基於空中無線充電之多架無人機合作資料 蒐集系統設計;Design of a Multi-UAV Data Collections System with Considerations of In-Flight Wireless Power Transfer

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題名:	基於空中無線充電之多架無人機合作資料蒐集系統設計;Design of a Multi-UAV Data Collections System with Considerations of In-Flight Wireless Power Transfer
作者:	魚見直矢;Naoya, Uomi
貢獻者:	通訊工程學系
關鍵詞:	One keyword per line;無人機;旅行商人問題;基因演算法;One keyword per line
日期:	2025-05-21
上傳時間:	2025-10-17 12:17:09 (UTC+8)
出版者:	國立中央大學
摘要:	近年來，無人機（Unmanned Aerial Vehicles, UAVs）技術有顯著進展。由於其具備高度靈活性與成本效益，無人機在建構通訊網路方面受到廣泛關注。無人機輔助的通訊網路可應用於精準農業、環境監測與災害應變等多種場景。儘管具有多項優勢與廣泛應用潛力，無人機仍面臨電力受限的關鍵問題。其電池續航力有限，使無人機長時間飛行是不可行的，導致無法完整地蒐集目標區域的資料。此外，飛行距離越長，電力消耗亦越高，因此設計節能的飛行軌跡至關重要。本論文設計一種由多架無人機合作之通訊網路，以延長網路整體運作時間。我們引入兩類無人機：任務型無人機與輔助型無人機。任務型無人機負責在指定區域內蒐集資料，數量眾多；輔助型無人機則運用無線充電技術，為任務型無人機進行電力補給。透過此架構，可望有效延長通訊網路的運作時間。任務型無人機透過分群方式分派至特定區域，並依預設路徑進行資料蒐集；輔助型無人機則按照預定路線依序對任務型無人機進行充電。為確保充電時間充足，輔助型無人機的飛行路線規劃至為關鍵。為此，我們採用基因演算法（Genetic Algorithm, GA）決定其路徑；而任務型無人機的路徑規劃是解旅行商人問題（Traveling Salesman Problem, TSP），我們納入則以模擬退火演算法（Simulated Annealing, SA）分析此問題，實現在有限的電力下，無人機搜集最多的資料。同時，我們亦比較數種不同。的規劃輔助型無人機飛行軌跡之演算法。透過模擬實驗，我們驗證了本研究所提方法的效能與可行性。;The development of unmanned aerial vehicles (UAVs) has advanced significantly in recent years. Due to their flexibility and cost efficiency, UAVs are gathering considerable attention for their potential to construct communication networks. UAV-assisted communication networks can contribute to numerous activities, including precision agriculture, environmental surveillance, and disaster response. Despite these advantages and the wide range of applicable situations, UAVs have a critical issue of energy limitation. The battery life of UAVs is limited, making prolonged flight times unfeasible. This limitation results in challenges such as the inability of UAVs to collect comprehensive data across the designated area. Additionally, the longer the distance UAVs must travel, the greater their energy consumption. Consequently, it is essential to design efficient UAV trajectories to minimize energy consumption. In this thesis, we design a communication network in which multiple UAVs cooperate to extend the network’s lifespan. We introduce two types of UAVs: mission UAVs and a supply UAV. The mission UAVs are numerous and responsible for collecting data within a designated area, while the supply UAV provides energy to the mission UAVs with wireless charging technology. Introducing two types of UAVs can potentially extend the network lifespan. Mission UAVs are allocated to specific areas through clustering and collect data based on predetermined routes. The supply UAV follows predefined routes to charge the mission UAVs sequentially. To ensure sufficient charging time, it is crucial to define the route for the supply UAV effectively. To do so, we determine the route with the use of the GA algorithm. Furthermore, to determine the routes for the mission UAVs, we solve the Traveling Salesman Problem (TSP) using the Simulated Annealing (SA) algorithm. For comparison, we adapt several algorithms to determine the path of the supply UAV. Through simulations, we will demonstrate the effectiveness of our proposed approach.
顯示於類別:	[通訊工程研究所] 博碩士論文

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