A robot learning from demonstration framework for skillful small parts assembly

Increasing demand for higher production flexibility and smaller production batch size pushes the development of manufacturing industry towards robotic solutions with fast setup and reprogram capability. Aiming to facilitate assembly lines with robots, the learning from demonstration (LfD) paradigm has attracted attention. A robot LfD framework designed for skillful small parts assembly applications is developed, which takes position, orientation and wrench demonstration data into consideration. In view of constraints in industrial small parts assembly applications, two cascaded assembly polices are learned from separated assembly demonstration data to avoid potential under-fitting problem. With the proposed assembly policies, reference orientation and wrench trajectories are generated as well as coupled with the position data. Effectiveness of the proposed LfD framework is validated by a printed circuit board assembly experiment with a torque-controlled robot.