本論文提供ㄧ基於已確立之超音波感測器模型並配合感測器融合技術，用以改進障礙物格狀地圖建立之方法。首先，對配置在Pioneer P3-DX Mobile Robot上的超音波感測器，進行實驗測試與數學推論以建立適當的感測器模型。用以在偵測障礙物空間時，給定地圖中網格一機率值，來表示該網格存在障礙物之可能性。 再利用Dempster-Shafer 理論進行感測器融合，將網格機率加以結合、運算得出一新機率值，進一步確認該網格存在障礙物之機率。 隨著機器人移動，地圖內格點資訊不斷地被計算更新。最終便可描繪出一未知環境的輪廓，獲得一正確、完整障礙物格狀地圖，以用於自主機器人之定位、導航等。 This paper provides a sensor fusion approach to improve the accuracy in building an occupancy map based on an established ultrasonic sensor model. We first construct a sensor model for the ultrasonic range finders mounted on the Pioneer P3-DX mobile robot by experimental test and mathematical reasoning. Based on the sensor model established, a probability can be assigned to each cell of the grid map that represents the possibility of obstacles. Second, by using sensor fusion technique, like Dempster-Shafer theory, probabilities of the cells can be combined to derive a new probability for representing the cell. As mobile robot moves, the probability of cell will be updated continuously. Finally, a complete occupancy grid map for the unknown environment can be established for use in navigation of the autonomous robot.
