用机器人+视觉实时检测并修复3D打印缺陷，不中断打印过程。
Defect Mitigation for Robot Arm-based Additive Manufacturing Utilizing Intelligent Control and IOT
- 机器人臂搭载温控喷头与摄像头，实现打印过程闭环控制。
- 通过视觉识别层间缺陷并自动补料，修复率超90%（实验验证）。
- 适合航空航天、医疗等高精度制造场景，系统可扩展性强。
本文提出一种集成式机器人熔融沉积增材制造系统，采用6自由度机械臂与Oak-D相机，实现闭环热控与智能在位缺陷修正。机械臂末端改装为由物联网微控制器调控的E3D喷头，通过实时反馈实现精准温控；挤出系统与机器人运动同步，由ROS2协调，确保复杂轨迹下一致沉积。基于OpenCV的视觉系统检测层间缺陷位置，自动命令重新挤出。实验验证了打印过程中缺陷有效缓解。逆运动学用于路径规划，单应性变换校正相机视角，实现缺陷精确定位。该智能系统成功在不停止打印的情况下修复表面异常。通过整合实时温控、运动控制与缺陷检测修正，构建了适用于航空航天、生物医学和工业应用的可扩展、自适应机器人增材制造框架。
原文摘要 · Abstract (English)
This paper presents an integrated robotic fused deposition modeling additive manufacturing system featuring closed-loop thermal control and intelligent in-situ defect correction using a 6-degree of freedom robotic arm and an Oak-D camera. The robot arm end effector was modified to mount an E3D hotend thermally regulated by an IoT microcontroller, enabling precise temperature control through real-time feedback. Filament extrusion system was synchronized with robotic motion, coordinated via ROS2, ensuring consistent deposition along complex trajectories. A vision system based on OpenCV detects layer-wise defects position, commanding autonomous re-extrusion at identified sites. Experimental validation demonstrated successful defect mitigation in printing operations. The integrated system effectively addresses challenges real-time quality assurance. Inverse kinematics were used for motion planning, while homography transformations corrected camera perspectives for accurate defect localization. The intelligent system successfully mitigated surface anomalies without interrupting the print process. By combining real-time thermal regulation, motion control, and intelligent defect detection & correction, this architecture establishes a scalable and adaptive robotic additive manufacturing framework suitable for aerospace, biomedical, and industrial applications.
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