機器人與智慧3D視覺：以工廠快速換線與隨機堆疊取料為例

Robots and Intelligenct 3D Vision: An Example in Rapid Line Change and Random Bin Picking

蔡承翰 ； 洪國峰

《機械工業雜誌》 436期 (2019/07) Pp. 55-62

摘要

根據IFR統計全球機器人每一萬名員工使用機器人的密度已大幅成長，又以汽車、電子、金屬生產加工為大宗，在工廠大幅採用機器人生產的過程中，配合產線訂單進行快速換線調整以及二十四小時不間斷進行機器人上下料以維持產線連續運轉為一大訴求。本文闡述透過人工智慧演算法進行2D圖像像素等級的對位匹配分割，僅需一個工作天就可對工件進行事先的學習與訓練。結合3D視覺，最終可預估6自由度機械手臂取得工件的姿態，並針對工件隨機堆疊於料籃中進行智慧自動化機器人取料，以期望提供相關業者發展參考之。

關鍵字

人工智慧 ； 隨機堆疊取料 ； 3D視覺

並列摘要

According to the International Federation of Robotics (IFR), the average robot usage density has grown to one robot per 10,000 employees in manufacturing. Robot usage is especially high in automotive, electronics, and metal industries. Rapid line change and 24-hour continuous operation have been major goals in robotic automation. However, current loading and unloading robots still rely heavily on structured environment and human tuning, thus resulting in long line change time. To remedy the issue, we propose an artificial intelligence-based algorithm to perform object pose estimation and robot picking or randomly stacked parts using 6 DOF robots. This algorithm first performs a learning-based object segmentation and then performs a 3D object pose estimation and grasping point determination.

並列關鍵字

Artificial intelligence(AI) ； Random bin picking(RBP) ； 3D vision