Toshiba AI Technology Catalog

• Welding process automation/optimization
• Laser processing automation/optimization

• Can optimize controls without system modeling by a specialist or teaching by an expert because it learns control methods for minimizing error of bead width through trial and error on a simulator.
• Uses an original learning method (a new reward definition and a learning parameter update method) because welding speed cannot be optimized by applying conventional reinforcement learning methods.

Inquiries to Toshiba Corporate Laboratory (Komukai region)

Please include the title “Toshiba AI Technology Catalog: Laser welding control technology using reinforcement learning” or the URL in the inquiry text.
Please note that because this technology is currently the subject of R&D activities, immediate responses to inquiries may not be possible.

References:

• T. Kaneko, G. Minamoto, Y. Hirose and T. Sakai, "Reinforcement Learning for Laser Welding Speed Control Minimizing Bead Width Error", 2023 IEEE International Conference on Robotics and Automation (ICRA).