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昆明冶金职业大学学报 ›› 2026, Vol. 42 ›› Issue (3): 51-.DOI: 10.3969/j.issn.1009-0479.2026.03.008

• 机械设计制造与自动化技术 • 上一篇    下一篇

YOLO检测算法在工业机器人装配作业中的应用

  

  1. (昆明冶金职业大学a.电气与机械学院;b.实训创新创业学院;c.教务处,云南昆明650033)
  • 出版日期:2026-08-31 发布日期:2026-09-04
  • 作者简介:李广伟(1987-),男,河南周口人,讲师,工学硕士,主要从事工业机器人、嵌入式软硬件开发与研究。
  • 基金资助:
    昆明冶金高等专科学校科研基金项目“基于ROS的轮式自主移动机器人设计与路径规划研究” (2024xjz05);
    云南省教育厅科学研究基金项目“低空遥感数据采集的无人机快速充电和中继策略研究”(2021J0943)。

Application of YOLO Detection Algorithm in Industrial Robot Assembly Operations

  1. a. Faculty of Electrical and Mechanical Engineering; b. Faculty of Training and Innovation and Entrepreneurship; c. Academic Affairs Office, Kunming Metallurgy University, Kunming 650033, China

  • Online:2026-08-31 Published:2026-09-04

摘要: 本文基于工业机器人智能检测与装配工作站实训平台,针对工业机器人开展 “关节模型” 装配作业过程中遇到的零件类别、颜色识别问题,聚焦 YOLO 算法在工业机器人装配作业中的创新应用,完成了零部件种类、颜色及输出法兰轴线夹角的高效精确识别实验,验证了 YOLO 检测算法在工业机器人装配作业中具备广泛的应用潜力。识别结果通过局域网直接与工业机器人(ABB IRB 120)交互,显著提升了装配效率与产品质量一致性。

关键词: 工业机器人, 机器视觉, YOLO目标检测

Abstract:

Based on the Intelligent Inspection and Assembly Workstation Training Platform for Industrial Robots, this paper addresses the challenges of part category and color recognition encountered during the "articulated model" assembly process of industrial robots. Focusing on the innovative application of YOLO algorithm in industrial robotic assembly operations, we conducted high-efficiency and high-precision recognition experiments for component types, colors, and output flange axis angles. The results validate that the YOLO detection algorithm demonstrates extensive application potential in industrial robotic assembly tasks. The recognition outcomes are directly communicated with the industrial robot (ABB IRB 120) through LAN, significantly enhancing assembly efficiency and quality consistency.

Key words:  industrial robot, machine vision, YOLO object detection

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