最近幾年，愈來愈多研究者投入自主性機器人的相關研究；在這些機器人中，譬如辦公室機器人、娛樂關懷型機器人、居家安全型機器人等，它們可以協助人們做日常生活中的事情。而機器人在室內環境導航的相關研究議題有：環境的感知、定位、路徑規劃、地圖建立、行動的執行…等等。在室內的環境中，準確且安全地的移動是這些機器人導航的重要基本能力之一。本論文的目的，就是要讓機器人可以知道自己的位置與周遭障礙物的遠近距離，進而能避免發生碰撞地閃開障礙物。

在我們建構的機器人裡，立體視覺系統在導引中扮演著重要的角色，而超音波系統則是扮演著協助機器人能安全地移動。在導引的過程中，我們利用立體視覺與已知地標來定位出機器人的位置。在障礙物偵測中，我們結合影像的邊緣與顏色特徵來偵測障礙物；在實驗的環境裡，我們使用特定顏色的圓錐作為障礙物。在取得立體視覺與超音波感測器於環境中的資訊後，機器人可以規劃它的區域路徑，這個規劃後的路徑可以讓機器人安全地且正確地行走，而當機器人到達我們設定的目的地時，它會停止行走並結束導航的動作。

經由我們的實驗獲得，全域的定位結果其角度的相對誤差範圍介於0°~10.4°，側面距離的相對誤差範圍介於0~0.21 m，而深度距離的相對誤差範圍介於0.05~0.12 m。這些準確的全域定位結果，可以充份地提供給區域路徑規劃作為導引機器人於室內環境中安全行走，且使其能航行於預期的軌道上。

In recent years, there have been more and more researchers taking interest in the development of autonomous mobile robots. These robots can help people in daily life, such as office robot, entertainment robot, and security robot. There are many issues; for example, perception of environments, localization, path planning, map building, and execution action, about the robot navigation in indoor environments. To move accurately and safely in an indoor environment is one of the important functionality of robot navigation. The aim of this thesis is to make the robot can know its location and the position of the obstacles surrounding it, and guide the robot to avoid the obstacles without collision.

On our experimental robot, the stereo vision system plays an important role during the navigation, and the ultrasonic sensors system acts as an assistant to help the robot walking safely. We adopt stereo vision techniques to localize robot's location using the known landmarks when the robot navigates in an indoor environment. In obstacle detection, we combine the edge and color features to detect obstacles; in the experiments, we use the specific colored cones as obstacles. After obtaining the environmental information from stereo vision and ultrasonic sensors, the robot can plan the local path. The planed path can keep the robot moving safely and correctly. Then the robot will stop the navigation if it reaches the destination where we set the place as the goal.

The experiments reveal that the relative error range of the global localization results is about 0°~10.4° for the orientation, 0~0.21 m for the lateral location, and 0.05~0.12 m for the depth location. These global localization results are sufficient to provide for the local path planning which can guide the robot to move safely and to keep it on the expected trajectory in an indoor environment.

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