Intelligent task robot system based on process recipe extraction from product 3D modeling file

This study introduces intelligent task robot system based on process recipe extraction from standard 3D model files. In small quantity batch production and mixed flow manufacturing condition, lots of time is spent on process planning and device control such as path planning in a robot system. If these processes could be automated, mixed flow production of various products will be working efficiently. This paper suggests automated process recipe extraction module based product registration subsystem and visual servoing based intelligent assembly task robot subsystem. The recipe module extracts list of parts, each part size and position from standard 3D model file (STEP) and analyzes the structure of product between parts. The extracted product data is stored in the recipe knowledge base as a recipe format and also plan-view image of each part. Robot system consists of real-time part recognition module, part scheduling module and motion planner module. The part recognition module identifies parts by matching real-time RGB image and plan-view image in knowledge base. The part scheduling module plan the sequence of part for task using a decision tree method. The motion planner module controls assembly task robot according to process recipe depending on task type. Performance of the system was tested with five types of sample products.