研究生: |
柯宏瑨 Ko, Hung-Chin |
---|---|
論文名稱: |
使用機器人視覺及安全軌跡規劃於自動化汽車車門噴塗系統之研究 Study of Automated Car Door Painting System with Robotic Vision and Safety Trajectory Planning |
指導教授: |
陳瑄易
Chen, Syuan-Yi |
口試委員: |
林政宏
Lin, Cheng-Hung 蔣欣翰 Chiang, Hsin-Han 陳瑄易 Chen, Syuan-Yi |
口試日期: | 2023/10/12 |
學位類別: |
碩士 Master |
系所名稱: |
電機工程學系 Department of Electrical Engineering |
論文出版年: | 2023 |
畢業學年度: | 112 |
語文別: | 中文 |
論文頁數: | 57 |
中文關鍵詞: | 機器人視覺 、軌跡規劃 、機械手臂 、工作空間監控 、人機協作安全 |
英文關鍵詞: | Robitic vision, trajectory planning, robot arm, workspace monitoring, safe human-robot collaboration |
研究方法: | 實驗設計法 |
DOI URL: | http://doi.org/10.6345/NTNU202301779 |
論文種類: | 學術論文 |
相關次數: | 點閱:122 下載:10 |
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自工業4.0興起後,機器手臂導入自動化的發展成為智慧製造中不可或缺的一部分,在許多生產或加工的工廠中可以見到機器手臂的應用,由於其具備快速及穩定的優點,使得製造過程得以在更短的時間內得到更好的成果,並大幅減少了人力及時間成本。本論文透過六軸協作型機器手臂整合RGB攝影機與二維光達執行汽車車門自動化噴漆的任務,首先機器手臂根據使用者設定的四個位置拍攝車門的影像,並將其儲存,透過影像拼接技術的幫助,將四張影像根據車門的特徵拼接,藉此得到完整的欲噴塗車門之影像。獲得完整的汽車車門影像後,使用色彩偵測方法將欲噴塗車門之範圍從原始影像中過濾出來,再利用輪廓檢測技術擷取出欲噴塗範圍之內輪廓。軌跡規劃演算法根據內輪廓的大小規劃出若干條車門噴漆之路徑,經過座標轉換將此路徑轉換為機器手臂的末端點座標,使得機器手臂得以根據的軌跡進行噴漆任務。在機器手臂進行噴漆的過程中,由於人類操作員有時需要查看汽車車門是否發生上漆不均勻的情況,為了避免機器手臂在噴塗的過程中發生人機碰撞的情形,透過二維光達監控是否有操作人員進入機器手臂工作範圍的情況,透過安全機制的協助得以避免人機碰撞的問題產生。
Due to the raising of Industry 4.0, the development of automation technology with robotic arms has become the indispensable requirement in modern manufacturing systems. In many production and manufacturing facilities, the application of robotic arms is commonly observed. With the advantages of speed and stability, robotic arms allow manufacturing plants to achieve better results in a shorter amount of time, significantly reducing labor and time costs. This thesis presents a system that utilizes a six-axis collaborative robot integrated with an RGB camera and a 2D LiDAR to perform the task of automating the painting process for automotive doors. The robotic arm captures images of the car door from four user-defined positions and stores them. With the assistance of image stitching technology, the four images are merged based on the features of the car door to obtain a complete image of the door to be painted. After obtaining the complete image of the automotive door, color-based detection is used to filter out the painting area from the door image. Then, contour detection technology is employed to extract the inner contour of the area to be painted. The trajectory planning algorithm generates multiple painting paths for the car door based on the size of the inner contour. After the coordinate transformation, these paths are converted into end-point coordinates for the robotic arm, allowing it to execute the painting task along the planned trajectories. During the painting process, as human operators may need to inspect whether the car door is painted evenly, a 2D LiDAR is used to monitor changes in the surrounding environment. In the case of a human operator entering the working area of the robotic arm, the safety mechanism can be executed to avoid human-robot collisions.
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DOBOT CR5六軸機器手臂規格,資料來源https://www.dobot-robots.com/products/cr-series/cr5.html
IDS RGB攝影機,資料來源 https://en.ids-imaging.com/store/gv-5880cp-rev-2-2.html
GenICam通訊協議,資料來源 https://www.baslerweb.com/zh-tw/learning/genicam-standard/
台灣西克2-D LiDAR規格,資料來源https://www.sick.com/tw/zf/lidar/2d-lidar/tim/tim551-2050001/p/p343045
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