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.

Contact the Toshiba Corporate Research & Development Center

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).