Abstract: As the robot’s working environment becomes more and more complex, through exemplary teaching to them, we can make the robot adapt to its environment faster and better accomplish the missions that humans have given. In the robot’s behavior, the robot arm is indispensable in the robot’s work. In recent years, the modeling and control of robotic arm grabbing has become a hot topic in scientific research. The most cutting-edge methods start with behavior acquisition and behavioral representation. There are roughly two methods for behavior acquisition, one is the real-person teaching method, the other is the virtual platform teaching method, and most of the behavioral characterization uses deep learning method. In this paper, the method of data acquisition is used as an example to review the research and development of manipulator modeling and control in recent years.

Key words: robot arm, modeling, control, imitation, deep learning, real-person teaching