目前智慧型自走車已經被廣泛的使用在各領域中，為了提高人類的居家生活品質，用來輔助人類生活的智慧型自走車也漸漸的開發出來，本論文提出使用類神經網路進行室內環境辨識及導航的工作，自走車使用超音波感測器和電子羅盤來取得環境中的距離和方向，當感測器取得環境的幾何特徵，相關資訊匯入類神經網路進行環境特徵辨識，接著會輸出七種環境基本類型。

環境規劃出2種不同寬度的路口大小，尺寸分別為40公分和60公分2種，接著分別收集資料進行環境辨識工作。根據類神經網路辨識結果可以發現不可辨識之區域，這些地方稱為失敗區域。性能指標提出了信賴度、準確度及有效性來做系統評估。

Nowadays, the mobile robot has been introduced and used widely in many fields. To increase the quality of human life, the intelligent mobile robot has been developed gradually and exercised in order to assist people in their living spaces. The following paper will demonstrate the processes of environmental recognition and navigation by using the neural network into the mobile robot. Moreover, it is significant to build an ultrasound sensor and the electrical compass in a gear to obtain the distance and the direction from the consequence of activities.
There are two different types are described, which are the global and the local navigations. The global navigation is distinct by adapting the routing cost function into the progress, which is aimed to work out the route optimization to follow. However, the local navigation is focused on the exploration in the unknown environment by using the neural network in result of environmental recognition. Thus, the combination of two steps is going to allow the mobile robot to move smoothly and randomly in the indoor areas.

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