本論文主旨為研究無人車之位置追蹤與地圖建置。里程計廣泛使用於追蹤無人車位置，但它存在累加誤差的問題，在建置環境資訊時，若不能即時修正，將導致地圖存在偏移量。本研究採用感測器融合方法於無人車地圖建置，以導航系統中之慣性感測模組估測朝向角取代里程計之估測朝向角，並使用迭代最近點演算法，將當前掃描資料與全域地圖做匹配，並將匹配結果用於修正里程計誤差，同時將新的量測資訊更新到全域地圖中。實驗過程中搭配V-REP機器人模擬軟體先行檢驗方法之可用性，以便在實際測試前排除硬體問題，有效測試位置追蹤與觀察地圖建立狀態，以減少實際測試時，花在修正軟體錯誤所耗費的時間。

The main theme of this thesis is position tracking and map establishment of Autonomous Guided Vehicle (AGV). Odometry is widely applied to track AGV position but it exists cumulative errors. Map offsets is presence if cumulative errors not corrected immediately. To solve this problem, multi-sensors are fused in this proposal. Firstly, an inertia measurement unit is applied for providing the odometry with a correct driving direction. Moreover, the iterative closest point algorithm is applied to match the scanned information of Laser Range Finder over time. Meanwhile, the results of scanning registration are used to eliminate odometry errors and updated the new information into global map. In experiment process, a simulation software called Virtual Robot Experiment Platform is firstly used to simulate the proposed algorithm before real experiment. It can make sure the hardware system can work well which will reduce the time on algorithm validation and software fault debugging time of practical testing.

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