慣性和地磁感測陣列的無人機導航

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姓名

楊世鴻(Shih-Hong Yang) 查詢紙本館藏

畢業系所

資訊工程學系在職專班

論文名稱

慣性和地磁感測陣列的無人機導航
(Unmanned Aerial Vehicle Navigation with Inertial and Geomagnetic Sensor Array)

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至系統瀏覽論文 (2029-7-20以後開放)

摘要(中)

無人機在無GNSS環境下，通常使用電腦視覺方法或是慣性導航。然而電腦視覺方法容易被環境光源影響。而現行的慣性導航有雜訊與誤差的問題，精度較高的慣性感測器有著成本高且體積大的缺點。因此我們採用MIAT系統設計方法論設計了高精度且低成本的無人機導航系統，它是基於一個慣性與地磁感測陣列及一個微控制器，透過校正演算法、卡爾曼濾波器、深度學習模型來降低導航的誤差。實驗結果顯示，我們的方法比起單一慣性感測器，在水平方向的矩形路徑實驗中平均定位誤差從11.3公尺降至1.65公尺，以及水平方向的圓形路徑實驗中平均定位誤差從7.11公尺減少至2.87公尺。此外在無人機實驗中，經過90秒的飛行後平均定位誤差為1.65公尺，證明我們的無人機導航系統的優秀性能。

摘要(英)

In environments without GNSS, drones typically rely on either computer vision techniques or inertial navigation systems. However, computer vision can be significantly affected by environmental lighting, while current inertial navigation systems suffer from noise and inaccuracies. Higher precision sensors are also costly and bulky. To address these challenges, we designed a high-accuracy, low-cost drone navigation system using the MIAT system design methodology. Our system is based on an array of inertial and geomagnetic sensors, along with a microcontroller. It employs a calibration algorithm, filters, and a deep learning model to reduce navigational errors. Experimental results demonstrate that our method significantly reduces the average position error in a horizontal rectangular path experiment from 11.3 meters to 1.65 meters, and in a horizontal circular path experiment from 7.11 meters to 2.87 meters. Additionally, during drone experiments, after 90 seconds of flight, the average position error was 1.65 meters, proving the superior performance of our drone navigation system.

關鍵字(中)

★ 無人機
★ 慣性導航
★ 遞迴神經網路

關鍵字(英)

★ UAV
★ Inertial navigation system
★ RNN

論文目次

中文摘要 i
Abstract ii
誌謝 iii
目錄 iv
圖目錄 vii
表目錄 x
第一章緒論 1
1-1研究背景 1
1-2 研究目的 3
1-3論文架構 3
第二章技術回顧 4
2-1慣性導航系統 4
2-2 卡爾曼濾波器 5
2-3 自編碼器 8
2-4 遞迴神經網路 9
2-5 MIAT系統設計方法論 12
2-5-1 IDEF0 12
2-5-2 GRAFCET 14
2-5-3 高階合成 16
第三章慣性和地磁感測陣列的無人機導航系統架構設計 17
3-1 無人機飛行系統 17
3-2 感測器模組 18
3-3 資料處理模組 19
3-3-1 校正模組 20
3-3-2 深度學習模型 25
3-4 導航模組 27
3-4 導航系統設計 29
3-5-1 感測器模組設計 30
3-5-2 感測器陣列初始化系統設計 32
3-5-3 資料處理模組設計 33
3-5-4 校正模組設計 34
3-5-5 導航模組設計 36
3-6 軟體合成及驗證 37
第四章系統整合驗證與實驗 39
4-1 實驗平台與工具 39
4-1-1 微控制器平台 39
4-1-2 九軸感測器 41
4-1-3 I2C多工器 42
4-1-4 無人機 42
4-1-5 實驗環境 43
4-2 資料收集 45
4-2-1 感測器資料收集 45
4-2-2 位移、面向資料收集 47
4-3 感測資料校正實驗 49
4-4 模型訓練 56
4-5 評估指標 57
4-6 水平方向移動實驗 58
4-6-1矩形路徑的導航實驗 59
4-6-2 圓形路徑的導航實驗 61
4-7 無人機導航實驗 63
第五章結論與未來展望 66
5-1 結論 66
5-2 未來展望 67
參考文獻 68

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指導教授

陳慶瀚(Ching-Han Chen)

審核日期

2024-7-23

推文