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    题名: 無人機基於智慧空間模型導航應用
    UAVs Intelligent Space Modeling and Navigation Applications
    作者: 馬智煒
    Ma, Chih-Wei
    贡献者: 劉吉軒
    Liu, Jyi-Shane
    馬智煒
    Ma, Chih-Wei
    关键词: 無人機
    空間模型
    自主導航
    空間資訊計算應用
    日期: 2023
    上传时间: 2023-03-09 18:36:37 (UTC+8)
    摘要: 近年來無人機的發展愈發成熟,從早期皆需要人為遠端操控到現在已逐漸在發展自主無人機,目的是為了取代許多高危險的工作,如救災、高壓電塔檢查、地面動態情境偵查。由此可知無人機應用已普及在我們的周遭。目前無人機的應用有許多,但對於自主無人機來說感測周遭的環境狀況往往都仰賴感測器的即時資訊,有些事前就已知的遠處資訊或是之前有探訪過的資訊無人機卻無從獲得。無人機需要再次抵達該區域才能夠使用感測器進行環境偵測獲得資訊,無人機難以達到較好的效率。因此本研究希望能設計一套空間模型,該空間模型將會紀錄無人機所需的任務與定位資訊。讓無人機可以不用移動就直接調用遠處的資訊,並以此資訊進行決策判斷。如此無人機將可以減少不必要的飛行時間,進而增加無人機任務效率。
    參考文獻: [1] International Civil Aviation Organization(ICAO). Global Air Traffic Management Operational Concept;ICAO,2005.
    [2] Y. Lin et al., "Image Processing Techniques for UAV Vision-Based River Floating Contaminant Detection," 2019 Chinese Automation Congress (CAC), 2019, pp. 89-94.
    [3] X. Yang, L. Tang, H. Wang and X. He, "Early Detection of Forest Fire Based on Unmaned Aerial Vehicle Platform," 2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP), 2019, pp. 1-4.
    [4] M. Elloumi, R. Dhaou, B. Escrig, H. Idoudi and L. A. Saidane, "Monitoring road traffic with a UAV-based system," 2018 IEEE Wireless Communications and Networking Conference (WCNC), 2018, pp. 1-6.
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    [15] J. Branu et al. "A Comparison of A* and RRT* Algorithms with Dynamic and Real Time Constraint Scenarios for Mobile Robots." SIMULTECH, 2019, pp. 398-405
    [16] C. Zammit et al. "Comparison between A* and RRT Algorithms for UAV Path Planning,", Proceedings of the 2018 AIAA Guidance, Navigation, and Control Conference, 2018.
    [17] W. C. Wright, B. E. Wilkinson, W. P. Cropper and C. E. Oxendine, "Classifying Terrestrial Based Forest Photography with Geographic Information Systems to Model Signal Loss," IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018, pp. 6420-6423.
    [18] A. G. Dubrovin, et al., "Analysis of noise immunity of GLONASS and GPS positioning receivers," IOP Conference Series: Materials Science and Engineering, 2020, vol. 734, no. 1.
    [19] A. Hameed and H. A. Ahmed, "Survey on indoor positioning applications based on different technologies," 2018 12th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS), 2018, pp. 1-5, pp.
    [20] X. Xin, J. Jiang, and Y. Zou. "A review of visual-based localization," Proceedings of the 2019 International Conference on Robotics, Intelligent Control and Artificial Intelligence, 2019.
    [21] N. Piasco et al., "A survey on visual-based localization: On the benefit of heterogeneous data," Pattern Recognition, 2018,vol.74, pp. 90-109.
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    [25] J. Engel, T. Schöps, and D. Cremers, "LSD-SLAM: Large-scale direct monocular SLAM." European conference on computer vision, 2014, pp. 834-849.
    [26] 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, 2015, vol. 31, no. 5, pp. 1147-1163.
    [27] A. Gautam, S. Mahangade, V. I. Gupta, R. Madan and K. Arya, "An experimental comparison of visual SLAM systems," 2021 International Symposium of Asian Control Association on Intelligent Robotics and Industrial Automation (IRIA), 2021, pp. 13-18.
    [28] M. Filipenko and I. Afanasyev, "Comparison of Various SLAM Systems for Mobile Robot in an Indoor Environment," 2018 International Conference on Intelligent Systems (IS), 2018, pp. 400-407.
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    [30] D. Malyuta, C. Brommer, D. Hentzen, T. Stastny, R. Siegwart, and R. Brockers, “Long-duration fully autonomous operation of rotorcraft unmanned aerial systems for remote-sensing data acquisition,” Journal of Field Robotics, 2020, pp. 137-157.
    [31] C. Brommer, D. Malyuta, D. Hentzen and R. Brockers, "Long-Duration Autonomy for Small Rotorcraft UAS Including Recharging," 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, pp. 7252-7258.
    [32] J. Wang and E. Olson, "AprilTag 2: Efficient and robust fiducial detection," 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016, pp. 4193-4198.
    [33] R. Ranftl, K. Lasinger, D. Hafner, K. Schindler and V. Koltun, "Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer," in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, vol. 44, no. 3, pp. 1623-1637.
    描述: 碩士
    國立政治大學
    資訊科學系
    108753129
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0108753129
    数据类型: thesis
    显示于类别:[資訊科學系] 學位論文

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