本論文整合智慧工廠中的自主移動機器人（AMR）與機械手臂系統，應對工廠自動化挑戰，搭配光學雷達(LiDAR)，利用SLAM建構出工廠地圖，並使用AMCL來實現機器人在地圖中的自主定位，ROS2和Navigation2架構建立了一個完整的AMR導航系統，實現AMR在智慧工廠中的路徑規劃和避障功能。由於AMR重複精度問題會影響機械手臂取物精準度，因此機械手臂結合深度攝影機和AprilTag定位技術，取得標記姿態後，進行座標轉換到機械手臂座標系，達到約±0.1 mm的精準定位，實現自動化試片取放料。此外導入5G企業專網及資料分散式服務（DDS），確保系統內資訊的高效流通和機台及機器人的自主運作。 本研究旨在提升AMR在智慧製造中的效能和應用價值，推動製造業的智慧化發展。 ;This thesis integrates autonomous mobile robots (AMR) and robotic arm systems within a smart factory to address automation challenges. Using LiDAR for mapping and AMCL for autonomous localization, a complete AMR navigation system is developed based on the ROS2 and Navigation2 frameworks, enabling path planning and obstacle avoidance within the smart factory. To counteract the impact of AMR′s repeatability accuracy on the robotic arm′s precision in object handling, the robotic arm is combined with a depth camera and AprilTag positioning technology. This integration achieves approximately ±0.1 mm precision by converting the tag′s position to the robotic arm′s coordinate system. Additionally, the implementation of a 5G private network and Data Distribution Service (DDS) ensures efficient information flow and autonomous operation of machinery and robots. This research aims to enhance the performance and application value of AMRs in smart manufacturing, promoting the advancement of intelligent manufacturing in the industry.
