LSD-SLAM system. The pose controller for both the simulated quadrotor and the real-world quadrotor are designed and verified. Also with the estimated scale, the proposed system avoids collision of the quadrotor body with any obstacle, allowing the quadrotor to only approach to those areas that are free of collision. An exploration strategy is also proposed in this thesis, which is essentially a frontier-based Next-Best-View (NBV) exploration strategy. The next point to approach to during each step of exploration is selected by taking the extracted frontier points as NBV candidates. The expected visibility-gain as well as the expected trackability are calculated for each NBV candidate and the most qualified among all is selected, moving towards the highest information gain in the meanwhile ensuring the trackability while moving. Experiments in both simulation and the real world are provided to verify the proposed system and the proposed exploration strategy. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T06:24:36Z (GMT). No. of bitstreams: 1 ntu-107-R05921016-1.pdf: 10435135 bytes, checksum: 192925efa8d37f96832d306ca900dad7 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 致謝 i
摘要 iii ABSTRACT v CONTENTS viii LIST OF FIGURES x LIST OF TABLES xiv Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Formulation 2 1.3 Contributions 4 1.4 Organization of the Thesis 5 Chapter 2 Background and Literature Survey 6 2.1 Simultaneous Localization and Mapping (SLAM) 6 2.2 Visual SLAM 8 2.3 Active SLAM 10 Chapter 3 Related Algorithms 11 3.1 Pinhole Camera Model 11 3.2 Large Scale Direct SLAM (LSD-SLAM) 14 3.3 Octomap 16 3.4 Dijkstra’s Algorithm and Min-Heap 18 Chapter 4 System Overview 21 4.1 Preliminaries 21 4.2 Coordinate Frames 23 4.2.1 The LSD-SLAM Coordinate System 23 4.2.2 The Octomap Coordinate System 26 4.3 System Structure 29 4.4 Controller Design 36 4.4.1 Controller for Simulations 37 4.4.2 Controller for Real-World Experiments 39 Chapter 5 Scale Estimation for Monocular SLAM 42 5.1 Method Outline 44 5.2 Mean of Ratio Method 49 5.3 Least Squares Method 50 5.4 Re-initialize with an IMU Sensor 51 Chapter 6 Autonomous Exploration and Navigation 55 6.1 Occupancy Map Construction with LSD-SLAM and Octomap 55 6.2 Collision-Free Quadrotor Navigation 64 6.3 Autonomous Environment Exploration 67 6.3.1 Frontier-Based Next-Best-View Exploration 67 6.3.2 Next-Best-View Candidate Evaluation 73 6.3.3 Complete Exploration Strategy 81 Chapter 7 Experimental Results and Analysis 85 7.1 Hardware and Software Platforms 85 7.1.1 Hardware Platform 85 7.1.2 Software Platform 87 7.2 Accuracy of Scale Estimation 90 7.3 Quadrotor Navigation 107 7.4 Autonomous Exploration 117 7.4.1 Hexagonal Room 118 7.4.2 Branched Corridor 125 7.4.3 Branched Corridor with an Unobservable Pillar 141 7.5 Real-World Experiments 146 7.6 Summary 159 7.6.1 Scale Estimation 159 7.6.2 Quadrotor Navigation 163 7.6.3 Autonomous Exploration 164 Chapter 8 Conclusions and Future Works 177 8.1 Conclusions 177 8.2 Future Works 178 References 181 | |
| dc.language.iso | en | |
| dc.title | 基於單眼視覺之無人飛行器自動環境探索與可行駛區域地圖之建立 | zh_TW |
| dc.title | Monocular Vision-Based Unmanned Aerial Vehicle Autonomous Exploration and Navigation with Map Construction Including Flyable Regions | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 簡忠漢,李後燦,黃正民 | |
| dc.subject.keyword | 自動探索,自動導航,單眼視覺同步定位與地圖建構,即時系統,路徑規劃,機器人視覺,飛行器控制, | zh_TW |
| dc.subject.keyword | autonomous exploration,autonomous navigation,monocular SLAM system,Real-time systems,path planning,robot vision,aerospace control, | en |
| dc.relation.page | 185 | |
| dc.identifier.doi | 10.6342/NTU201803911 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-08-17 | |
| 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 |
| 顯示於系所單位： | 電機工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-107-1.pdf 目前未授權公開取用 | 10.19 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。