本篇論文採用一個雷射測距儀做為輪型機器人的感測器，並運用雷射測距儀得到輪型機器人周遭的環境資訊，建立出一個即時的地圖，透過一些影像處理的程序可以得知每一個障礙物的位置、大小和形狀，並測出每一個障礙物的邊角，接著再利用障礙物的邊角找到不會發生碰撞且可以順利到達目標點的路徑，另外也使用了基因演算法來讓整個避障方法更加完善。
為了達到定位的效果，本篇論文使用了一個位置控制器來記錄輪軸旋轉的資料，根據這些資料可以計算出輪型機器人目前的所在位置和方向，使輪型機器人在未知環境中不會迷失且能往目標點移動。
在實驗的部分，做各種不同的場景的模型，輪型機器人可以成功的避過各個障礙物，並順利且精準地到達目標點，這項功能也在研究室中測試，讓輪型機器人扮演運送物品的角色，物品送達後輪型機器人也可以順利的回到原位，驗證了本篇論文所提出的方法的可行性。

It uses a laser range finder as sensor for the wheeled mobile robot (WMR) in this thesis. To apply the environmental data from the wheeled mobile robot around can build a local map immediately. Through some image processing one can realize every obstacle’s position, size and shape. After finding every obstacle’s corners, we use them to find collision-free path to the target. Besides, the genetic algorithm is used to perform the adjustment of the obstacle avoidance.
For positioning the WMR, we record the rotating conditions from wheel axle by using a position controller. Base on the data, we can compute the WMR’s position and direction and make sure that it wouldn’t stray in the unknown area.
In the experiment, WMR can avoid the obstacles successfully and reach the target accurately in different scenarios. This function is applied to take the WMR as a porter who would return the former place after delivering the article.

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