Use Case 2.17: AI & Cloud enabled vision system for agile teach-in of assembly processes
SpinEye - Methodology: HRI that enables humans to “teach” the cobot where to insert screws based on visual inputs from a camera, fast changeover between screw assembly tasks in agile manufacturing, and accurately detecting screw holes utilizing the power of AI. Objectives: O1: To create an AI-enabled vision-based system for robust detection of screw positions. O2: To build a teach-in interface for human-robot collaboration. O3: To build an Edge device for machine vision tasks incl. a Cloud infrastructure for training. O4: To build a web-based UI for monitoring and continuous enhancement of the hole detection model. O5: To produce a machine vision product with a TRL 7 or higher. O6: To develop a business plan for co-exploitation and a dissemination plan for SpinEye to enter the market.
Some more details about SPINEYE Demonstration
More info: TRINITY Website (SPINEYE)