隨著科技日新月異的進步，使近年來無人機產業蓬勃發展並逐漸應用在生活當中，例如 : 航拍、環境監測、物流運輸或是橋樑檢測等。然而，隨著無人機的應用不斷擴展，相應的飛行環境也變得更加複雜多變，因此無人機的避障系統在執行飛行任務上是未來無人機發展的關鍵技術之一。本研究將以無人機在路徑規劃模式下之避障系統研究為目標。
本研究結合了光達感測器 ( RPLidar ) 的高精度測距能力和Vector Field Histogram (VFH)的避障演算法，建立一套高效、實時且安全的四旋翼無人機避障系統。當無人機在執行飛行任務的過程中，當障礙物在行進路徑上觸發到避障條件時會啟動避障系統，此時樹莓派會透過 MAVLink 通訊協議的方式與飛行控制器進行連接，並且傳送訊號即時改變無人機的飛行姿態以及飛行模式進行無人機的迴避，最後將此避障系統套用在無人機的路徑規劃模式下，並成功完成實際飛行。
實驗部分，我們將使用無人機的路徑規劃模式設定起飛原點和降落終點，並在飛行路線上放置在不同的障礙物環境中，評估其避障性能。經過多次測試，無人機在各種複雜環境中均能夠成功避開障礙物並自主完成後續飛行任務，證明了我們系統的有效性和可靠性。

With the rapid advancement of technology, the drone industry has flourished in recent years, increasingly finding applications in daily life such as aerial photography, environmental monitoring, logistics, and bridge inspection. As drone applications expand, the flying environment becomes more complex and variable, making obstacle avoidance systems a critical aspect of future drone development. This study focuses on the research of obstacle avoidance systems for drones under path auto mode.
This research combines the high-precision ranging capabilities of RPLidar sensors with the VFH obstacle avoidance algorithm to develop an efficient, real-time, and safe quadcopter obstacle avoidance system. During flight missions, when an obstacle triggers the avoidance system, the Raspberry Pi connects to the flight controller via the MAVLink communication protocol, transmitting signals to instantly change the drone's flight attitude and mode for evasion. The system is then implemented in the drone’s path auto mode, successfully completing actual flights.
In the experimental part, we set the takeoff origin and landing destination in the drone's path planning mode and placed various obstacles along the flight route to assess its obstacle avoidance performance. After multiple tests, the drone successfully avoided obstacles in various complex environments and autonomously completed subsequent flight tasks, demonstrating the effectiveness and reliability of our system.

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[17] 激光三角測距原理, https://www.slamtec.com/cn/News/Detail/190
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