This paper presents an innovative autonomous mobile spray painting system that integrates a MiR200 mobile platform with a UR10 collaborative robotic arm, offering a flexible, reconfigurable solution for large-scale industrial painting tasks. Designed to address the limitations of traditional stationary systems, the robot combines mobility, precision, and modularity to paint complex components like wind turbine blades and glider wings efficiently and with high quality. By incorporating advanced features such as onboard power supplies, pneumatic systems, and safety mechanisms, the system operates autonomously in dynamic environments while ensuring seamless collaboration with human workers. Its adaptability allows for quick reprogramming and deployment across various production layouts, making it ideal for low-volume, high-cost manufacturing scenarios. The paper highlights the system’s transformative potential in industrial automation and explores future directions, including fleet-level coordination, AI-driven navigation, sustainability improvements, and broader applications such as cleaning and inspection. This research demonstrates how autonomous mobile robots can revolutionize industrial processes while advancing smart manufacturing practices.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Spray Painting AMR System

  • Grzegorz Iskierka,
  • Bartosz Poskart,
  • Kamil Krot,
  • Paweł Krowicki

摘要

This paper presents an innovative autonomous mobile spray painting system that integrates a MiR200 mobile platform with a UR10 collaborative robotic arm, offering a flexible, reconfigurable solution for large-scale industrial painting tasks. Designed to address the limitations of traditional stationary systems, the robot combines mobility, precision, and modularity to paint complex components like wind turbine blades and glider wings efficiently and with high quality. By incorporating advanced features such as onboard power supplies, pneumatic systems, and safety mechanisms, the system operates autonomously in dynamic environments while ensuring seamless collaboration with human workers. Its adaptability allows for quick reprogramming and deployment across various production layouts, making it ideal for low-volume, high-cost manufacturing scenarios. The paper highlights the system’s transformative potential in industrial automation and explores future directions, including fleet-level coordination, AI-driven navigation, sustainability improvements, and broader applications such as cleaning and inspection. This research demonstrates how autonomous mobile robots can revolutionize industrial processes while advancing smart manufacturing practices.