政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/141186

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/141186

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | 全文笔数/总笔数 : 113648/144635 (79%)
造访人次 : 51632062 在线人数 : 558

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

搜寻范围

查询小技巧：

您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果

若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据

进阶搜寻

主页 ‧ 登入 ‧ 上传 ‧ 说明 ‧ 关于政大典藏 ‧ 管理

到手机版

政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 > Item 140.119/141186

请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/141186

题名:	結合多模控制機制之水下無人載具自主導航系統 Autonomous Navigation for Unmanned Underwater Vehicles Using Multimodal Control Strategies
作者:	蔡孟哲 Tsai, Meng-Tse
贡献者:	廖文宏 Liao, Wen-Hung 蔡孟哲 Tsai, Meng-Tse
关键词:	水下無人載具自主水下導航 AprilTag 線段偵測光流法 UUV autonomous underwater navigation AprilTag line detection optical flow
日期:	2022
上传时间:	2022-08-01 18:13:59 (UTC+8)
摘要:	隨著時間的推移，自動化工程越來越被重視；透過無人載具結合自動化控制技術，可有效降低人力成本並節省大量時間，加上近年來由於軟硬體技術的進步，純視覺導航系統變得有開發價值。與陸上、空中環境進行導航任務不同，水下進行導航會面臨到下面幾個問題：包含水下色差、濁度、懸浮物導致影像品質不佳，且不同水域在水色上有相當的差異；由於水下無法使用GPS，所以較難進行路徑分析；另外因海水色差、折射的關係，所以較難透過第三方視角來進行觀測；最後水下水流多變，需即時調整無人載具之位姿才可完成導航任務，所以發展可靠、具有定位功能的導航系統有其必要性。本論文主要的貢獻有三，首先本論文提出一款階層式多模架構的導航演算法，以因應不同水質環境中之導航任務，此階層式多模架構是由AprilTag、線段偵測、光流法所組成；其次本論文亦透過無人載具之多鏡頭協作來增強系統之穩定性，使其可在水下順利完成導航任務；最後、透過定義「引導以及控制規則」限制並調整無人載具之移動，使其可在水流的影響下保持穩定的導航。為驗證本系統之可靠性以及穩定性，本論文透過自行搭建模擬環境進行單元測試，並於多種仿真的水下場景進行整合測試，驗證結果顯示本架構可於各種場景順利、穩定的運行，最後也針對實際水下場景進行驗證，確立了本系統在現實中運行的可能性。 Autonomous navigation has been actively investigated and developed in recent years. By empowering unmanned vehicles with automatic controls, labor cost can be reduced effectively and a lot of time can be saved. In particular, vision-based navigation system has been the focus of many researches due to the advances in sensor technology. Unlike the ground and aerial navigation tasks, underwater vehicles usually face the following problems: underwater chromatic aberration, turbidity, and suspended objects that cause poor image quality. Since GPS cannot be used underwater, localization and path analysis are more challenging. Additionally, observing through third-person view is also difficult because of refraction. Finally, as waterflows are ever-changing, real-time control is needed. To sum up, the need to develop a reliable navigation system with positioning function is evident. There are three main contributions in this thesis. First, we design a hierarchical multimodal control algorithm to perform navigation tasks in different underwater environments. The multimodal system is composed of AprilTag, line detection, and optical flow. Second, this thesis also enhances the stability of the system through the collaboration of unmanned vehicle’s multi-cameras. Third, by devising "guidance and control rules" to limit and adjust the movement of the unmanned vehicle, we can maintain more stable navigation. To verify the reliability and stability of the system, this research conducts a number of unit tests in simulated environments. Integration tests on various simulated underwater scenes are then performed. Experimental results clearly indicate that the proposed framework can run smoothly and stably in various scenes. At last, we conducted multiple tests in real underwater environments to validate the feasibility of the proposed control schemes in real world.
參考文獻:	[1] Mur-Artal, R., Montiel, J. M. M., & Tardos, J. D. (2015). ORB-SLAM: a versatile and accurate monocular SLAM system. IEEE transactions on robotics, 31(5), 1147-1163. [2] Engel, J., Koltun, V., & Cremers, D. (2017). Direct sparse odometry. IEEE transactions on pattern analysis and machine intelligence, 40(3), 611-625. [3] Olson, E. (2011, May). AprilTag: A robust and flexible visual fiducial system. In 2011 IEEE international conference on robotics and automation (pp. 3400-3407). IEEE. [4] Ang, K. H., Chong, G., & Li, Y. (2005). PID control system analysis, design, and technology. IEEE transactions on control systems technology, 13(4), 559-576. [5] Human Interface Technology Lab, ARToolKit, http://www.hitl.washington.edu/artoolkit/, Last visited on Jan 2022 [6] Fiala, M. (2005, June). ARTag, a fiducial marker system using digital techniques. In 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR`05) (Vol. 2, pp. 590-596). IEEE. [7] Mohan, A., Woo, G., Hiura, S., Smithwick, Q., & Raskar, R. (2009). Bokode: imperceptible visual tags for camera based interaction from a distance. In ACM SIGGRAPH 2009 papers (pp. 1-8). [8] Rublee, E., Rabaud, V., Konolige, K., & Bradski, G. (2011, November). ORB: An efficient alternative to SIFT or SURF. In 2011 International conference on computer vision (pp. 2564-2571). Ieee. [9] Lowe, D. G. (1999, September). Object recognition from local scale-invariant features. In Proceedings of the seventh IEEE international conference on computer vision (Vol. 2, pp. 1150-1157). Ieee. [10] Lucas, B. D., & Kanade, T. (1981, April). An iterative image registration technique with an application to stereo vision. [11] Ismail, A. H., Ramli, H. R., Ahmad, M. H., & Marhaban, M. H. (2009, October). Vision-based system for line following mobile robot. In 2009 IEEE Symposium on Industrial Electronics & Applications (Vol. 2, pp. 642-645). IEEE. [12] Li, Y., Wu, X., Shin, D., Wang, W., Bai, J., He, Q., ... & Zheng, W. (2012, December). An improved line following optimization algorithm for mobile robot. In 2012 7th International Conference on Computing and Convergence Technology (ICCCT) (pp. 84-87). IEEE. [13] Hartley, R., Kamgar-Parsi, B., & Narber, C. (2018). Using roads for autonomous air vehicle guidance. IEEE Transactions on Intelligent Transportation Systems, 19(12), 3840-3849. [14] Arbelaez, P., Maire, M., Fowlkes, C., & Malik, J. (2010). Contour detection and hierarchical image segmentation. IEEE transactions on pattern analysis and machine intelligence, 33(5), 898-916. [15] Felzenszwalb, P. F., & Huttenlocher, D. P. (2004). Efficient graph-based image segmentation. International journal of computer vision, 59(2), 167-181. [16] Noshahri, H., & Kharrati, H. (2014, June). PID controller design for unmanned aerial vehicle using genetic algorithm. In 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE) (pp. 213-217). IEEE. [17] Sangyam, T., Laohapiengsak, P., Chongcharoen, W., & Nilkhamhang, I. (2010, August). Path tracking of UAV using self-tuning PID controller based on fuzzy logic. In Proceedings of SICE annual conference 2010 (pp. 1265-1269). IEEE. [18] Zhang, T., & Gao, J. X. (2010, May). Multi-sensor data fusion approach for terrain match navigation of autonomous underwater vehicles. In 2010 The 2nd International Conference on Industrial Mechatronics and Automation (Vol. 1, pp. 130-133). IEEE. [19] Hidalgo, F. (2020, October). ORBSLAM2 and Point Cloud Processing towards Autonomous Underwater Robot Navigation. In Global Oceans 2020: Singapore–US Gulf Coast (pp. 1-4). IEEE. [20] Park, J., & Kim, J. (2016, November). High-precision underwater navigation using model-referenced pose estimation with monocular vision. In 2016 IEEE/OES Autonomous Underwater Vehicles (AUV) (pp. 138-143). IEEE. [21] Panetta, K., Kezebou, L., Oludare, V., & Agaian, S. (2021). Comprehensive underwater object tracking benchmark dataset and underwater image enhancement with GAN. IEEE Journal of Oceanic Engineering. [22] Du, D., Wen, L., Zhu, P., Fan, H., Hu, Q., Ling, H., ... & Zhao, Z. (2020, August). VisDrone-CC2020: The vision meets drone crowd counting challenge results. In European Conference on Computer Vision (pp. 675-691). Springer, Cham. [23] Centelles, D., Soriano, A., Martí, J. V., Marin, R., & Sanz, P. J. (2019, June). UWSim-NET: An open-source framework for experimentation in communications for underwater robotics. In OCEANS 2019-Marseille (pp. 1-8). IEEE. [24] Manhães, M. M. M., Scherer, S. A., Voss, M., Douat, L. R., & Rauschenbach, T. (2016, September). UUV simulator: A gazebo-based package for underwater intervention and multi-robot simulation. In OCEANS 2016 MTS/IEEE Monterey (pp. 1-8). IEEE. [25] Suzuki, S. (1985). Topological structural analysis of digitized binary images by border following. Computer vision, graphics, and image processing, 30(1), 32-46. [26] THUNDER TIGER, Seadragon 8-Axis, https://www.ttrobotix.com/zh-tw/products/detail/927.html, 2019
描述:	碩士國立政治大學資訊科學系 109753112
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0109753112
数据类型:	thesis
DOI:	10.6814/NCCU202200839
显示于类别:	[資訊科學系] 學位論文

文件中的档案:

档案	描述	大小	格式	浏览次数
311201.pdf		5079Kb	Adobe PDF2	63	检视/开启

在政大典藏中所有的数据项都受到原著作权保护.

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

DSpace Software Copyright © 2002-2004 MIT & Hewlett-Packard / Enhanced by NTU Library IR team Copyright © - 回馈