This seminar explores the intersection of machine learning and robotic fabrication, focusing on real-world applications in material manipulation, computer vision, and adaptive workflows. The course covers key ML techniques such as computer vision, reinforcement learning, and generative AI, applied to applications such as robotic assembly, 3D vision, and real-time fabrication processes. By the end of the seminar, students will have developed a working ML model integrated with a robotic fabrication task within the ROS framework.

Learning Objectives
By the end of this workshop, students will be able to:

• Understand how to use the full range of the software stack from previous seminars
• Understand how ML techniques apply to robotic fabrication workflows.
• Utilize computer vision and 3D sensing for robotic perception.
• Design ML models for material-aware fabrication and robotic control.
• Collaborate in teams to develop and present an ML-driven fabrication prototype.

Keywords

• Machine Learning in Fabrication
• Machine Learning for Robotics
• Computer Vision & 3D Sensing
• Reinforcement Learning for Automation

Hardware / Software requirements 

Linux Ubuntu 20.04 or higher