7.1 結論
同時定位與建圖演算法由於可以解決無網路、無地圖環境相關之機器人探索 之問題，因此被廣為討論。但是一般傳統 SLAM 演算法遇到較複雜之地形時，常 會因為建立之地標具有誤差而導致定位的錯誤，進而影響致整個系統。為了解決 此問題，本論文提出了一個改良型同時定位與建圖演算法，透過特徵比對的方式，
過濾特徵不夠強烈的感測資訊，以減少資料關聯的計算，且因為可以有效減少地 標數量，又能增強更新地標之效果，因此本論文採用三角定位之方法實現機器人 定位，取代傳統 FastSLAM 預測模組。由模擬結果可以證實本論文所提出改良型 演算法有效地改善了機器人原先容易陷入發散的問題，並且確實提升定位與建圖 的精確度以及效率。
透過模擬結果確認改良型演算法之精確度以及效率後，本論文將其演算法實 現於 FPGA 之中，透過全硬體電路設計之方式，建立一個同時定位與建圖的嵌入 式系統。此外，也以 NIOS II 以及市面上電腦以純軟體實現基於本論文所提出之 改良型同時定位與建圖演算法之同時定位與建圖，得以驗證全硬體電路確實可以 縮短運算時間，進而提升同時定位與建圖之效率，達到即時的處理效果，並能有 效結合於機器人之中。
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