在大規模災害發生的環境下，地形與時間的限制是目前搜救團隊所面臨的最大問題，因此也越來越多案例使用無人機來對災害環境進行勘查，情報的蒐集以及定位受災戶位置。

本研究利用了當今社會手機普及率的特性，由無人機搜尋手機無線訊號位置，也因無線訊號的特性，結合RSSI與Log-Distance Model，來預估當前無人機位置與訊號源間的距離。因此比起生命探測儀，更能從較大範圍的距離下開始搜查任務。此外，我們也設計了一種動態路徑規劃(Dynamic Path Planning)演算法，能夠根據現場無線訊號源的變化，使得無人機可以更快速接近受災戶，並定位出其位置。研究致力的方向為縮小搜尋時間與定位誤差，蒐集現場環境情報來提供給搜救團隊參考。而最後我們實驗的結果也顯示了使用了動態規劃演算法，比起一般的固定路徑規劃，更快速且精準的定位出受災戶位置。

In a large disaster area, search and rescue (SAR) operations can face great challenges due unfriendly, inaccessible, or even danger terrains for rescue teams. Unmanned Aerial Vehicle (UAV) is a good option to assist operations support searching victims and collecting information in the disaster area. In this research, a UAV is used to detect wireless signal from smart phones to locate possible victims. Using Received Signal Strength Indicator (RSSI) and path loss model (i.e., Log-Distance model), the distance between the UAV and the wireless signal source (e.g., smart phone) can be estimated. With the estimated distance, we propose a Dynamic Path Planning (DPP) algorithm for UAV to assist SAR operations. It allows UAV dynamically adjust its search path based on the estimated location of the victim. Our approach is able to reduce the search time and minimize the location error. We show in our experiment studies DPP provides a more accurate location estimation with less time compare with other fixed-path searching (i.e., half-circle and two-leaf) algorithms.

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