Configuration Analysis and optimization of Collaborative Robots

The configuration of collaborative robots is analyzed and optimized based on the Kriging model. First, through analyzing configurations of the existing collaborative robots, it can be seen that the offset is an important factor affecting the configuration, which is divided into S type and Y type by the influence on the range of motion of the joint. Then, based on the Kriging model, the multi-objective optimization function is established, which takes the length and offset of each link as parameter variables and regards the global performance index, the workspace volume index and the workspace dexterity performance index as optimization objective. And the influence of the link and offset parameters of the robot on the robot performance index is analyzed. In the end, the pareto optimal solution set and the optimization configurations are obtained using multi-objective genetic algorithm, and the performance is improved, the solution provides theoretical basis for the configuration design of collaborative robots.