基於模型分析與曲線擬合之去毛邊工序3D軌跡線上提取技術及其應用

3D Trajectory Recognition Method and Its Application for Deburring Process Based on CAD Analysis and Curve Fitting

黃成凱 ； 陳祉翔 ； 麥朝創

《機械工業雜誌》 468期 (2022/03) Pp. 65-75

摘要

目前自動化去毛邊大多以離線編程方式產生加工軌跡，但礙於機械手臂不具有良好的精度、且工件尺寸存在誤差而容易使加工結果不如預期，因此大多仍以人力執行為主。本文提出去毛邊軌跡提取方法，以曲線擬合方式進行毛邊檢測並產生加工路徑：透過線性輪廓掃描感測器，取得輪廓二維資訊並與CAD模型比對進行曲線擬合以檢測毛邊位置並產生加工軌跡，解決現有方法須人工調教或3D點雲分析耗時而無法即時追蹤之限制，即時補償路徑與尺寸偏差提升加工品質。

關鍵字

自動化去毛邊 ； 線上軌跡識別 ； 隨機抽樣曲線擬合

並列摘要

Currently, most of the automated deburring trajectories are generated by the offline programming method, but the process results are not as expected due to lack of accuracy of the robotic arm, and the workpiece dimension errors. Hence the deburring process still relies on manpower. This article proposes a deburring trajectory generation method to detect the burr region and generate the trajectory by curve fitting: (1) using a linear contour scanning sensor to obtain the 2D contour information; (2) comparing with the CAD model to detect the burr position then generate the processing trajectory. This method solves the limitations of the existing methods that require manual adjustment or 3D point cloud analysis that is time-consuming and cannot be tracked in real time. The trajectory and workpiece dimension deviations can be compensated in real-time to improve the processing quality.

並列關鍵字

Automatic deburring ； On-line trajectory recognition ； Random sampling curve fitting

參考文獻

International Federation of Robotics, World Robotics Report 2019, 2019.

International Monetary Fund, World Economic Outlook, 2019.

Y. Gu, “Deburring device including visual sensor and force sensor,” US Patent 9724801, June 2013

A. Kuss and M. Drust, AlexanderVerl, “Detection of workpiece shape deviations for tool path adaptation in robotic deburring systems,” Procedia CIRP 57, 545-550, 2016.

F. Leo Princely T. Selvaraj, “Vision Assisted Robotic Deburring of Edge Burrs in Cast Parts,” Procedia Engineering 97, 1906-1914, 2014.