Learning from demonstration enabled robotic small part assembly

Abstract

The small parts assembly process is a complex but necessary task in the modern manufacturing industry. It is not easy to use industrial robots to afford this task because different control modes and coordination algorithms have to be designed and updated periodically to adapt the rapidly changing products. It is desired to improve the conventional robot programming technology. The concept of Learning from Demonstration(LfD) is adopted and a LfD framework for small parts assembly problem is proposed in this paper. We categorize the robot control modes into Position Control(PC), Force Control(FC) and Hybrid Control(HC) and formulate the small parts assembly skill learning problem into control mode identification and coordination problem. By recording the human teacher's demonstration and learning the control modes and mode switching conditions from the records, the robot is able to imiate the small parts assembly skill autonomously. According to this framework, a LfD method is specifically designed for the semi-structured phone cover assembly platform. The experimental results verify the effectiveness of the proposed algorithm. This method can be implemented in different small part assembly applications, releasing the human workers from the dull and repetitive jobs and improving the productively.