A peg-in-hole robot assembly system based on Gauss mixture model

Using robots to assemble parts has always been a research hotspot, but the traditional analysis model of assembly mainly focuses on establishing the linear equation between the feedback force and the relative position of the peg and hole, which leads to high requirements for the material properties and geometric parameters of the assembly parts. In this paper, a new assembly strategy is proposed that learns skills from manual teaching to carry out the assembly process. A Gauss mixture model and regression is used to fit the teaching data, and then, the compliance control method is applied to conduct assembly when the geometric profile parameters and material elastic parameters of the assembly are inaccurate. Finally, the experiment was implemented under the tolerance is 0.18 mm, and the success rate reaches 100%. These findings verified the effectiveness of the compliance control method.