臺灣博碩士論文加值系統

本論文提出一套以無人飛機為主軸，將感測器加裝於無人機上，透過行動網路傳輸控制訊號的方式取代傳統的手持遙控器，遠距離控制無人機群飛行的系統，並且透過隊形的演算法，讓無人機能更有效率且有目地的執行任務，本論文針對不同任務特性需求，實作了兩種不同的隊形演算法，而無人機群之間的溝通主要是透過Message Queuing Telemetry Transport （MQTT） protocol此一通訊機制來完成彼此訊息的交換，達到群體智能(Swarm Intelligence)的目標。另外，搭載在無人機上的感測器也會即時的將感測數值回傳，在本地端能夠以即時視覺化圖表呈現，甚至於能夠讓無人機在返航回地面後，能夠將完整的資訊取出，進行資料的2D、3D視覺化呈現。最後，本論文提出一群體智能於汙染源搜尋的演算法，讓無人機能夠更快速的搜尋出汙染來源，經模擬器驗證本論文所提出的演算法能夠較現有的無人機汙染源搜尋演算法更符合經濟效益並且能更快速的找出汙染來源。

This thesis presents a group UAV navigation system for air pollution search. The system consists of a number of unmaned aerial vehicles equipped with air pollution sensors. The communication among the drones is through the Message Queuing Telemetry Transport （MQTT） protocol. In addition, the information collected by the sensors mounted on the drones will immediately be transmitted and presented visually on the control panel. Furthermore, an improved swarm intelligence algorithm for pollution source search is proposed to allow the drones to search for multiple pollution sources more efficient. Simulation results prove that the proposed algorithm can search multiple pollution sources more efficient than PSO.

論文審定書 i
摘要 ii
Abstract iii
目錄 iv
圖目錄 vi
第一章 簡介 1
1.1、 論文概述 2
1.2、 論文貢獻 3
1.3、 論文架構 4
第二章 文獻探討 6
2.1、 群體智能（Swarm Intelligence） 6
2.2、 超視距控制 9
2.3、 無人機的發展 11
2.4、 現有無人機應用於空汙感測之方式 12
2.5、 Message Queuing Telemetry Transport （MQTT） 16
2.6、 Web Real-Time Communication (WebRTC) 17
2.7、 Gaussian Plume Model 17
第三章 研究方法 20
3.1、 超視距控制無人機 21
3.2、 無人機群飛隊形控制 22
3.2.2、 雁行飛行模式 24
3.3、 運用群體智能演算法於模擬無人機群汙染源搜尋 25
3.4、 空汙數值視覺化 30
3.5、 基於WebRTC技術實現無人機影像串流 31
第四章 實作成果與分析 33
4.1、 系統功能 34
4.1.1、 使用者控制介面 34
4.1.2、 本論文架構下MQTT測試 35
4.2、 測試與分析 35
4.2.1、 超視距無人機控制 35
4.2.2、 兩隊形測試 36
4.2.3、 群體智能演算法模擬 39
4.2.4、 視覺化資料呈現 45
第五章 結論與未來工作 49
5.1、 結論 49
5.2、 未來工作 49
參考文獻 50

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