Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 06, 2021 - June 08, 2021
This paper aims to build dexterity into a machine. Specifically, we will focus on fitting precision parts, which is considered difficult with the current technology, eliminate "assembly failure" such as biting of shafts and holes due to machine learning, and aim to reduce total assembly time. In the final evaluation, the robot incorporating the appropriate control law and machine learning system performs the reducer assembly work, and determines whether the work time can be shortened or the assembly failure can be eliminated compared to experienced personnel. By advancing this research, I think that one assembly robot will be able to flexibly handle various tasks in the future. My ultimate goal is to create an assembly robot that is versatile and can do all the work without failure. This will solve problems such as "high installation costs", "difficult to set for each product", and "assembly work that cannot be automated".
