後續研究

於實驗過程中，發現仍可從許多建圖功能方面進行改良，其中有系統 執行的速度，即時化、感測器模型等。以下將條列出為後續研究可改善的 項目與方向：

1. 超音波感測器模型演化

在不同的環境中，如障礙物充斥的環境中，超音波感測器模型需要進 行加以改良，增強其建圖能力。

2. 多種感測器結合

複雜的環境類型特別是牆角及轉角處對超音波而言，容易產生多重反 射，增加辨識的困難度，因此在未來應增加其它種類的感測器作為輔助，

如影像類之感測器，使自走車能夠充分得到更完整的環境資訊。

3. 自走車控制

由於自走車於行走過程中容易有偏移的現象，導致其自走車所認定的 自身座標與真實環境並不符合，存在偏移量，希望能加入 ICP(Iterative Closest Point)等演算法修正自走車在移動過程所造成的偏移量，使其正 確。

4. 地圖維度

因真實環境屬於三維的立體空間，若僅使用平面超音波的量測，僅能 判斷在特定高度時的牆面型態，且二維地圖亦無法完全說明三維空間的資 訊，而環境誤判及偵測死角可能會造成自走車受困，故未來可朝三維空間 地圖建構為方向努力。

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