Fengming Li

Dr. Fengming Li


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 February 2020 in Applied Sciences
Verified
Journal Article
Open access
PDF file
RSRui Song
Rui Song
FLFengming Li
Fengming Li
TFTianyu Fu
Tianyu Fu
Jie ZhaoJie Zhao
Jie Zhao
At present, the production lines of mobile phones are mainly manual and semi-automatic. Robots are the most important tools used to improve the intelligence level of industry production. The design of an intelligent robotic assembly system is presented in this paper, which takes the assembly of screen components and shell components as examples. There are major factors restricting the application of robots, such as the calibration of diversified objects, the moving workpiece with incomplete information, and diverse assembly types. A method was proposed to solve these technological difficulties. The multi-module calibration method is used to transform the pose relationship between the robot, the conveyor belt, and the two cameras in the robot assembly system. Aiming at a workpiece moving with incomplete information, the minimum matrix method is proposed to detect the position. Then dynamic fetching is realized based on pose estimation of the moving workpiece. At last, the template matching method is used to identify the assembly area of the workpiece type. The proposed method was verified on a real platform with a LINKHOU LR4-R5 60 robot. Results showed that the assembly success rate was above 98%, and the intelligent assembly system of the robot can realize the assembly of mobile phone screens and back shells without any staff.

21 March 2022 in Applied Sciences
Verified
Journal Article
Open access
PDF file
ZWZiyue Wang
Ziyue Wang
FLFengming Li
Fengming Li
MYMen yu
Men yu
TFTianyu Fu
Tianyu Fu
XYXuting Yang
Xuting Yang
RSRui Song
Rui Song
Robot automatic assembly of weak stiffness parts is difficult due to potential deformation during assembly. The robot manipulation cannot adapt to the dynamic contact changes during the assembly process. A robot assembly skill learning system is designed by combining the compliance control and deep reinforcement, which could acquire a better robot assembly strategy. In this paper, a robot assembly strategy learning method based on variable impedance control is proposed to solve the robot assembly contact tasks. During the assembly process, the quality evaluation is designed based on fuzzy logic, and the impedance parameters in the assembly process are studied with a deep deterministic policy gradient. Finally, the effectiveness of the method is verified using the KUKA iiwa robot in the weak stiffness peg-in-hole assembly. Experimental results show that the robot obtains the robot assembly strategy with variable compliant in the process of weak stiffness peg-in-hole assembly. Compared with the previous methods, the assembly success rate of the proposed method reaches 100%.