臺灣博碩士論文加值系統

隨著無人飛行載具的蓬勃發展，人們利用無人機進行拍攝、農藥噴灑、監視、救災等任務的執行，以上應用皆需對無人機飛行時的覆蓋路徑進行規劃設計，才可有效率達成目的。目前無人機大都於任務結束時，才進行搜尋資料的卸載讀取，為避免無人機突然發生墜機、電池沒電等不可預測之情況，致最終無法獲取搜尋資料。本文提出無人機群具 D2D 通訊效能之搜索路徑規劃，利用裝置與裝置間(Device to Device, D2D)通訊技術，在設計路徑點時考量最遠傳輸距離，讓無人機群具有「即時通訊」的功能，使其於任務過程中可即時將資料傳回基地台。本研究利用多架無人機在平坦、無障礙物的環境下同時搜索，以提高搜索效率。本文也利用目標搜索區為正六邊形之邊長等特性去規畫路徑點，讓無人機群在有相同移動次數下，其移動總距離相等。本研究結果呈現可即時資料傳回基地台之成功率為1.89%~100%，此數據與最遠傳輸距離大小相關。另外在覆蓋搜索方面，對目標區的覆蓋率為83.5%~91%間，對無人機飛行路徑之重複率為12.10%~13.33%，以上兩種數據皆與路徑點設計相關。

Along with the booming development of the unmanned aerial vehicles, people use drones for missions such as photography, pesticide spraying, surveillance, and disaster relief, the above applications all need to plan and design the coverage path of the UAV in order to achieve the goal efficiently. Currently, most UAVs only unload and read the search data at the end of the mission. In order to avoid unpredictable situations such as the sudden crash of the UAV and the loss of battery power, the search data cannot be obtained in the end.This paper proposes a search path planning for UAVs with D2D communication performance. Using Device to Device (D2D) communication technology, the longest transmission distance is considered when designing path points, so that UAVs can have "instant communication". The function enables it to transmit data back to the base station in real time during the mission.In this study, multiple UAVs are used to search simultaneously in a flat, obstacle-free environment to improve search efficiency. This paper also uses the feature that the target search area is a regular hexagon with equidistant side lengths to plan path points, so that the total moving distance of the UAVs is equal when the number of movements is the same.The results of this study show that the success rate of transmitting data back to the base station in real time is 1.89%~100%, and this data is related to the maximum transmission
distance. In addition, in terms of coverage search, the coverage rate of the target area is between 83.5% and 91%, and the repetition rate of the flight path of the UAV is 12.10% to 13.33%. The above two data are related to the way point design.

摘要 .........................................................i
Abstract ...................................................ii
誌謝 ...........................................................iv
目錄 ............................................................v
表目錄 .........................................................viii
圖目錄 ............................................................x
第一章 緒論 ....................................................1
1.1 前言 ....................................................1
1.2 研究動機與目的 ............................................2
1.3 章節大綱 ....................................................3
第二章 文獻回顧 ....................................................4
第三章 覆蓋式路徑規劃設計 ...................................17
3.1 背景知識介紹 ...................................................17
3.1.1 覆蓋路徑規劃分類 ...........................................17
3.1.2 無人機數量 ...................................................19
3.1.3 裝置對裝置(Device to Device,D2D)通訊技術 ...................20
3.2 架構介紹 ...................................................21
3.2.1 目標區網格劃分 ...........................................21
3.2.2 路徑點走法與計算 ...........................................26
3.2.3 經緯度轉換 ...................................................46
3.3 機載相機相關介紹 ...........................................48
3.3.1 鏡頭角度 ...................................................48
3.3.2 焦距與畫幅 ...................................................49
3.3.3 拍攝範圍 ...................................................50
3.3.4 覆蓋區域 ...................................................52
第四章 實驗結果與分析 ...........................................56
4.1 模擬軟體 ...................................................56
4.1.1 MATLAB ...................................................56
4.1.2 Visual Studio ...........................................57
4.2 D2D成功率分析與比較 ...........................................58
4.2.1 D2D成功率 ...................................................58
4.2.2 D2D數據分析 ...........................................59
4.3 覆蓋率與路徑重複率分析與比較 ...................................63
4.3.1 覆蓋率、路徑重複率 ...........................................63
4.3.2 覆蓋率、路徑重複率數據分析 ...................................63
4.4 拍攝面積分析與比較 ...........................................71
4.4.1 相關介紹與計算 ...........................................71
4.4.2 拍攝面積數據分析 ...........................................74
第五章 結論 ...................................................79
5.1 結論 ...................................................79
5.2 未來展望 ...................................................80
參考文獻 ...........................................................81
Extended Abstract ...........................................83

[1] Y. Guo, C. Liu and M. Coombes, "Spraying Coverage Path Planning for Agriculture Unmanned Aerial Vehicles," 2021 26th International Conference on Automation and Computing (ICAC), Portsmouth, United Kingdom, 2021, pp. 1-6, doi: 10.23919/ICAC50006.2021.9594271.
[2] N. Wu, W. Cowles and A. Kudelin, "Addressing Greenhouse’s Lack of Natural Pollinators - A UAV-Based Artificial Pollination System," 2021 17th International Conference on Distributed Computing in Sensor Systems (DCOSS), Pafos, Cyprus, 2021, pp. 314-318, doi: 10.1109/DCOSS52077.2021.00058.
[3] C. Di Franco and G. Buttazzo, "Energy-Aware Coverage Path Planning of UAVs," 2015 IEEE International Conference on Autonomous Robot Systems and Competitions, Vila Real, Portugal, 2015, pp. 111-117, doi: 10.1109/ICARSC.2015.17.
[4] Z. Luo et al., "A UAV Path Planning Algorithm Based on an Improved D* Lite Algorithm for Forest Firefighting," 2020 Chinese Automation Congress (CAC), Shanghai, China, 2020, pp. 4233-4237, doi: 10.1109/CAC51589.2020.9327111.
[5] G. Sanna, S. Godio and G. Guglieri, "Neural Network Based Algorithm for Multi-UAV Coverage Path Planning," 2021 International Conference on Unmanned Aircraft Systems (ICUAS), Athens, Greece, 2021, pp. 1210-1217, doi: 10.1109/ICUAS51884.2021.9476864.
[6] S. Zheng and X. Li, "An Adaptive Multi-UAV Area Coverage Method," 2022 International Conference on Advanced Robotics and Mechatronics (ICARM), Guilin, China, 2022, pp. 882-885, doi: 10.1109/ICARM54641.2022.9959275.
[7] K. Vinh, S. Gebreyohannes and A. Karimoddini, "An Area-Decomposition Based Approach for Cooperative Tasking and Coordination of UAVs in a Search and Coverage Mission," 2019 IEEE Aerospace Conference, Big Sky, MT, USA, 2019, pp. 1-8, doi: 10.1109/AERO.2019.8741565.
[8] A. Gupta and R. K. Jha, "A Survey of 5G Network: Architecture and Emerging Technologies," in IEEE Access, vol. 3, pp. 1206-1232, 2015, doi: 10.1109/ACCESS.2015.2461602.
[9] N. Zhao et al., "UAV-Assisted Emergency Networks in Disasters," in IEEE Wireless Communications, vol. 26, no. 1, pp. 45-51, February 2019, doi: 10.1109/MWC.2018.1800160.
[10] L. Shi and S. Xu, "UAV Path Planning With QoS Constraint in Device-to-Device 5G Networks Using Particle Swarm Optimization," in IEEE Access, vol. 8, pp. 137884-137896, 2020, doi: 10.1109/ACCESS.2020.3010281.