建立在ArduPilot自動駕駛器之慣性導航系統
開發與驗證

近年來無人載具性質的研究主題受到廣大關注，一般民用定位系統皆以GPS為主，GPS雖然有著省時、高精度定位的表現，但其容易受到地形遮蔽以及大樓反射造成影響GPS之定位表現，為了能使GPS資訊在受到影響的狀況下得到輔助定位，需要一套系統能在此狀況下對載具進行即時之輔助定位。基於上述動機，本研究於ArduPilot無人載具控制系統中架構了一套結合卡爾曼濾波器之慣性導航系統(Inertial Navigation System, INS)。 INS之感測元件是由加速計與電子羅盤組成，將加速計取得之加速度值，利用基礎運動原理將加速度值進行兩次積分後，可得載具位移量；由電子羅盤取得載具之航向方位，利用兩者資訊整合即可幫助載具定位及導航。但慣性導航系統還無法做自動駕駛，因此本論文建立INS慣性導航自動駕駛系統，為驗證本研究建構之INS可靠度，更模擬了GPS在隧道裡斷訊的情況以實驗驗證本研究開發之系統確實可行。

關鍵字

ArduPilot ；慣性導航系統；自走車；自動駕駛

並列摘要

The Global Positioning System(GPS) is now commonly used for vehicle’s navigation, but GPS signal would possibly be affected by environment such as mountains, trees, high buildings or even tunnel. When GPS signal lost, there is a need that autonomous vehicle have to has a backup system for navigation. This research is aiming to create a Inertial Navigation System(INS) combine with Kalman Filter for navigation on unmanned vehicle’s autopilot system. Sensors of INS include accelerometer and e-compass. Regarding basic Newton’s law of motion, vehicle’s speed and displacement (position) can be obtained by the integral of acceleration. Heading angle measured from e-compass indicates where the vehicle moving toward. The combination of displacement and heading gives the very basic information to fill the vacancy of GPS signal lost. Based on previous INS positioning principle, in the end of this research, a computer code was written into the Ardupilot controller to validate the effectiveness of INS positioning during the period of GPS signal lost. Tests shows our INS method can successfully take the place of GPS positioning up to 60 seconds as a result.

並列關鍵字

Inertial Navigation System ； ArduPilot ； Autopilot

參考文獻

[8]李育慈，”建立在ArduPilot自動駕駛器之慣性導航系統開發”，碩士論文，國立虎尾科機大學自動化工程系，2014

[7] 張耕魁，”利用卡曼濾波器整合全球定位系統及慣性導航系統”，碩士論文，國立台北科技大學機電整合研究所，2008

[16] Greg Welch and Gary Bishop，” An Introduction to the Kalman Filter”，2006

參考文獻

Google Scholar

[1] Ardupilot，http://dev.ardupilot.com/。

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建立在ArduPilot自動駕駛器之慣性導航系統開發與驗證

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