| Abstract: | 本論文主要是應用德州儀器的數位訊號處理器TMS320C6713、視覺模組VM480CCD及相關軟體系統(Code Composer Studio)，實現以類神經網路定位目標物體之主動視覺系統，並導引人形機器人與執行足球罰踢。此研究內容主要由四個部分整合實現，其分別為人形機器人的步態規劃、視覺影像的處理、類神經網路定位及導引人形機器人的策略，完成人形機器罰踢足球之任務。
首先由CCD視覺模組將擷取到的影像輸入到TMS320C6713，以進行包括二值化、中值濾波器去除雜訊、影像修正、計算面積與目標物中心點位置的影像處理，接著以類神經網路建立影像座標平面與世界座標之關係(或轉換)，正確計算出目標物體與人形機器人的相對方位與距離，進而導引人形機器人走向目標物的所在位置。當機器人到達目標物附近約10公分後，視覺系統將會開始搜尋球門並且定位虛擬目標位置，以進行機器人罰踢的姿態修正，當姿態修正完成後，則開始執行罰踢的任務。
由於影像視覺系統最重要的卽是目標物位置定位的準確性，因此本論文選用以類神經網路來定位，將影像視覺投影所形成的影像平面轉換到世界座標，進而導引人形機器至所規劃的姿態(卽方位與距離)。運用所開發的圖形化之人機介面，設計與規劃導引人形機器人所需要的不同動作，並且將影像視覺系統與人形機器人核心系統以RS232方式互相傳輸資料，實現本論文之任務。最後我們以相關的實驗驗證本論文之有效性及效率性。
This thesis is to use the Texas Instruments TMS320C6713 digital signal processor, the vision module VM480CCD, and the related software systems (e.g., Code Composer Studio) to obtain the task of the penalty kick of a humanoid robot by using neural network based localization. In this thesis, there have four parts: the path planning of gait, the image processing, the modeling using neural network, and the strategy for visual navigation, to execute the task of the PK for an HR.
First, the CCD module will capture the visual image, which is transferred to the TMS320C6713 for the image processing, including binary segmentation to reduce the storage and computation load, median filter to remove noise, image restoration to improve the accuracy, and calculation of the target position. The modeling using neural network is applied to establish the relationship between the image plane coordinate and the world coordinate. When the robot reaches in the vicinity of target (i.e., about 10 cm), the visual system starts searching the gate and the virtue target point to modify the posture of the HR for the PK. After the posture revision, a fine visual window is employed to confirm the posture for the PK.
The most important thing for vision system is the accuracy of localization. Therefore, a neural-network-based active embedded vision system is developed to approximate the relation between the world coordinate and the image plane coordinate. An interface for man and machine is also applied to design the desired motion of the HR, to connect the signal between the embedded vision system TMS320C6713 and the central embedded system RB-100, and then to navigate the HR to the planned posture for the PK. Finally, the corresponding experiments for the PK of an HR confirm the effectiveness and efficiency of the proposed system. |
